The Impacts of Learning and Digital Platforms & ICTs on the Success of Women Entrepreneurs... by ACPIL

The Impacts of Learning and Digital Platforms & ICTs on the Success of Women Entrepreneurs in Communities of Practice in South-East Wales A doctoral dissertation by

Dr Florica Tomos

Submitted to the Faculty of Business, University of South Wales, UK in fulfilment of the requirements for the degree Doctor of Philosophy

ISBN: 978-1-912764-66-2 CopyrightÂŠ Florica Tomos Licence to publish granted to Academic Conferences and Publishing International Limited, 2020 For more information see www.academic-conferences.org

THE IMPACTS OF LEARNING AND DIGITAL PLATFORMS & ICTs ON THE SUCCESS OF WOMEN ENTREPRENEURS IN COMMUNITIES OF PRACTICE IN SOUTH-EAST WALES

FLORICA TOMOS

A thesis submitted to the Faculty of Business & Society at University of South Wales in fulfilment of the requirements for the degree of DOCTOR OF PHILOSOPHY

Faculty of Business & Society University of South Wales, Cardiff, United Kingdom

September 2019

ABSTRACT There is little research on women entrepreneurship, with fragmented analyses concerning the impact of learning and digital platforms & ICTs on women entrepreneurs’ chances of success. There is also very little research on Communities of Practice (CoPs) and the effects of networking on women entrepreneurs’ success (WES). In order to address these gaps in knowledge, this thesis explores the impacts of learning and digital platforms & ICTs on WES, and how these effects are mediated through CoPs and networking. In order to do this, a comprehensive positivist, hypotheses testing approach of women entrepreneurs in South East Wales is adopted. The study uses Mixed Method Research (MMR) and statistical techniques such as exploratory factor analysis (EFA), regression, correlation, exploratory research and descriptive statistics. The author conducted a survey with 150 questionnaires, 37 semi-structured interviews and a Focus Group with five women entrepreneurs. The results of this research suggest that, learning and digital platforms & ICTs have a significant impact on WES, and the impact is controlled by CoPs & networking. The research discovered two important aspects. The first aspect revealed by the research is that, the main methods of learning for women entrepreneurs were ‘experience-based’ (trial and error), and ‘multiple methods’ such as role model, asking, doing and applying; and the main learning requirements were digital platforms, marketing, sales and promotion.

The second aspect is that, the styles of learning were interactive and

networking, using digital platforms & ICTs (in particular, Facebook, YouTube and iPhone). The author combined these findings and developed the “Theoretical Business Model for Women Entrepreneurs” and the “Andragogical Model of Learning for Women Entrepreneurs”. The thesis contributes (1) a theoretical business model for women entrepreneurs’ success, (2) an andragogical learning model for women entrepreneurs, and (3) a new conceptual framework for women entrepreneurs’ success, (4) a theoretical framework, together with an (5) innovative operationalization of the constructs. The implications of this research are for women entrepreneurs, entrepreneurial academic research, Higher Education Institutions (HEIs), Government, practicians, educational academic research, consultants and policy makers.

TABLE OF CONTENT ABSTRACT......................................................................................................................3 LIST OF TABLES............................................................................................................9 LIST OF FIGURES.........................................................................................................12 LIST OF JOURNALS.....................................................................................................14 DEDICATIONS..............................................................................................................16 ACKNOWLEDGEMENT...............................................................................................17 CERTIFICATE OF RESEARCH....................................................................................18 THE AUTHOR................................................................................................................19 LIST OF ABBREVIATIONS.........................................................................................24 CHAPTER ONE: INTRODUCTION TO THESIS (p. 25) 1.1 Introduction to Chapter 1...........................................................................................25 1.2 Background and Rationale of the Research...............................................................26 1.3 Aims and Objectives..................................................................................................28 1.4 Research Methods......................................................................................................29 1.5 Key Terms Defined....................................................................................................31 1.6 Structure of the Thesis...............................................................................................33 1.7 Contribution to Knowledge.......................................................................................35 1.8 Limitation of Scope...................................................................................................36 1.9 Summary of the Chapter............................................................................................36 CHAPTER TWO: LITERATURE REVIEW (p. 38) 2.1 Small Businesses, Women Entrepreneurs, Success and Growth……………………39 2.1.1 Introduction……………………………………………………………………………………....39 2.1.2 SMEs in the United Kingdom……………………………………………………………………41 2.1.3 SMEs & Women Entrepreneurs in South East Wales, the UK…………………………………..44 2.1.4 Women Experience as Entrepreneurs……………………………………….................................46 2.1.5 Entrepreneurs and Entrepreneurship………………………………………………………………48 2.1.6 The Phenomenon of Women’s Entrepreneurship…………………………………………………51 2.1.7 Business Growth and Women Entrepreneurs’ Success……………………………………………55

2.2 A Perspective on Learning….....................................................................................59 2.2.1 Learning and Women’s Opportunity…………………………………………………………….60 2.2.2 Learning Process. Methods & Styles of Learning……………………………………………….61

2.2.3 Models of Learning……………………………………………………………………………….63 2.2.4 Entrepreneurial Learning…………………………………………………………………………65

2.3 Communities of Practice and Networks.....................................................................68 2.3.1 Introduction…………………………………………………………………..............................68 2.3.2 How Women Learn and How Digital Platforms Support their Learning……………………….71

2.4 Digital Platforms & ICT.............................................................................................73 2.4.1 Introduction……………………………………………………………………………………..73 2.4.2 ICTs, Digital Platforms and M-learning for women entrepreneurs……………………………..73

2.5 Summary of the Literature Review………………………………………………….77 CHAPTER THREE: RESEARCH FRAMEWORKS (p. 79) 3.1 Introduction to Chapter 3...........................................................................................80 3.2 Theoretical Research Framework………………………………...............................82 3.2.1 Entrepreneurship Theory……………………………………………………...............................82 3.2.2 Learning Theories………………………………………………………………………………..87 3.2.3 Social Capital Theory……………………………………………………………………………91 3.2.4 Theoretical Research Framework……………………………………………………………….95

3.3 Conceptual Research Framework……………………………………………..........98 CHAPTER FOUR: RESEARCH DESIGN & METHODOLOGY (p. 103) 4.1 Introduction to Chapter 4.........................................................................................104 4.2 Research Problem & Philosophy.............................................................................107 4.3 Researcher’s Philosophical Perspective..................................................................110 4.4 The Rationale and Implications of Using Mixed Paradigms...................................113 4.5 Research Purpose & Types of Research..................................................................115 4.6 Research Approach and Design...............................................................................116 4.7 Research Methods and Methodology......................................................................119 4.8 Sampling Techniques, Samples and Data Collection..............................................125 4.9 Questionnaires Design and Data Collection: Survey, Focus Group, Interviews….131 4.9.1 Data Collection and Pilot Study………………………………………………………………131 4.9.2 Coding and Processing Data…………………………………………………………………..132

4.10 Ethical Concerns....................................................................................................133 4.11 Summary of Chapter 4…………………………………………………………...134

CHAPTER FIVE: QUANTITATIVE DATA ANALYSIS (p. 136) 5.1 Introduction to Quantitative Data Analysis............................................................136 5.2 Descriptive Statistics...............................................................................................138 5.2.1 Displaying and Summarizing Categorical Variables...............................................................138 5.2.1.1 Demographic Data………………………………………………………………….....138 5.2.1.2 Learning……………………………………………………………………………….142 5.2.1.3 Digital Platforms a& ICTs…………………………………………………………….144 5.2.1.4 Communities of Practice and Networks……………………………………………....144 5.2.1.5 Women Entrepreneurs’ Success……………………………………………………....145 5.2.2 Displaying and Summarizing Scale Variables..........................................................................147

5.3 Inferential Statistics: Reliability and Validity in Measurement..............................160 5.4 The Analysis of Relationship between Categorical Variables and the Role of Significance Test...........................................................................................................164 5.5 The Analysis of the Relationship between Scale Variables and the Role of Significance Test...........................................................................................................170 5.6 Partial Correlation Analysis.....................................................................................175 5.7 Introduction to Factor Analysis...............................................................................179 5.7.1 Factor Analysis for Learning……………………....................................................................182 5.7.2 Factor Analysis for Digital Platforms & ICTs……….............................................................187 5.7.3 Factor Analysis for CoPs & Networking.................................................................................191 5.7.4 Factor Analysis for Women Entrepreneurs’ Success...............................................................196

5.8 Factor Analysis. Discussions and Interpretations....................................................200 5.9 Correlations and Regressions..................................................................................202 5.9.1 Introduction to Correlation...................................................................................................203 5.9.2 Correlation Analysis.............................................................................................................205 5.9.3 Simple Regression Analysis.................................................................................................207 5.9.4 Standard Multiple Regressions.............................................................................................211

5.10 Total Factor Extraction and Analysis and Regression Analysis............................214 5.10.1. Multiple Standard Regression Analysis............................................................................217

5.11 Correlation Analysis..............................................................................................225 5.12 Partial Correlation Analysis...................................................................................229 5.13 Summary Chapter..................................................................................................230 CHAPTER SIX: QUALITATIVE DATA ANALYSIS (p. 238) 6.1 Introduction to Qualitative Data Analysis...............................................................239 6.2 Phenomenology and Qualitative Data Analysis......................................................241 6.3 Qualitative Data Analysis: Interviews and Focus Group.......................................242 6

6.4 Qualitative Data Analysis: Focus Group................................................................243 6.5 Interviews Analysis Using IPA and TA..................................................................256 6.6 Data Analysis: Interviews with 37 Women Entrepreneurs. Final Template...........259 6.7 Focus Group and Interviews Content Analyses…………………………………..282 6.8 Summary of Chapter Six.........................................................................................287 CHAPTER SEVEN: DATA INTERPRETATIONS AND DISCUSSIONS (p. 303) 7.1 Introduction to Chapter 7........................................................................................304 7.2 The Analyses of the Relationship/Correlation between Learning, CoPs & networking and WES........................................................................................................................304 7.3 Factors Impacting on Women Entrepreneurs’ Success...........................................309 7.4 Theoretical Contribution of the Thesis....................................................................311 7.5 Models of Learning.................................................................................................313 7.6 Learning and Acquiring Knowledge.......................................................................317 7.7 Validity and Reliability of the Results....................................................................323 7.8 Data Storage and Management................................................................................324 CHAPTER EIGHT: CONCLUSIONS AND CONTRIBUTIONS (p. 325) 8.1 Conclusions.............................................................................................................325 8.2 Main Findings.........................................................................................................329 8.3 Contributions to Knowledge: Theory & Practice...................................................331 8.4 Limitations and Recommendations.........................................................................335 APPENDICES APPENDIX A1: Statistics in Europe & UK.................................................................338 APPENDIX A2: Descriptive Statistics……………………………………………….343 APPENDIX B: Sampling and Data Collection.............................................................352 Frame list with networks and associations with women entrepreneurs.....................................................352 Survey with Questionnaires: Women Entrepreneurs in High Street SE Wales………………………….353 Pilot Study – Feedback on the Questionnaires...........................................................................................355 Statement of Informal Consent...................................................................................................................356 Data Collection – Statistics Table 1 – Table 4...........................................................................................357

Online Survey – Address to Women Entrepreneurs..................................................................................358 Focus Group – Questions...........................................................................................................................359 Interview – Questions.................................................................................................................................360 Focus Group/Interview – Registration Form..............................................................................................361 Interview Invitation....................................................................................................................................361 Focus Group Agenda..................................................................................................................................361 Data Protection Act, 1998 & Research Consent.........................................................................................362 Information for the Participants..................................................................................................................363 Survey Questionnaire.................................................................................................................................365

APPENDIX C: Data Coding..........................................................................................375 Codebook for entreprsurvey.sav Variables Allocation.............................................................................................................................375 List of Variables/Type of Variables.....................................................................................................375 The Coding Frame................................................................................................................................378 Coding Book........................................................................................................................................381 Selected Answers to Open Question (Survey)...........................................................................................498

APPENDIX D: Interviews’ Transcript..........................................................................402 APPENDIX E: Focus Group Transcript…....................................................................419 APPENDIX F: Focus Group Coding Data....................................................................429 REFERENCES References……………….............................................................................................445

List of Tables Table 2.1: Population of active enterprises in industry and services...............................40 Table 2.2: EU definition of SMEs...................................................................................42 Table 2.3: Self-employment situation/categories............................................................55 Table 4.1: Research Methodology.................................................................................104 Table 4.2: Sampling Selection Criteria..........................................................................129 Table 4.3: Data Collection and the Response Rate.......................................................130 Table 5.1: Scale variable: ‘Learning Preferences’.........................................................148 Table 5.2: Scale variable: ‘Styles of learning and doing business’...............................150 Table 5.3: Scale variable: ‘Communities of Practice’...................................................153 Table 5.4: Test of Normality.........................................................................................158 Table 5.5: Scale variable: ‘Impact of various factors on business success’..................159 Table 5.6 Scales.............................................................................................................162 Table 5.7 Reliability Table............................................................................................162 Table 5.8 Crosstabulation..............................................................................................167 Table 5.9 Chi-Square Test.............................................................................................167 Table 5.10 Symmetric Measures...................................................................................167 Table 5.11Crosstabulation.............................................................................................169 Table 5.12Chi-Square Test............................................................................................169 Table 5.13Symmetric Measures....................................................................................169 Table 5.14 Crosstabulation............................................................................................169 Table 5.15 Chi Square Tese...........................................................................................170 Table 5.16 Symmetric Measuers...................................................................................170 Table 5.17 Symmetric Measures...................................................................................170 Table 5.18 The Analysis of Two Scale Variables.........................................................171 Table 5.19 NET & ICTs * CoPs & networking............................................................171 Table 5.20 The Analysis of the Relationship between Two Scale Variables................172 Table 5.21 NET & ICTs * WES....................................................................................172 Table 5.22 Learning Preferences * Impact of various factors on WES........................173 Table 5.23 Correlations.................................................................................................174 Table 5.24 Correlations.................................................................................................174 Table 5.25 EED * CoPs & networking..........................................................................175 Table 5.26: Correlations................................................................................................176 Table 5.27: Summary of the Analysis (Inferential Statistics/Categorical Variables)...177 Table 5.28: Summary of the Exploratory Analysis/Scale Variables.............................177 Table 5.29: Two Factors Extraction Solution EED, KMO and Bartlett’s Test.............183 Table 5.30: Correlation Matrix......................................................................................183 Table 5.31: Two Factors Extraction Solution, EED, Communalities...........................185 Table 5.32: Two Factors Extraction Solution, EED, Component Matrix.....................185 Table 5.33: Two Factors Extraction Solution, EED, Pattern Matrix............................186 Table 5.34: Two Factors Extraction Solution, EED, Structure Matrix.........................186 Table 5.35: Correlation Matrix, NET & ICTs...............................................................188 Table 5.36: Correlation Matrix, NET * ICTs................................................................188 Table 5.37 KMO and Bartlett’s Test, NET & ICTs......................................................188 Table 5.38: Three Factors Extraction Solution, Pattern Matrix, NET & ICTs.............190 Table 5.39: Three Factors Extraction Solution, Structure Matrix, NET & ICTs..........190 Table 5.40: Correlation Matrix, CoPs & Networking...................................................191 Table 5.41: KMO and Bartlett’s Test, CoPs..................................................................191 Table 5.42: One Factor Extraction Solution, Communalities, CoPs.............................192 9

Table 5.43: One Factor Extraction Solution, Component Matrix, CoPs.......................193 Table 5.44: Two Factor Extraction Solution, KMO and Bartlett’s Test, CoPs.............194 Table 5.45: Two Factor Extraction Solution, Component Correlation Matrix, CoPs...194 Table 5.46: Two Factor Extraction Solution, Component Matrix, CoPs......................194 Table 5.47: Two Factor Extraction Solution Pattern Matrix, CoPs...............................195 Table 5.48: Three Factors Extraction Solution, KMO and Bartlett’s Test, WES.........196 Table 5.49: Three Factors Extraction Solution, Component Correlation Matrix, WES...............................................................................................................................196 Table 5.50: Three Factors Extraction Solution, Correlation Matrix, WES ..................196 Table 5.51: Three Factors Extraction Solution, Communalities, WES.........................197 Table 5.52: Three Factors Extraction Solution, Component Matrix, WES...................198 Table 5.53: Three Factors Solution, WES, Pattern Matrix............................................198 Table 5.54: Three Factors Solution, WES, Structure Matrix........................................199 Table 5.55: FA Labels and variances explained by factors within the variables and dataset............................................................................................................................201 Table 5.56A: Correlations, NET & ICTs * WES, NET & ICTs * CoPs & networking.....................................................................................................................205 Table 5.56B: Correlation Analysis................................................................................206 Table 5.57: Descriptive Statistics..................................................................................207 Table 5.58: Coefficients................................................................................................208 Table 5.59: Correlations................................................................................................209 Table 5.60: Model Summary.........................................................................................209 Table 5.61A: ANOVA...................................................................................................209 Table 5.61B: Regression Analysis.................................................................................210 Table 5.62: KMO and Bartlett’s Test, TFAEED...........................................................215 Table 5.63: KMO and Bartlett’s Test, TFANET...........................................................215 Table 5.64: KMO and Bartlett’s Test, TFACPN...........................................................215 Table 5.65: KMO and Bartlett’s Test, TFAMSC..........................................................215 Table 5.66: Assessment of Suitability of Data for TFA................................................216 Table 5.67: Correlations................................................................................................218 Table 5.68: Coefficients................................................................................................218 Table 5.69: Coefficients................................................................................................221 Table 5.70 Model Summary..........................................................................................222 Table 5.71: ANOVA......................................................................................................223 Table 5.72: Correlations TFAEED, Pearson.................................................................226 Table 5.73: Correlations TFA EED, Spearman’s rho....................................................226 Table 5.74: Correlation TFANET, Pearson...................................................................227 Table 5.75: Correlation TFANET, Spearman’s rho......................................................227 Table 5.76: Correlation TFAMSC, TFAEED, TFANET, Pearson...............................228 Table 5.77: Correlation TFAMSC, TFAEED, TFANET, Spearman’s rho...................228 Table 5.78: Descriptive Statistics, TFAEED, TFAMSC, TFACPN.............................229 Table 5.79: Correlations TFAEED, TFAMSC, TFACPN............................................229 Table 5.80: Descriptive Statistics.................................................................................230 Table 5.81 Correlations TFANET................................................................................230 Table 5.82: Summary of the Research Hypotheses, RQ, Statistical Analysis.............232 Table 5.83A: Emergent Hypotheses.............................................................................235 Table 5.83B: New Relationships/Hypotheses Emergent from the Quantitative Analysis.........................................................................................................................237 Table 6.1: Template Analysis, Final Coding Template for the FG...............................243 Table 6.2: Methods of Learning, Illustrations...............................................................248 10

Table 6.3: Styles of learning, Illustrations.....................................................................249 Table 6.4: Preferences for NET & ICTs........................................................................250 Table 6.5: WES, EED, NET&ICTs, Illustrations..........................................................251 Table 6.6: Entrepreneurial Terms, Defined, Illustrations..............................................252 Table 6.7: Networking & CoPs, Illustrations................................................................254 Table 6.8: Entrepreneurial Activity and Gender...........................................................256 Table 6.9: Initial Coding Template, EED......................................................................257 Table 6.10: Initial Coding Template, NET....................................................................257 Table 6.11: Initial Coding Template, WES...................................................................258 Table 6.12: Initial Coding Template, CoPs & Networking...........................................259 Table 6.13: Initial Coding Template, EA & G..............................................................259 Table 6.14: Master Template Design for Theme Validation by Recurrence, EED......260 Table 6.15: The Final Template for the Interviews.......................................................263 Table 6.16: Methods and Styles of Learning, Illustrations, EED..................................264 Table 6.17: Master Template Design for Theme Validation by Recurrence, NET & ICTs...............................................................................................................................267 Table 6.18: Final Coding Template, NET & ICTs........................................................268 Table 6.19: NET & ICTs, Illustrations..........................................................................269 Table 6.20: Master Template Design for Theme Validation by Recurrence, WES......272 Table 6.21: The Final Coding Template, WES.............................................................273 Table 6.22: Women Entrepreneursâ&#x20AC;&#x2122; Success, Illustrations............................................273 Table 6.23: Master Template Design for Theme Validation by Recurrence, CoPs & Networking....................................................................................................................277 Table 6.24: The Final Coding Template, Networking & CoPs.....................................278 Table 6.25: Networking & CoPs, Illustrations..............................................................278 Table 6.26: Master Template Design for Theme Validation by Recurrence, EA & EP/G...............................................................................................................................280 Table 6.27: The Final Coding Template, EA & EP/G...................................................281 Table 6.28: EA & EP/G, Illustrations............................................................................281 Table 6.29 Women Entrepreneurs Learning Methods, Interviews................................283 Table 6.30 Generation Y vs X. Age vs Connectivity...................................................284 Table 6.31 Gender. Reasons for starting Entrepreneurship..........................................286 Table 6.32 Women Entrepreneurs & Children (CA, Is and FG)...................................286 Table 6.33: Emergent Themes from Qualitative Data Analysis (FG & Is)...................295 Table 6.34: Solutions to Research Questions (Q3/Q5/Q6)............................................300

List of Figures Figure 1.1: The Structure of the Thesis………………...................................................37 Figure 2.1: The Structure of Chapter 2............................................................................38 Figure 3.1: Chapter 3.......................................................................................................79 Figure 3.2: The Structure of Chapter 3............................................................................81 Figure 3.3: The Theoretical Research Framework..........................................................97 Figure 3.4: Research Framework for Women Entrepreneurs’ Success.........................101 Figure 3.5: The Research Path.......................................................................................102 Figure 4.1: Chapter 4………………………………………………………………….103 Figure 4.2: The Structure of Chapter 4..........................................................................106 Figure 4.3: Methodological and Methods Framework..................................................123 Figure 4.4: Mixed Methods Framework........................................................................124 Figure 4.5: Research Design Phases..............................................................................135 Figure 5.1: Chapter 5.....................................................................................................136 Figure 5.2: The Structure of Chapter 5..........................................................................137 Figure 5.3: Legal Form and Type of Business..............................................................139 Figure 5.4: Market area of the business.........................................................................140 Figure 5.5: Entrepreneurship courses after starting the business..................................142 Figure 5.6: Type of learner............................................................................................143 Figure 5.7: Participation in Communities of Practice...................................................145 Figure 5.8: Entrepreneurship education enhances business success.............................146 Figure 5.9: Flexible formal learning..............................................................................148 Figure 5.10: Flexible informal learning.........................................................................149 Figure 5.11: Experience-based learning........................................................................149 Figure 5.12: Role model-based learning........................................................................149 Figure 5.13: Attending courses......................................................................................150 Figure 5.14: Learning yourself at home........................................................................151 Figure 5.15: Learning in groups....................................................................................151 Figure 5.16: Learning online.........................................................................................151 Figure 5.17: Learning with ICTs...................................................................................152 Figure 5.18: Doing business with ICTs.........................................................................152 Figure 5.19: Box Plot ‘Participation in CoPs’...............................................................153 Figure 5.20: Participation in CoPs increases knowledge & Normal Q-Q Plot..............153 Figure 5.21: Participation in CoPs facilitates learning from experts & Normal Q-Q Plot.................................................................................................................................154 Figure 5.22: In CoPs I find information to grow my business & Normal Q-Q Plot.....155 Figure 5.23: In CoPs I share knowledge & Normal Q-Q Plot.......................................155 Figure 5.24: Through CoPs I am encouraged to succeed & Normal Q-Q Plot.............156 Figure 5.25: CoPs give me a sense of identity & Normal Q-Q Plot..............................157 Figure 5.26: CoPs are important for business success & Normal Q-Q Plot..................157 Figure 5.27: Box Plot EED............................................................................................159 Figure 5.28: Box Plot NET............................................................................................159 Figure 5.29: Entrepreneurship Education......................................................................160 Figure 5.30A: New Emerging Technologies.................................................................160 Figure 5.30B: Exploratory Model of the Relationship/Categorical/Scale.....................178 Figure 5.31: Scree Plot FA EED ..................................................................................184 Figure 5.32: Scree Plot NET & ICTs............................................................................189 Figure 5.33: Scree Plot CoPs & networking.................................................................192 Figure 5.34: Scree Plot WES........................................................................................197 12

Figure 5.35: The Regression Line.................................................................................210 Figure 5.36: Normal P-P Plot TFAMSC.......................................................................219 Figure 5.37: Scatterplot TFAMSC................................................................................220 Figure 5.38: Scree Plot Matrix TFAEED, TFAMSC, TFANET...................................223 Figure: 5.39: Scree Plot TFAEED, TFAMSC...............................................................223 Figure 5.40: Scree Plot Matrix TFANET, TFAMSC....................................................224 Figure 5.41: Theoretical Business Model for WES, Quantitative Analysis..................236 Figure 6.1: The Structure of Chapter 6..........................................................................238 Figure 6.2: Model 1: Reasons of Enjoyment.................................................................289 Figure 6.3: Model 2: Various Factors Affecting WES..................................................290 Figure 6.4: Model 3: Benefits of Networking & CoPs..................................................291 Figure 6.5: Model 4: Women Entrepreneurs’ Capabilities and Characteristics............292 Figure 6.6: Model 5: Entrepreneurial Activity and Process/ Gender ...........................293 Figure 6.7: Theoretical Model for WES, Qual Data Analysis.......................................297 Figure 6.8: The Andragogical Model for Learning.......................................................299 Figure 6.9: Theoretical Business Model for WES (Final).............................................303 Figure 7.1: The Structure of Chapter 7..........................................................................304 Figure 8.1: The Structure of Chapter 8 ….....................................................................326 Figure 8.2: Theoretical Business Model........................................................................330

LIST OF JOURNALS AER – American Economic Review AE – Applied Economics AJSB – American Journal of Small Business AMJ – Academy of Management Journal AMLE – Academy of Management Learning and Education BHR – Business Harvard Review BMD – Business Management Dynamics CDI – Career Development International EBR – European Business Review ECAM – Engineering, Construction and Architectural Management EDIIJ – Equality, Diversity and Inclusion: An International Journal EE – Education Economics EER – Economics of Education Review EJE – European Journal of Education E+T – Education and Training ET&P - Entrepreneurship Theory and Practice EQI – Equal Opportunities International FA – Foreign Affairs FE – Feminist Economics FT – Feminist Theory GE – Gender and Education GMIJ – Gender in Management: An International Journal GS – Gender and Society GSE – Globalisation, Societies and Education GWO – Gender, Work and Organisation HRMR – Human Resources Management Review IJEBR – International Journal of Entrepreneurial Behaviour and Research ICT – Industrial and Commercial Training IE – Informatica Economica IJEI – International Journal of Entrepreneurship and Innovation IJESB – International Journal of Entrepreneurship and Small Business IJGE – International Journal of Gender and Entrepreneurship IJMP – International Journal of ManPower IJM – International Journal of Marketing IJMM – International Journal of Mobile Marketing IJOPM – International Journal of Operations and Production Management IJPP – International Journal of Productivity and Performance IJTD – International Journal of Training and Development IMDS – Industrial Management and Data Systems IR – International Relations IRRODL – International Review Open Distributed Learning ISBJ – International Small Business Journal IS – International Sociology ISIT – Journal of Systems and Information Technology ITID – Information Technologies and International Development ITP – Information Technology and People JAF – Journal of Applied Finance JBR – Journal of Business Research 14

JBC – Journal of Business Communication JBS – Journal of Business Strategy JD – Journal of Documentation JDS – Journal of Development Studies JEC – Journal of Enterprising Culture JECPPGE – Journal of Enterprising Communities: People and Places in Global Economies JEIT – Journal of European Industrial Training JEIM – Journal of Enterprise Information Management JEL – Journal of Economic Literature JFQA – Journal of Financial and Qualitative Analysis JGE – Journal of Gender and Entrepreneurship JGER – Journal of Global Entrepreneurship Research JIA – Journal of International Affairs JIM – Journal of Interactive Marketing JKM – Journal of Knowledge Management JM – Journal of Marketing JMD – Journal of Management Development JME – Journal of Macroeconomics JMM – Journal of Marketing Management JMP – Journal of Managerial Psychology JMS – Journal of Management Studies JOB – Journal of Organisational Behaviour JOCM – Journal of Organisational Change Management JSBE – Journal of Small Business and Entrepreneurship JSBED – Journal of Small Business and Enterprise Development JSIT – Journal of Systems and Information Technology JSSP – Journal of Sociology and Social Policy JRS – Journal of Rural Studies LO – The Learning Organisation LQ – Leadership Quarterly MF – Managerial Finance MIS – MIS Quarterly MMR – Management Research Review O - Organisation PEF – Proceedia Economics and Finance QRJ – Qualitative Research Journal RWE – Review World Economics ROFCE – Revue de l’OFCE S - Sociology SAM AMJ – SAM Advanced Management Journal SCE – Studies in Continuing Education SP – Social Politics SPR – Social Policy Review SPQ – Social Psychology Quarterly SSCMIJ – Supply Chain Management: An International Journal WMR – Women in Management Review WES – Work, Employment and Society

DEDICATIONS I dedicate this thesis to God Almighty, who helped me along this hard time, towards the completion of the thesis. I dedicate also this thesis to my daughter Ms. Oana Balan MA Costume Design, BSc Fashion Design, BA Textile Design, PGCE, Freelancer and entrepreneur. Thirdly, I wish to dedicate this research to the Community of Women Entrepreneurs from Wales, the United Kingdom, and to Women Entrepreneurs across the Globe.

ACKNOWLEDGEMENT First, I give praises, thanks and Glory to God Almighty and Jesus Christ for helping me along this incredible hard period. Secondly, I wish to express thanks to my supervision team: Dr Andre Clark and Professor Jenny Rowley, for their dedication in supporting and encouraging me along this process towards the achievement of the degree. My special thanks go to Professor Andrew Rogers and the management of Faculty of Business. I am particularly grateful to my friends Roger, Ursula, Robert, Sonia, Kish, Lyl and many others. In addition, I express a very special thanks to Emeritus Professor David Turner for the collaboration and wonderful advice. I also express thanks to my lecturers from PGCE Program at University of Cardiff, who had a decisive role in my formation as a Lecturer. I wish to express my thanks to ACPIL, BERA and HEA for encouragement and awards. I am especially thankful to all women entrepreneur participants, who had the kindness and the willingness to participate in the survey, Focus Group and interviews. Finally, I wish to express my sincere thanks to my family, my husband Mr Clifford Tomos M.Th., B.Th. (Hons) and to my daughter. The author acknowledges that she published materials, related and derived from this thesis. These publications are book chapters and academic papers published by IGI, ACPIL and ISBE and mentioned in the Authorâ&#x20AC;&#x2122;s section.

CERTIFICATE OF RESEARCH This work has not previously been accepted in substance for any degree and is not currently submitted in candidature for any degree. I certify that the work is that of the author except where due acknowledgement has been made. The content of the thesis is the result of work that has been carried out since the official starting date of the approved research program. Any published work related to this research is acknowledged. I confirm that the intellectual content of the work is the result of my own efforts. The copyright of this research belongs to the author under the terms of the United Kingdom and Copyright Acts as qualified by the South Wales University Regulations. The acknowledgement must always be made of the use of any materials comprised in, or derived from this thesis.

X Florica Tomos PhD Candidate

Signed

20.09.2019

Signed Dr Andre Clark

20.09.2019

STATEMENT 1 The thesis is being submitted in fulfilment of the requirements for the degree of PhD. Signed

Florica Tomos

Date 20.09.2019

STATEMENT 2 This thesis is the result of my own independent work, except where otherwise stated. Other resources are acknowledged by explicit references. Signed

Florica Tomos

Date 20.09.2019

THE AUTHOR Florica Tomos is a Fellow of Higher Education Academy and has a passion for andragogy, economics, women entrepreneurship, accounting, management, educational and business research and teaching. She completed with Distinction her BSc (Econ.) at University of Economics, Bucharest in 1985. In 1991, she enrolled on Postgraduate Diploma in Costings and Accounting and completed this with Distinction in 1992. She worked as an Economist for the Ministry of Public Finances, Ministry of Public Health and Food Agency, and as a part time Lecturer. After arriving in the United Kingdom, she worked and studied across a period of sixteen years. She studied English Literature, ECDL and Mathematics and qualified as an Accounting Technician and Teacher. Before enrolling on PhD, she completed PGCE with Merit, at Cardiff University. Along the PhD studies, she worked as a Technology Enhanced Learning Researcher and as a Lecturer for Business Research Methods, at Glamorgan University. Whilst studying at Cardiff University, she participated in a cross-disciplinary research team for the development of SAVI project.

Her research interests are: learning, entrepreneurship education,

educational research, interdisciplinary studies, business start-up, development and growth, entrepreneurship, women entrepreneurs, communities of practice, knowledge management, small businesses, economics, teaching and learning, game-based learning, technology enhanced learning, management, pedagogy and andragogy, e-learning, Mixed Methods Research, digital pedagogy, research methods, assessment and feedback, student learning experience and entrepreneurship innovation. Along her studies on PhD, she participated and published refereed academic research papers within ECEL, ECGBL, ECRM, IISA, ICCITDS, ISBE, BAM, IGI Global USA and EDULEARN. She is an editor and reviewer for the British Educational Research Academy, British Academy of Management, the European Conferences on Game-Based Learning and e-Learning (ACPIL), Bentham Science Publishers, IGI Publishing USA, and two American Journals. In addition, she collaborated with various researchers across the world, and published the following academic papers, journal articles and book chapters: JOURNALS Tomos, F., Shabalina, O., Malliarakis, C., O.C. Balan and Mozelius, P. (2017) â&#x20AC;&#x153;Creativity and Game-Base Learningâ&#x20AC;?, 9th The International Conference on Education and New Learning Technologies, 3-5 July, Barcelona, Spain, EDULEARN Proceedings,

Publisher: IATED Publications, ISBN: 978-84-697-3777-4, 10.21125/edulearn.2017.2534, www.IATED Digital Library.

DOI:

Mozelius, P., Tomos, F., Shabalina, O., Malliarakis, C., Miller, C., Balan, O.C. and Chickerur, S. (2016) “Game-Based Technologies in Teaching Programming in Higher Education: Theory and Practice”, Recent Patent on Computer Science, Vol. 8, Canada: Bentham Science Publishing, ISSN: 2213-2759, 1874-4796 www.benthamscience.com BOOK CHAPTERS Tomos, F., Clifton, N., Balan, O.C., and Hyams-Ssekasi, D. (2019) “Inequalities, a Concern for Capitalism and Global Strategy”, In Tomos, F., Kumar, N., Clifton, N. and Hyams-Ssekasi, D. (Eds.) Women Entrepreneurs and Strategic Decision Making in the Global Economy, USA: IGI Global, ISBN: 978-1-5225-7479-8, eISBN: 9781522574804, ISSN: 2327-3429, eISSN: 2327-3437 https://www.igi-global.com/ DOI: 10.418/978-15225-7479-8ch001, pp. 1-20. Tomos, F., N. Clifton, N., Thurairaj, S. and Balan, O.C. (2019) “Perspectives on Women’s Entrepreneurial Learning and the Evolution of Women Entrepreneurship Research”, In: Tomos, F., Kumar, N., Clifton, N. and Hyams-Ssekasi, D. (Eds.) Women Entrepreneurs and Strategic Decision Making in the Global Economy, USA: IGI Global, ISBN: 978-1-5225-7479-8, eISBN: 9781522574804, ISSN: 2327-3429, eISSN: 23273437 https://www.igi-global.com/ DOI: 10.418/978-1-5225-7479-8ch012, pp. 232-258. Tomos, F. and Thurairaj, S. (2019) “New Emerging Technologies and ICTs and their Impact on Women Entrepreneurs’ Success”, In: Tomos, F., Kumar, N., Clifton, N. and Hyams-Ssekasi, D. (Eds.) Women Entrepreneurs and Strategic Decision Making in the Global Economy, USA: IGI Global, ISBN: 978-1-5225-7479-8, eISBN: 9781522574804, ISSN: 2327-3429, eISSN: 2327-3437 https://www.igi-global.com/ DOI: 10.418/978-15225-7479-8ch008, pp. 144-167. Tomos, F., Shabalina, O., Mozelius, P. and Malliarakis, C. (2017) “Creativity and GameBase Learning”, (the short version of the paper), EDULEARN, 3-5 July, Barcelona, Spain, Publisher: IATED Publications, ISSN: 2340-1117, www.IATED Digital Library. Tomos, F., Andre, C., Thurairaj, S., Balan, O.C., and Turner, D. (2016) “The Emergence of Women Entrepreneurs and Communities of Practice within the Global Context”, In Buckley, S., Majewski, G. and Giannakopoulos, A. (Eds.): Organizational Knowledge Facilitation through Communities of Practices in Emerging Economies, USA: IGI Global, ISSN: 2326-7607, eISNN: 2326-7615, pp. 85-114. DOI: 10.4018/978-1-52251923-2. Ch089, www.IGI Global Publishers. ACADEMIC RESEARCH PAPERS – PEER REVIEWED Tomos, F. and Clark, A. (2018) “An Andragogic Perspective on Women Entrepreneurial e-Learning: Styles and Methods”, 17th European Conference on e-Learning, ECEL Proceedings 2018, 1-2 November, 2018, Athens, Greece, pp. 547-554, In: Ntalians, K., 20

Andreatos, A. and Sgoropoulou, C. (Eds.): Proceedings of the 17th Conference on eLearning, Publisher: Academic Conferences and Publishing International Conferences, Reading, UK, ISBN: 978-1-9127634-07-5, ISSN: 2048-8637, E-Book, ISBN: 978-1912764-08-2, E-Book, ISSN: 2048-8645. Malliarakis, C., Tomos, F., Shabalina, O. and Mozelius, P. (2018) “Andragogy and E.M.O.T.I.O.N.: 7 Key Factors of Successful Serious Games”, 12th European Conference on Game-Based Learning, 4-5 October, 2018, Sophia Antipolis, France, pp. 371-379, In: Ciussi, M. (Ed.): Proceedings of the 12th Conference on Game-Based Learning, Publisher: Academic Conferences and Publishing International Conferences, Reading, UK, ISBN: 978-1-911218-99-9, ISSN: 2049-0992, E-Book, ISBN: 978-1-912768-00-6, E-Book, ISSN: 2049-100X. Shabalina, O., Malliarakis, C., Tomos, F. and Mozelius, P. (2017) “Game-Based Learning to Program: from learning to play to learning through game development”, 11th European Conference on Game-Based Learning, ECGBL Proceedings, 5-6 October, Graz, Austria, pp. 571-576, Publisher: Reading, UK, Academic Conferences and Publishing International Limited, ISSN: 2049-0992 (Sherpa/RoMEO, JCR). Tomos, F., Deacon, J., Balan, O.C. and Clark, A. (2016) “Women Entrepreneurial Success across Europe. A Comparative Study”, ISBE Conference, October, Paris, France. Shabalina, O., Tomos, F., Mozelius, P. and Malliarakis, K., Balan, O.C. and Alimov, A. (2016) “Game-Based Learning as a Catalyst for Creative Learning”, The 10th Conference on Games Based Learning, Paisley, Scotland, 6th-7th October 2016. Proceedings of the 10th Conference on Games Based Learning, Vol 1, pp. 589-598. Tomos, F. and Deacon, J. (2015) “Models of learning and Adult Learners: Women Entrepreneurs”, ISBE Conference, 9-11 November 2015, Glasgow, Scotland. Tomos, F., Djebarni, R., Rogers, A., Thomas, A., Clark, A. and Balan, O.C. (2015) “Mixed Methods Research: Former and New Trends in Women Entrepreneurship”, Proceedings of the 14th European Conference Research Methodology for Management and Business Studies, 11-12 June 2015, University of Valetta, Malta, In: Bezzina, F. and Cassar, V. (Eds.), Proceedings of the 14th European Conference on ECRM, Publisher: Academic Conferences and Publishing International Limited, Reading, UK, ISBN: 9781910810118, www.academic-publishing.org Tomos, F. and Deacon, J. (2015) “Models of learning and Adult Learners: Women Entrepreneurs”, ISBE, General Confreat, Networking Seminar, July 16-17, 2015, Leeds, England. Shabalina, O., Mozelius, P., Malliarakis and Tomos, F. (2015) “Creativity-based learning versus game-based learning”, Proceedings of the International Conference on Creativity and Intelligent Technologies & Data Science, September 15-17, 2015, University of Volgograd, Russia, pp. 720-733, ISBN: 9783662468937, Source: Europäisches Arbeitsrecht: Mit zahlreichen Beispielsfällen aus der Rechtsprechung des EuGH. 21

Shabalina, O., Mozelius, P, Vorobkalov, P., Malliarakis, C. and Tomos, F. (2015) “Creativity in Digital Pedagogy and Game-Based Learning Technique; theoretical aspects, techniques and case studies”, The 6th International Conference on Information, Intelligence, Systems and Applications, July 06-08, 2015, Ionian University, Corfu, Greece. In: Proceedings of the 6th Conference on Information, Intelligence, Systems and Applications, (IISA), Publisher: IEEE, 2015, ISBN: 978-1-4673-9311-9, 978-1-46739310-2, AMSID: 738-7963, DOI: https://doi.org/10.1109/IISA.2015.7387963 Malliarakis, C., Tomos, F., Shabalina, O. and Mozelius, P. (2015) “How to Build an Ineffective Serious Game: Worst Practices in Serious Game Design”, The European Conference on Game-Based Learning, 27-28 October 2015, Trøndelag University, Norway. ”, In: Munkvold, R. and Kolas, L. (Eds.) Proceedings of the European Conference on Game-Based Learning, Publisher: ACPIL, UK, Vol 1, pp. 338-345, ISBE: 978-1910810590, www.academic-publishing.org Tomos, F., Grosch, M., Balan, O.C., Clark, A., Blackey, H., Turner, D. and Bennett, E. (2014) “Students’ Learning Preferences and Patterns of Media and Information Technology Usage in Higher Education Institution”, The 13th European Conference on eLearning, 30-31, October, 2014, Copenhagen, Denmark, pp. 555-563, Aalborg University, In: Ørngreen, R. and Tweddell Levinsen, K. (Eds.), Proceedings of the 13th European Conference on e-Learning, Publisher: Academic Conferences and Publishing International Limited, Reading, UK, e-Book ISBN: 978-1-910309-69-8, e-Book ISSN: 2048-8645, Book version ISBN: 978-1-910309-67-4, Book version ISSN: 2048-8637, www.academic-publishing.org Shabalina, O., Mozelius, P., Malliarakis, C., Tomos, F., Balan, O.C., Blackey, H. and Gerkushenko, G. (2014) “Combining Game-flow and Learning Objectives in Educational Games”, The 7th European Conference on Game-Based Learning, 8-9 October, 2014, Berlin, Germany. In: Busch, C. (Ed.) Proceedings of the 8th European Conference on Game-Based Learning, Vol 2, pp. 529-537, Publisher: ACPIL, UK, ISBE: 978-1-91030955-1, ISSN: 3049-0992, www.academic-publishing.org Tomos, F., Mozelius, P., Shabalina, O., Balan, O.C., Malliarakis, C., Miller, C., Jones, P. and Turner, D. (2013) “An International Approach to Creative Pedagogy and Students’ Preferences of Interactive Media”, The 12th European Conference on e-learning, October 30-31, 2013, Nice, France, In: Proceedings of the 12th European Conference on elearning, Publisher: Academic Conferences and Publishing International, Reading, UK, pp. 479-487, ISBN: 1-909507-82-2, 1-909507-84-9, 978-1-909507-82-1, 978-1-90950784-5. www.academic-publishing.org Tomos, F., Miller, C., Jones, P., Djebarni R., Olubode, O.O., Obaju-Falade, F.A., Eleodimuo Nkiruka, H. and Asmath, T. (2013) “Impacts of Internet Usage on Students’ Academic Performance at University of Glamorgan”, Proceedings of the 12th European Conference on e-learning, October 30-31, 2013, Nice, France. Academic Conferences and Publishing International, Reading, UK, ISBN: 1-909507-82-2, 1-909507-84-9, 9781-909507-82-1, 978-1-909507-84-5. www.academic-publishing.org 22

Mozelius, P., Shabalina, O., Malliarakis, C., Tomos, F., Miller, C.J. and Turner, D.A. (2013) “Let the students construct their own fun and knowledge – learning to program by building computer games”, The 7th European Conference Game-Based Learning, 8-9 October, 2013, Porto, Portugal, In: Escudeiro, P. and Vaz de Carvalho, C. (Eds.), Proceedings of the 7th European Conference Game-Based Learning, pp. 418-426. EBook ISBN: 978-1-909507-65-4, E-Book ISSN: 2049-100X, Book version ISBN: 9781-909507-63-0, Book version ISSN: 2049-0992, CD version ISBN: 978-1-909507-66-1, CD version ISSN: 2049-1018. Tomos, F., Price, T., Blackey, H., Jones, W.P., and Miller, C.J. (2012) “Technology Enhanced Learning at the University of Glamorgan with a focus on Students’ Mobile Technologies”, Proceedings of the 11th European Conference on e-learning, October 3031, 2012,University of Groningen, Netherland, pp. 601-610. SPECIAL INTEREST GROUPS: Creativity in Education Higher Education Educational Technology in Higher Education Gender Entrepreneurship Network (ISBE) Entrepreneurship Studies Network (ISBE) International Mobility and Curriculum Pedagogy and Andragogy STATISTICS/SOFTWARE AND EXPERTISE: SPSS, MAXQDA, Nvivo. EDITING SKILLS: e-Editorial Discovery System, IGI Global USA COMMITTEES MEMBERSHIP: ECEL, ECGBL, ECSM, ECRM, IISA, ICPPL, ICCITDS, MEMBERSHIP: ISBE, FHEA, BAM, FE, HEEG.

LIST OF ABBREVIATIONS Acc: Accounts (for the variance in DV) CoPs & networking: Communities of Practice & networking DV: Dependent Variable EA: Entrepreneurial Activity EP: Entrepreneurial Profile EED: Learning EFA: Exploratory Factor Analysis NET & ICTs: Digital Platforms and Information Communication Technologies IPA: Interpretative Phenomenological Analysis Is: Interviews IT: Information Technology IV: Independent Variable H: Hypothesis FG: Focus Group; FGP1: Focus Group Participant One MSRA: Multiple Standard Regression Analysis MMR: Mixed Methods Research PRCTS: Predicts P: Participant QUAL: Qualitative QUAN: Quantitative Q: Question R: Respondent SMEs: Small Medium Sized Enterprises TA: Template Analysis ThA: Thematic Analysis TFA EED: Total Factor Extraction Learning TFA NET: Total Factor Extraction Digital Platforms & ICTs TFA CoPs: Total Factor Extraction Communities of Practice & networking TFA NTCP: Total Factor Extraction Networking & Communities of Practice TFA MSc: Total Factor Extraction Measures of Success WES: Women Entrepreneursâ&#x20AC;&#x2122; Success

THE IMPACTS OF LEARNING AND DIGITAL PLATFORMS & ICTs ON THE SUCCESS OF WOMEN ENTREPRENEURS IN COMMUNITIES OF PRACTICE IN SOUTH-EAST WALES

CHAPTER 1: INTRODUCTION TO THESIS This is an interdisciplinary research on women entrepreneurs, attempting to discover the impact of Learning (EED) and Digital Platforms & Information Communication Technologies (NET & ICTs) on Women Entrepreneurs’ Success (WES), in the context of Communities of Practice and networking (CoPs & networking) in South East Wales. 1.1 Introduction to Chapter 1 Chapter 1 presents the background and rationale of the thesis, research problem, aim and objectives, research methodology, key terms defined, structure of the thesis, contributions and limitations. The thesis emphasises the contribution of women entrepreneurs from South East Wales to the national economy; focuses on the impact of Learning and Digital Platforms & ICTs upon WES, in the context of CoPs & networking; and raises awareness regarding women entrepreneurs’ methods, styles, models of learning and learning needs, in the context of Digital Platforms & ICTs, and CoPs & networking. In order to have a robust background, the author considers the following factors: the changing role of women in the world, their characteristics, barriers, inequalities, stereotypes, role identity, policies, gender segregation; the major trends in education and global technology; the role of CoPs & networking; and women entrepreneurs’ perceptions of success (Hislop, 2009; Alimo-Metcalfe, 1994; Dicken, 2011; Wenger, McDermott and Snyder, 1952; Marlow and Patton, 2005; McKay, Campbell and Thomson, 2013; Leung, 2011; Bradley, 1996; Bradley, 2014; Lockyer and George, 2012; Coleman, 2010; Brierton and Bennett, 2012; Clark Muntean, 2013; Rubery, 2015; Rafferty, 2014; Norbäck and Douhan, 2014; Andringa, Nieuwenhuis and van Gerven, 2015; Sweida and Reichard, 2013; Stead, 2015; Marques, 2017; Tomos et al., 2016; Tomos and Thurairaj, 2019; O’Leary, 2017; Martin, Lord and Warren-Smith, 2018).

The research

acknowledges that entrepreneurship is crucial for the national economy, and women entrepreneurs are factors of innovation and change (Coulter, 2000; Metcalfe, 2008; Parker, 2009). 25

1.2 Background and Rationale of the Research Small Medium Sized Enterprises (SMEs) are an essential element for the national economic growth, and in times of economic turmoil, they play an important role for economic regeneration and growth (Bolton Report, 1971; Fielden et al., 2003; Brodman and Berazneva, 2007).

This research highlights the increasing role of SMEs,

entrepreneurship, learning, knowledge, CoPs & networking, and digital platforms & ICTs within the national and global economies (de Rouffignac, 1991; Szarka, 1992; Hannum et al., 2008; Hanushek, 2009; Alquézar and Johansen, 2010; Mei, 2012; Xiaoying, 2012; Shi and Yonezawa, 2012; Deakins and Freel, 2012; Scarborough, 2012; Lafuente and Rabetino, 2011). SMEs generate 59% of employment and 51.5% of turnover in the United Kingdom (UK) (Burns, 2011), and therefore the Government encourages enterprises and provides business assistance across the UK (Department for Business, Innovation and Skills, 2011; BERR, 2011). Another phenomenon, which parallels the increasing role of SMEs for economies across the world, is women’s entrepreneurship. The UK Small Business Service (Carter, Anderson and Shaw, 2001) indicated that women business owners contribute £50-70 billion in gross value added to the UK economy per year, and represent 12.3% - 16.5% of the UK business stock (Carter and Shaw, 2006). Even though, the Government recognised the contribution of women entrepreneurs to the national economy, there are still barriers to business start-up and development, lack of experience, business knowledge and training for women entrepreneurs (Roomi et al., 2009; O’Carroll and Millne, 2010). However, in spite of the challenges, barriers and controversies regarding the gender relationships, and the labour market segmentation, with unequal employment and lack of capital and policies (Carter and Cannon, 1992; Carter and Shaw, 2006), the number of women entrepreneurs is growing rapidly (Griffin, 2002; Sweida and Reichard, 2013). The above-enumerated matters suggest a number of factors affecting women entrepreneurs’ success, and the need of research on women entrepreneurs as a distinct segment of entrepreneurial population. In the field of entrepreneurship, there are controversies and contradictions regarding the main factors affecting entrepreneurial success. One group of authors suggested that the entrepreneurial character is crucial for success (Chell, 2001; Burns et al., 2007). A second group of research studies indicated that, managerial and leadership capabilities are 26

important to entrepreneurial success (Armstrong and Baron, 1990; Drucker, 1985; 2015). The third group of academic research supports the idea that formal education and experience are factors determinants for business success (Powel, 1999; Laurent and Aretino, 2011; Delgado-Verde, 2011; Hexham and Capillaries, 2010). It follows that, in view to acquire skills and capabilities for business survival and success, women entrepreneurs need to learn. In line with the literature review, learning is a holistic process, which incorporates two elements: (1) the entrepreneur; (2) the entrepreneurial process with its methods, styles and models of learning. In the ‘information’ and ‘network’ society, which is assisted by the ‘revolution in electronic communication’ (Dicken, 2011, p. 3), another issue emerging from the literature review gravitates around Digital Platforms & ICTs, and their impact on entrepreneurial learning and women entrepreneurs’ success (Reynolds et al., 2001; Toffler, 1980; Moss, 1981; Webster, 2002; Johnsen and McMahon, 2005; Farr-Wharton and Brunetto, 2009; Ottösson and Klyver, 2010). Besides this, other authors (Goleman, 2001; Burt, 1992; Ottösson and Klyver, 2010) emphasised the role of social capital and social networks for the entrepreneurial success. Uzzi (1996) stated that the networks facilitates exchange of knowledge and collaborative learning (Farr-Wharton and Brunetto, 2009) and increases the chance of survival (Huggins, 2000). This study explores the impact of Learning and Digital Platforms & ICTs upon WES, and the role of CoPs & networking for learning and entrepreneurial success (Richardson, 1969; Fillis, 2007; St-Pierre and Audet, 2011). The author undertakes an interdisciplinary and holistic approach to studying the impact of learning and digital platforms & ICTs on WES, in the context of CoPs & networking. Further, Maslow’s Hierarchy of Needs and his holistic approach to self-actualizing people is regarded by the author of this thesis as a point of reference in designing the Andragogical Model of Learning for Women Entrepreneurs.

By studying women

entrepreneurs, the author of the thesis can address elements in the literature and create a link between learning, digital platforms & ICTs and WES, in the context of CoPs & networking (Furnham, 2005).

The rationale for this study is to bring an original

contribution to knowledge, by finding out the significance of the impact of learning and digital platforms & ICTs upon WES, and the role of CoPs & networking for WES. The author of the thesis answers the research questions and provides well-documented instructions regarding women entrepreneurs’ learning needs, styles and methods of 27

learning, with preferences for digital platforms & ICTs. The study provides wellformulated definitions of the main terms of the research. By testing the hypotheses of the study, the author was able to design and recommend an Andragogical Model of Learning for WES, and a Theoretical Business Model for WES, ready for generalization to Women Entrepreneurs in SE Wales. The outcome of the analysis demonstrates the importance of CoPs & networking for Women Entrepreneurs in SE Wales. According to the literature review, in the last decades, there was an increase of research on women’s entrepreneurship. However, there is not yet academic research work that has considered such a holistic, interdisciplinary and multidimensional perspective, and only a certain number of studies, which addressed separately research topics such as: women entrepreneurship, entrepreneurship education, business growth, success, ICTs and networks. 1.3 Aims and Objectives The aim of this thesis is to investigate the impact of learning and Digital Platforms & ICTs on WES in the context of CoPs & networking, in South East Wales (UK). The thesis has both a holistic and interdisciplinary perspective, upon the research topic. This is mainly a positivist study, complemented by an interpretative approach, which enhances the understanding, and the interpretation of the results. Thus, the study explores women entrepreneurs as learners, and their methods and styles of learning, in the context of Digital Platforms & ICTs and CoPs & networking. In this respect, the thesis analyses their approach to learning and their learning needs, in view to discover a learning model flexible and adaptable to the environments and the demands of women entrepreneurs, in order to achieve entrepreneurial success. The objectives of this research are as follows: •

To investigate the impact of learning and Digital Platforms & ICTs on WES;

•

To ascertain if there is a significant relationship and a correlation between learning, Digital Platforms & ICTs and WES;

•

To develop a theoretical business model for women entrepreneurs’ success, that can be used by women entrepreneurs to adopt learning and Digital Platforms &

ICTs and CoPs & networking within their businesses in order to assure entrepreneurial success; â&#x20AC;˘

To find out a model of andragogical learning, methods of learning with Digital Platforms & ICTs and styles of learning women entrepreneurs employ to acquire knowledge, in order to achieve success;

â&#x20AC;˘

To explore the role of CoPs & networking, in the context of Digital Platforms & ICTs, in acquiring knowledge and information required by women entrepreneurs in view to achieve success;

1.4 Research Methods The research was conducted in the South East Wales (UK). The study addressed the gaps in knowledge regarding women entrepreneurs, learning, Digital Platforms & ICTs, CoPs & networking and WES. The study endeavoured to answer the following research questions: Q1: What are the impacts of learning and Digital Platforms & ICTs on WES? Q2: Is there a significant relationship between learning, Digital Platforms & ICTs and WES? Q3: What are the methods, and styles of learning women entrepreneurs employ and what are their entrepreneurial learning needs and learning preferences in the context of Digital Platforms & ICTs and CoPs & networking? Q4: Are there correlations between: learning, Digital Platforms & ICTs and WES? Q5: How do women learn and acquire knowledge and information in the context of CoPs & networking and Digital Platforms & ICTs in order to achieve entrepreneurial success and business growth? Q6: What is the role of CoPs & networking for WES? The research questions of this study were answered through a mixed methodology, employing both quantitative and qualitative methods (methodological triangulation). In the first phase, the literature regarding women entrepreneurs was gathered via searches on internet. The study collected data through secondary sources for instance, published 29

sources such as the National Office of Statistics, European Official Statistics, Enterprise Research Centre, House of Commons, Business Statistics, Womenâ&#x20AC;&#x2122;s Business Council and Federation of Small Businesses, and through primary sources such as Survey with Questionnaires, Focus Group and Interviews. The author of the thesis, attempted at the beginning, to develop a research across two countries (Wales and England). Therefore, the study included both an online and paper form Survey with 450 Questionnaires. Thus, a sample of 300 SMEs with women entrepreneurs was recruited through different networks such as: the Association of Accounting Technicians, the Association of Chartered Certified Accountants, the Association of Women in Business (NAWBO), etc. and questionnaires were emailed to 300 women entrepreneurs across Wales and England. Whilst the online survey with 300 questionnaires sent in Wales and England was unsuccessful, the paper form, face-to-face survey with 150 questionnaires in South East Wales only, recorded a successful outcome. The semi-structured questionnaires comprised 55 open and closed questions. The research was enriched with qualitative methods such as a Focus Group with five women entrepreneurs and 37 interviews with women entrepreneurs from South East Wales (UK). The study employed the complementary approach to increase reliability and validity of the results, as well as to achieve a better interpretation of the results and to have a holistic view of the research topic. The expected return of this research is a better understanding of the relationship between learning, Digital Platforms & ICTs and WES, and the role of CoPs & networking in achieving success. In addition, the thesis informs, the models, methods and styles women entrepreneurs use to learn and acquire knowledge, in order to achieve success in the context of Digital Platforms & ICTs and CoPs & networking. Furthermore, there is an enhanced portrait of women entrepreneurs, as owners/managers and a comprehensive outline of womenâ&#x20AC;&#x2122;s identity role. For the analysis of correlation between the variables of the research: learning, Digital Platforms & ICTs and WES, the study employed modelling techniques such as multiple regression analysis, correlation and factor analysis (Jarrett, 1991). With regard to the analysis and data presentation, the study employed SPSS, basic mathematics, tables and graphs (Koops, 2005).

For the

qualitative data analysis, the author used Interpretative Phenomenological Analysis (IPA) and Template Analysis (TA) (Langdridge, 2007; Smith, Flowers and Larkin, 2009). 30

This study followed the guidelines for good practice in quantitative and qualitative research and provided anonymity and confidentiality as well as obtained informed consent (Warren, 2002). The research built on previous work and not only confirmed previous researches (Carter, 1993) but also contributed to a better understanding of the role women entrepreneurs have nowadays within the society and economy. Additionally, the author used the results of this research to recommend suggestions for improvements of government policies and practices regarding women entrepreneurs. Finally, this study designed a conceptual research framework for women entrepreneurs’ success and provided opportunity for generalisation in SE Wales, whilst offering suggestions for further research. In order to achieve the objectives of the research, the following hypotheses were formulated: Hypothesis One: ‘There is a significant relationship between Learning, Digital Platforms & ICTs and WES’; Hypothesis Two: ‘Learning has a positive impact on WES’; Hypothesis Three: ‘Digital Platforms & ICTs have a positive impact on WES’; Hypothesis Four: ‘There is a correlation between Learning, Digital Platforms & ICTs and WES’. 1.5 Key Terms Defined (1) Women Entrepreneurs: Women owned business totally, or in partnership. Womenowned businesses have grown since 1980 because of dissatisfaction with corporate life, due to glass ceiling phenomenon and lack of balance between work and home (Lambing and Kuehl, 2003). Women Entrepreneurs’ Success (WES) means having control over their own lives, good relationships with customers and achievement (Lambing and Kuehl, 2003). (2) Learning: In this context and for the purpose of this research, learning (EED) replaces Entrepreneurship Education, which is defined as “communication of business knowledge” (Packham et al., 2010). The purpose of Learning (in this context) is firstly, to help individuals to understand what is: (a) entrepreneurship and (b) the role of entrepreneurs and secondly, to teach how (c) to become an entrepreneur and manage the business (Bridge et al., 2009). For the purpose of this research, and because the focus of section B of the Survey Questionnaires is mainly on learning, therefore, the author of the 31

thesis uses learning, instead of EED, and uses EED abbreviation for ‘learning’. Furthermore, the author of the thesis approached learning for women entrepreneurs from the andragogical perspective. These abbreviations are used for the statistics across the thesis. (3) In the context of this thesis, and for the purpose of this research, based on the content of the survey questionnaire, the author defines New Emerging Technologies and Information Communication Technologies (NET & ICTs) as follows: New Emerging Technologies are social media technologies such as: Facebook, Twitter, LinkedIn, etc. In addition, for the purpose of the research, the author replaced in the text of the thesis, NET & ICTs with ‘Digital Platforms & ICTs’. Information Communication Technologies (ICTs) are the following: smart phones, iPhones, iPad, Androids, tablets, laptops, etc. These abbreviations are used for the statistics, across the thesis. (4) Communities of Practice and Networking (CoPs & networking): Network is defined as ‘a complex or interconnected group or system’ whilst networking ‘involves using the arrangement to accomplish particular tasks’ (Bessant and Tidd, 2007: 84). Communities of Practice (CoPs) are ‘groups of people who share a concern, a set of problems, or a passion about a topic, and who deepen their knowledge and expertise in the area by interacting on an ongoing basis’ (Wenger, McDermott and Snyder, 1952, p. 4). In the statistics, when used, in the text of the thesis, CoPs incorporates networks/networking. These abbreviations are used for the statistics across the thesis. (5) A business model is ‘the way a company applies knowledge to capture values’ or ‘a framework in which entrepreneurs ...explore ways... to function and grow profitably...’ (Kaplan and Warren, 2007, p. 260). (6) Andragogical Model of Learning is an intricate and holistic framework proposing methods and styles of learning for women entrepreneurs as adult learners, in the context of Digital Platforms & ICTs and CoPs & networking, considering additional relevant environments. (7) Woman is a designed human being with rights and obligations; embedded within the meaning of the concept “hommes” (Hebrew Bible; De Beauvoir, 1959; 2015), and uniquely situated in society, economy and witthin the intricate phenomenon of entrepreneurship. In the context of this thesis, the concept ‘woman’ belongs to the wider 32

concept called ‘women’. This is a very heterogenic group, with different levels of education, knowledge, information, intellectual capabilities, technological capabilities, social status, financial and economic power, economic and business knowledge, social and cultural background, networking capabilities, experiences, professions, family responsibilities, and marital status, with/without children, caring responsibilities, nationality, ethnicity, belief and health. 1.6 Structure of the Thesis The structure of this thesis is depicted over the following eight chapters: Introduction, Literature Review, Research Frameworks, Research Methodology and Design, Quantitative Data Analysis, Qualitative Data Analysis, Discussions & Interpretations, and Conclusions & Contributions. This First chapter introduces the background and rationale of the research, aims and objectives, research methods and hypotheses, key terms defined the structure of the thesis and contribution to knowledge. Chapter two is entitled Literature Review comprises eight sub-sections and provides comprehensive information. The first sub-section of chapter two presents information regarding small and medium sized businesses (SMEs), women entrepreneurship, growth and success. Moreover, it discusses practices and policies about small businesses, describes the role of the historical, administrative and legal context for SMEs in Wales, the United Kingdom and across Europe. It provides an overview of SMEs and women entrepreneurs within the Welsh Context, in the United Kingdom. Further, the chapter presents a short historical development of thoughts, which is followed by an introduction to women’s entrepreneurship phenomenon. The next sub-section includes information regarding learning and women’s opportunity, the learning process, methods and styles of learning, models of learning, and entrepreneurial learning.

The following sub-section

emphasises the role of Communities of Practice (CoPs) and networks, knowledge creation, transmission and sharing process. Additionally, the chapter describes the types of knowledge, and the networking phenomenon.

Further sub-section presents the

important role that Digital Platforms & ICTs play within the transmission of learning to entrepreneurs. The chapter introduces the concept of ‘cloud computing’ and describes the impact of e-learning and m-learning on learners and businesses. Finally, the ultimate sub-section of the chapter ends the literature review section. This sub-section is a 33

summary of the literature review, presents the quintessence of the chapter and provides information regarding the gaps in the field of women’s entrepreneurship, and explains how this thesis addresses the gaps. The literature of this chapter was reviewed at the time of questionnaire design and is fundamental for the thesis. Chapter three introduces the theoretical and conceptual research frameworks.

addition, the chapter presents theory development. Chapter four is entitled Research Methodology and Design, and presents the introduction to chapter, Research Problem and Philosophy, Researcher’s Philosophical Perspective, the Rationale and Implications of using Mixed Paradigms, Research Purpose and Types of Research, Research Approach and Design, Research Methods and Methodology, Sampling, Sample and Data Collection, Questionnaires Design and Data Collection, Ethical Concerns, and Summary. Chapter five is Quantitative Data Analysis, which introduces quantitative data analysis, with descriptive statistics, and inferential statistics, Factor Analysis, Correlations and Regression. Chapter six is Qualitative Data Analysis and presents qualitative data analysis with introduction to phenomenology, interviews and focus group analyses, thematic analysis, Interpretative Phenomenological Analysis (IPA) and Template Analysis (TA), FG and Interviews Content Analyses and the Summary of the chapter. Chapter seven Discussions, includes the following content: introduction to the chapter, the analyses of the relationship and correlation between learning, CoPs & networking and WES, factors impacting on WES, theoretical contribution of the thesis, models of learning, learning and acquiring knowledge, validity and reliability of the results, and data storage & management. Chapter eight is entitled “Conclusions & Contributions” and comprises conclusions, main findings, thesis contributions to knowledge: theory & practice, limitations, future research and recommendations. In addition, a list of References and Appendices are attached at the end of the thesis.

1.7 Contribution to Knowledge There is a gap in understanding women’s entrepreneurship phenomenon in Wales (UK) from a holistic and relational perspective.

There is no research on women’s

entrepreneurship in SE Wales, little research studies on women’s entrepreneurship in the UK, and on the role of learning for women entrepreneurs. In addition, the phenomenon is regarded in isolation, and very few studies considered the roles of Digital Platforms & ICTs for learning, and CoPs & networking for WES. This research brings a significant contribution to knowledge, provides a holistic view on this phenomenon, in South East Wales, UK. The research explores the relationship between Learning, Digital Platforms & ICTs and WES, and the role of CoPs & networking for WES. The study is the first to investigate the relationship between such constructs (Learning, Digital Platforms & ICTs, WES). The research is also the first in exploring the role of CoPs & networking, within the relationship (Learning, Digital Platforms & ICTs, WES) from women’s perspective. The impact of Digital Platforms & ICTs upon WES has not been yet empirically addressed in South East Wales, UK. Furthermore, the proposed conceptual research framework was tested and developed into a Theoretical Business Model for WES. The thesis provides evidence for the perceived relationship between Learning, Digital Platforms & ICTs and WES. In addition, the role of CoPs & networking as a controlled variable provides additional insights and better understanding of women’s entrepreneurship phenomenon, in South East Wales, in the United Kingdom. Because of the analysis, a thorough Andragogical Model of Learning for Women Entrepreneurs, in Wales, UK, was designed.

Thus, the study is the first to design a thorough

Andragogical Model of Learning for Women Entrepreneurs’ Success in South East Wales, UK. The findings of this investigation provide the HEIs, Government, academic research, practitioners and policy makers with information regarding methods of helping women entrepreneurs to achieve entrepreneurial success, and helps meeting their learning needs. The thesis informs the Governments, HEIs, practitioners, academics, consultants and policy makers with regard to models, styles and methods of learning, and the role of CoPs & networking for WES, in the context of Digital Platforms & ICTs, from women’s perspective.

1.8 Limitation of Scope In order to achieve the objectives of the research, this thesis is mainly exploratory, and hypotheses testing. In addition, and for the enhancement of understanding, the study is also, explanatory. The thesis is aimed to explore the relationship between the variables of the research and their impact upon WES, in the context of CoPs & networking. The study was designed to approach women entrepreneurs in Wales and England. However, because of the low response rate to online survey, and due to time constraints and lack of financial resources, the research was limited to a regional analysis, South East Wales, in the UK. 1.9 Summary of the Chapter This chapter presented the research problem, background and rationale behind the study, the aims and research objectives, research methods and contributions. Having identified the aims, objectives and introduced the topic of the research, the following chapter discusses the literature review. Accordingly, the research introduces the concepts of small businesses, women entrepreneurship, business growth and success, learning, CoPs & networking and Digital Platforms & ICTs.

Figure 1.1: Structure of the Thesis CHAPTER 1: Introduction

CHAPTER 3 Theoretical Framework & Conceptual Research Framework CHAPTER 4 Research Design & Methodology (Sampling Techniques & Sample) Questionnaires Design, Focus Group, Interviews and Data Collection

CHAPTER 2: Literature Review 2.1: Small Businesses, Women Entrepreneurs, Success & Growth 2.2: Learning 2.3: Communities of Practice and Networks 2.4: The Digital Platforms & ICTs 2.5: Summary of Literature Review

DATA ANALYSIS CHAPTER 5: Quantitative Data Analysis CHAPTER 6: Qualitative Data Analysis CHAPTER 7 Data Interpretations & Discussions

CHAPTER 8: Conclusions and Contributions

CHAPTER 2: LITERATURE REVIEW Chapter two includes seven sub-sections (Figure 2.1). In section one of the chapter, the author presents a short overview on small businesses definitions and background, SMEs in the United Kingdom, the Welsh economic context in the United Kingdom, and SMEs owned by women. Further, the second section develops the literature about womenâ&#x20AC;&#x2122;s experience as entrepreneurs, information on retail and services sectors and entrepreneurship, growth and success. Section three discusses learning. Section four argues about the role of knowledge, networks and communities of practice for women entrepreneurs and business growth. Section five introduces information regarding the crucial role of Digital Platforms & ICTs play for the entrepreneurial process and women entrepreneurs, globally, nationally and regionally. It also discusses about the new methods of learning, such as m-learning. Section six closes chapter two with a critique of the literature review, followed by a summary of the literature review of section two. Figure 2.1: The Structure of Chapter Two

CHAPTER TWO LITERATURE REVIEW

COMMUNITIES of PRACTICE and NETWORKS

DIGITAL PLATFORMS & ICTs

LEARNING

SMALL BUSINESSES, WOMEN ENTREPRENEURS, SUCCESS

Summary of the Literature Review

2.1 SMALL BUSINESSES, WOMEN ENTREPRENEURS, SUCCESS AND GROWTH 2.1.1 Introduction The section describes the main characteristics of SMEs and the difficulty to formulate a general definition for SMEs due to the heterogeneity of the sectors in the UK. Further, it presents a history of the evolution of SMEs legislation in the UK. Thus, the section introduces the definition of SMEs, their role and importance for the development and economic growth and the challenges faced by them because of globalization and technological progress. Particularly important is the welsh context of the SMEs owned by women entrepreneurs in South East Wales and women entrepreneurs’ experiences, and barriers. Further, the section introduces the phenomenon of women entrepreneurship, business growth and success. The rationale behind these is to create a link between the literature and the aim and objectives of the research. There is a significant body of literature and discussions about what constitutes a Small and Medium Sized Enterprise (SME) in the UK. In spite of the difficulty to define small businesses, Bolton Report (1971) suggested an early definition by highlighting three main characteristics. Thus, small businesses are managed by the owner, have small share of the market and are independent (Beesley and Wilson, 1984). Beesley and Wilson (1984) argued that previously, the United Kingdom had no business legislation excepting the Small Business Act of 1953, which established the Small Business Administration. However, the ‘small business’ concept was the first time mentioned in the UK, within the Report of the Macmillan Committee on Finance and Industry published in 1931 (Hertz, 1982). This was followed by the first attempt to define small business by Bolton Committee in 1971 (Hertz, 1982). As a result of heterogeneity of the sectors and differences between countries across the European Union (EU), it is difficult to formulate a general definition. There are many definitions of a small business and most of them are based on the number of employees and the sales of the firm (Casson et al., 2008). Nevertheless, a second definition more homogenous was provided by the European Union (EU) in 1996 and updated in 2004 (Greene and Mole, 2006). Thus, the European Commission defined the Small and Medium Sized Enterprise as an organisation, which employs less than 250 people, has an annual turnover less than € 50 million and a Balance Sheet less than € 43 million 39

(Commission Recommendation of 6 May 2003). This definition is most commonly recognised by authors and used across the EU (Greene and Mole, 2006; Burns, 2011). For a better understanding of the role of SMEs, the research needs to explore the situation and the main trends of the SMEs in the EU and highlight the impact of the Small Business Act upon SMEs in Europe. In June 2008, the Commission for the European Communities sent to the Council and European Parliament the “Think Small First”, a “Small Business Act” for Europe. The Small Business Act (SBA) placed SMEs at the centre of business growth and employment. Furthermore, the SBA emphasised the challenges of globalization and technological progress faced by the entrepreneurs and SMEs, and encouraged them to incorporate technology into their businesses in order to survive in a very competitive global environment. The SBA created a framework and ten principles, which are the legal and administrative foundation for SMEs in Europe (SBA, 2011). The designed principles have the main aim to help the entrepreneur, facilitate the access to finance, promote skills and innovation within SMEs (SBA, 2011). However, despite the fact that SMEs are job creators in the EU, because of the economic crisis about 3.25 million jobs have been lost. Nonetheless, they are at the heart of the economy, as a source of competition against big companies (SBA, 2011). Webster (2002, p. 103) argued that globalisation and competition effected directly the breaking down of large corporations into smaller “multidirectional networks”. According to SBA (2011), by promoting entrepreneurship, governments promote job creation and growth. Below, the study provides a table with the figures showing the evolution of SMEs population in the UK across seven years. The table indicates an increase in the number of active enterprises in industry and services from 2007 to 2013 (Table 2.1).

Further analysis, indicated an

increase in the number of SMEs in the United Kingdom, from 4,536,765 in 2011 (NACE, 2011) to 4,787,000 at the start of 2012 (SBS, 2012; Labour Force Survey, 2015). Table 2.1: Population of active enterprises in industry and services Country 2007 2008 2009 2010 2011 2012 United Kingdom

2,072,500

2,157,830

2,109,610

Source: NACE Rev. 1.1. 2011; LFS, 2016

2,013,215

2,027,605

2,054,935

2013 2,126,7 80

2.1.2 SMEs in the United Kingdom Since the fifteenth century, England (before the UK) was one of promoters of entrepreneurship (Ricketts, 2008). Its rulers used the same features of “the merchant” and tried to accumulate treasures in view to build a powerful state. Ricketts (2008, p. 36) emphasised that the enterprise was “statist at heart” and lately, the development of computer technology and communication, was instrumental to the development of entrepreneurship. Additionally, the notion of the entrepreneur, developed over time. The entrepreneur is not only the old artisan or the sole trader, but also the innovator and the founder of new technologies (Ricketts, 2008). SMEs represent a very important part of its industrial structure and a means of job creation, innovation and economic growth. In spite of the economic crisis, statistics on business demography show that the number of new enterprises started to recover. Statistics, depicting business demography in 2014, indicated an increase in the number of active businesses and in the survival rate over a five year period (2009/2014) (41.7%) in the UK (ONS, 2016). Additionally, the rate of business birth across five year period proved to be superior (2009/2014 – 10.1%/13.7%) to business death rate (2009/2014 – 11.8%/9.6%) (ONS, 2016). With regard to the economic structure, OECD (2010) statistics show that micro and small size enterprises are the main creators of jobs, employing about 85% of the active population. There were differences between female and male employment rates in the way that female employment rate was lower (65.55% in 2000) than their male counterpart (78.94% in 2000). However, the statistics show that while the male rate decreased over a ten year period, the female rate remained constant (75.27% for male, 65.34% for female in 2010). It is also worthy to mention that self-employment rate per total for a ten year period (20002010) knew an increase from 12.82% to 13.81%. There was an increase for both male and female entrepreneurs even though the statistics depict quite a gap between male and female self-employment rate, e.g. 16.70% for male than 8.27% for female in 2000; 18.10% male than 8.92% female rate of self-employment in 2010 (OECD, 2010). According to the Department for Business, Innovation and Skills (BIS, 2012) Business Population Estimates (BPE) show the existence of 3,557,255 businesses with no employees in the United Kingdom, representing 74% of all private businesses in the United Kingdom (BMG Research, 2013). According to this source, the SME population 41

for the United Kingdom was 4,782,650 businesses. Of this, the SME population in each nation was as follows: 4,162,285 businesses in England; 318,655 in Scotland; 189,160 in Wales and 112,550 in Ireland. The latest figures provided by the Statistics Bulletin (APS, Business Register & Employment Survey & Welsh Agricultural Census, 2016) showed that Wales had 238,000 SMEs in 2015. From this total, about 100,200 SMEs are located in South East Wales (2015). Of 100,200 SMEs, 94% have ‘0 to 9’ employees (APS, Business Register & Employment Survey & Welsh Agricultural Census, 2016). Conform to BIS (2016) estimates at the beginning of 2012, women-led business represent 18% of 4,787,000 SMEs and contributes £75 billion to Gross Added Value. The European Commission (Table 2.2) initiated a set of definitions of small and medium-sized enterprises (SMEs). Small and medium-sized enterprises are defined as ‘the backbone’ of the European economy. They provide a source for jobs and economic growth. Table 2.2: EU definition of SMEs Enterprise Head count category Micro Small Medium-sized

<10 <50 <250

Turnover or

Balance Sheet

< €2m €10m €50m

< €2m €10m €43m

Source: EU (2005), European Commission (2011)

In the EU, 23 million SMEs employed 67% of the private sector workforce. They represented 99% of all businesses and employed more than 90 million in Europe (Antonio Tajani, EC Vice-President). According to Articles 1 and 2 of the Small Business Act (SBA), an enterprise is “an entity engaged in an activity” and includes self-employed persons, family business, partnership or associations. In spite of Government initiatives to develop an enterprise culture, there is evidence indicating that SMEs have a high chance of failure. Nearly 50% of the entrepreneurs are women who started small businesses. Factors that affect female entrepreneurship are the growth in the service sector, niche markets, and a high level of unemployed and labour force flexibility (Sloman and Hindle, 2007). There is an industrial division in the UK, which has an impact on small businesses in the sense that most of them are directed towards sectors such as agriculture, construction and private sector services (Brooksbank, 2006). The same author argues that there are low participation rates in manufacturing and public sectors. However, recent changes in the British economy demonstrate patterns of increase in the service sector. Statistical figures from the Labour Force Survey (2005) showed the percentage of self-employment in 42

Wales 11.9% compared to UK 12%. Nevertheless, there are regional differences, which vary between 8.4% in North-East and 14.7% in South-West or 15.1% in London (Brooksbank, 2006). Bennett (2006) with regard to government action, noted constraints regarding the development and design of solutions for SMEs, such as: difficulty in the adoption of appropriate, suitable public policy and in providing help; lack of updated information and lack of business skills. However, starting with 2002 the UK government has taken actions to stimulate the growth and survival of new businesses (Robertson et al., 2003). Weaknesses and strengths in relation to business growth have been examined and the strategic innovative thinking reconsidered for successful business development (Beaver, 2002).

One of the strategies for business growth is globalization and innovation.

Following the general trend of globalization and innovation by information technology (IT) and networking involvement, some authors provided an insight into the barriers to internationalization faced by small UK retailers (Hutckinson et al., 2009). Other authors (Jones et al., 2011) conducted a survey with 500 SMEs in Wales and discovered a limited usage of information technology, particularly in micro and small sized businesses. According to the National Economic Strategy (NOP, 2000; DTI/BERR; eCIC, 2005/2006, FSB) Wales was classified as being a poor economic area due to the existence of an indigenous business base, lack or low rate of export, information technology, low level of wages and activities, under developed tourism and more than these a quite reduced level of business start-up. The research depicts Wales as having poor access to internet, online trading and ordering. Further examination of information technology in Wales since 2000, displays relevant increase in internet utilisation, broadband access, website and e-mail usage (NOP 2000; DTI - Department for Trade and Industry; eCIC â&#x20AC;&#x201C; eCommerce Innovation Centre 2005/ 2006; FSB â&#x20AC;&#x201C; the Federation of Small Businesses). Additional information regarding statistical data, on employment and unemployment rates in the UK and European Union (EU), is provided in a comparative manner between men and women. Further indicators on educational attainment, gender segregation in occupations, key indicators for the non-financial business economy, entrepreneurship indicators and the number of enterprises in the private sector, are provided by Eurostat (EC, 2011) in the Appendix (Tables 1-15, Appendix A1). In conclusion, in the UK, SMEs are the means of job creation and economic growth. Therefore, the UK government uses 43

innovative thinking, access to knowledge, information and information technologies (IT), to stimulate the survival and growth of the new businesses. 2.1.3 SMEs & Women Entrepreneurs in South East Wales, the UK In the national economy, which is still recovering from the 2007/2008 financial crisis, keeping the regional economy afloat is essential for South East Wales in the United Kingdom.

In this sense, promoting, supporting and acknowledging women

entrepreneursâ&#x20AC;&#x2122; contribution to the local and national economy has been a challenge. This section introduces the Welsh economic context in the United Kingdom, and SMEs owned by women. The United Kingdom normally defines Small and Medium Sized Enterprises (SMEs) as being businesses with less than 250 employees. In 2018, in the UK there were 5.7 million SMEs and 5.4 million micro-businesses, which represented 96% of all businesses (House of Commons, 2018). Business statistics (House of Commons, 2018) indicate an increase in businesses by 63% in 2018, than in 2000. Statistics reporting the share of businesses and businesses in the United Kingdom by size, in 2018, are presented in Tables 16 and 17 (Appendix A1). The number of enterprises in 2018, in Wales was 199,000 (BEIS, 2018; House of Commons, 2018). Statistics conducted by ONS (2017) on business birth and deaths by region, revealed a higher percent in business birth (14%) than business death (10%) in Wales (House of Commons, 2018). This indicate an increased rate in enterprise promotion and development in Wales, compared with Northern Ireland, Scotland, East Midlands and even London (Table 18, Appendix A1). According to BEIS (2018) and House of Commons (2018) even though a great proportion of businesses are in construction and manufacturing, however, the main concentration of the businesses in the UK is within the services sector, which accounted for 79% of employment, and 72% of turnover (Table 19A, Appendix A1). Conform to the same source, the retail sector represents 10% of the businesses in the UK and provides 19% of the employment and 34% of the turnover (Ibid, 2018). It seems that, women from the European area are highly concentrated in the service sector, and this is a general characteristic of women owned businesses, across Europe and North America, with small differences per region (Me and Giovanelli, 2003). Furthermore, the sectors with higher number of women owned businesses, such as wholesale, retail trade (16%), real estate (27%), hotels and restaurants (5%), health and social work (18%), and personal services (18%), have also smaller business growth and turnover (FSB, 2018) (Table 19B, 44

Appendix A1). According to business statistics (House of Commons, 2018) women owned and women led businesses bring £ 85 billion to economic output (Gross Added Value/GVA) (Table 20, Appendix A1). Despite the fact that, women owned businesses contribute £ 105,551 million per year (2015) in economic value added to the national economy, research conducted recently by the Federation of Small Businesses (2018) discovered that, policy makers do not have sufficient information and real data to facilitate adequate and strong analyses on women owned businesses in the UK, and in Wales particularly. FBS (2018) estimates also that, businesses with women owners contribute annually with £3,306 million to the economy in Wales, only. Furthermore, statistics present an increase in the number of SMEs in Wales with women majority owners to 112,289 in 2015, comparing with 102,708 in 2012 (FSB, 2018). Women owned and women led businesses in Wales represent a percentage of 26.9% of all businesses in Wales (FBS, 2018) (Table 21, Appendix A1). These statistics confirm women’s contribution to the regional and national economy in Wales and the UK. In line with this, an important role in enhancing women’s contribution to the national and regional economy, has Women’s Business Council (WBC). In view to enrich women’s economic capacity, the reports published by WBC (2013; 2018) related that, WBC (2018) encourages women to have their own businesses and helps them to gain enterprise skills, whilst providing for them role models and support for improved childcare. In a comparative approach WBC (2018) offers a perspective upon the percentage of women engaged in early stage of entrepreneurship (5.3% - in 2018, compared with 5.8% - in 2013), women in self-employment (19% – in 2017, compared with 19% - in 2012) and women having knowledge and business experience (33.4% - in 2017 compared with 31.2% - 2012).

There was an increase in the number of self-employed women from

1,294,000 in 2013 to 1,594,000 in 2018, in the United Kingdom (WBC, 2018). According to the same source, women accounted for 32% of self-employment in 2016, percent that exceeded 28% of self-employment before the recession in 2008. Women entrepreneurs own about 20% of businesses with single owner, circa 1.1 million small businesses, whilst additional 38% represent small businesses with women within the managerial teams (WBC, 2018). These reports and analyses provide a comprehensive view regarding Wales as part of the United Kingdom and as a nation.

However, there is no research yet, providing data and information at the regional level in Wales (SE Wales). Therefore, this thesis aims to cover this lack of research and analysis, contributing thus to a better understanding of the regional economic situation, and women entrepreneurs’ contribution to the economy in the SE Wales, and providing a conceptual research framework for women entrepreneurs’ success. There is not yet a framework for women entrepreneurs in Wales, neither women entrepreneurship strategy. Therefore, the Welsh Government makes sure that women in Wales receive support, knowledge and skills to start a business, by means of various organisations, programmes and initiatives, such as: Chwarae Teg, Mentoring programme, Inspiring Women, Enterprise Passport, Women in Rural Enterprise (WiRE), Enterprise for All, Enterprise Advisors and Childcare initiative (FSB, 2018). 2.1.4 Women Experience as Entrepreneurs Women entrepreneurship provides younger and older women with financial opportunities, independence and flexibility (WBC, 2018). Enterprise programmes help women to gather skills and competences for setting up and developing businesses, whilst raising the awareness of their role as contributors to the British and Welsh economies (WBC, 2018). In this sense, Women’s Business Council (2018) raised the awareness of the experience of famous women entrepreneurs and the emergence and need of diverse role models, able to enhance the confidence and determination of younger and older women to become entrepreneurs.

In line with this, WBC (2018) increased their

collaboration with organisations such as: Innovate UK, Everywoman and Inspire the Future, and created innovative websites which provided examples of role models women entrepreneurs, with successful businesses, able to transmit successful stories and offer to other women some of their entrepreneurial experiences. Role models from business associations, based on their experience and success, have the ability to motivate other women to start an entrepreneurial career (FSB, 2017). Similarly, NatWest Everywoman program, with their accredited specialists in ‘women entrepreneurship’, offered well designed support and motivations to women who desired to start and develop a business, whilst dispersing differences between men and women, eliminating barriers to entrepreneurial process, and opening the potential to women entrepreneurship (WCB, 2018; FSB, 2017). A report on women in enterprise revealed that the main skills needed by women entrepreneurs to grow a business and secure success were marketing, digital skills and business strategy (FSB, 2017). According to FSB 46

(2017) entrepreneurial skills required by women in view to start and develop a business, can be acquired by training with women entrepreneurs who wish to share their experiences. Nevertheless, in the new economic climate, business skills proved to be a perishable resource, which requires periodical updates, through lifelong learning. In this sense, the following are the skills, which secure business growth and must suffer recurring updates: marketing, business and finance, sales, business strategy, digital skills, management and decision-making (FSB, 2017). However, there is a lack of diverse role models to inspire and share these skills with women and girls.

As a result, inspiring

women with different professions, including businesswomen participate in this process, together with 16,500 volunteers through the Education and Employers Taskforce (FSB, 2017). McClelland et al. (2005) argued that women face barriers in acquiring entrepreneurial training, and claimed that women lack experience, knowledge and business degree when starting the entrepreneurial career. Moreover, according to demographic data, women entrepreneurs were highly educated, between 30 to 45 years old, and the majority were married with children. The area of their degree was in fashion, teaching, counselling, nursing and social sciences (McClelland et al., 2005). According to McClelland et al. (2005), all women from the survey had previous industry experience across various sectors. Moreover, the data indicated that women had businesses with social orientation and a strong sense of altruism, towards community and family. Similarly, research by Sharafizad (2018) highlighted that, women entrepreneurs have sector and industry experience, however, as a result of resources and time constraints, they depend on their networks for the acquisition of business knowledge and skills (Sharafizad, 2018). This research confirms that, women entrepreneurs are highly qualified, with industry and sector experience, and prefer flexible informal learning by means of networks (Sharafizad, 2018). As opposed to the above opinions, Ndemo and Maina (2007) found women entrepreneurs with leadership and management experiences.

In addition, Bennett and Dann (2000)

presented women entrepreneur with business education compared with liberal arts education reported by McClelland et al. (2005). An increased number of younger women achieve a degree, which embeds within practical experiences acquired through live projects, which are developed by universities with the industry. This enhance not only their employability skills, but also their entrepreneurial skills, which are transferable to 47

future enterprises (O’Leary, 2017).

These findings are consistent and lead to the

argument that women are a heterogeneous group with various experiences and skills when starting and developing their enterprises.

Furthermore, it seems that women

entrepreneurs are moving away from traditional sectors, towards male dominated industries, according to their level of education and skills, which is higher and more diverse. Additionally, the last research witnesses a shift in the learning style, which is experiential learning pioneered by Kolb (1984) and defined by O’Leary (2017, p. 79) as “learning through experiences and practices”. In the present business, environment women entrepreneurs learn by experience, through interpretation, reflection, conceptualization and action (Kolb, 1984; O’Leary, 2017).

This thesis argue that

women’s employability skills acquired through HEIs could be equated with women’s entrepreneurial skills, embedding both soft and hard skills, very much required for the entrepreneurial success (O’Leary, 2017). 2.1.5 Entrepreneurs and Entrepreneurship An early article entitled ‘The Evolving Perspective of Businessman’ by Cole (1949) argued about the role of businessman [sic] in the economy, and highlighted the role of entrepreneurship in the economic development in the United States (US), global leader in entrepreneurship, as well as its impact upon the economic growth. Cole (1949) emphasised the role of the entrepreneur, and made distinction between the ‘ownership’ of the business and the ‘management’of the business. The businessman is placed at the heart of the ‘dynamic’ economic process, having well-established responsibilities towards society at large and acting as a mediator between the employees, the customers and the stakeholders (Cole, 1949). The author makes clear the distinction between the tasks within the business. However, there is not clear definition of the entrepreneur and his responsibilities, neither a gender perspective of this. Is the entrepreneurial profile a new version of the businessman profile?

The classical economic theory of capitalism

introduced ‘the entrepreneur’ as ‘rational and self-motivated individual’ or ‘ambitious and motivated’ and ‘the main “engine” of the time’ (Levitt, 1956, pp. 38, 39). A subsequent study by Long (1983) undertook research on various definitions of entrepreneurship used by different economists since Richard Cantillon (1755) and discovered three major themes. According to Long (1983) entrepreneurship (traditional perspective) involves: (1) risk and uncertainty (Richard Cantillon, 1755; Frank Knight, 48

1920); (2) management capabilities (Jean-Baptiste Say, 1810; Alfred Marshall, 1890; Edith Penrose, 1960; Harvery Leibenstein, 1970) and (3) a continuous creative process searching for opportunities (Joseph Schumpeter, 1910; Israel Kirzner, 1975). The literature revealed that, there is no accepted consent about the meaning of the following terms: entrepreneurs and entrepreneurship.

Some authors defined

entrepreneurs as ‘business owners’ or ‘self-employed’, whilst other authors considered that entrepreneurs are “business owners who employ other workers” (Parker, 2009, p. 6). On the contrary, Schumpeter saw entrepreneurs as individuals capable to bring in innovations (Parker, 2009) and embraced Knight’s ‘uncertainty – based theory’, meaning that, the entrepreneurs undertook risk and worked in uncertain situations (Ricketts, 2008). Additionally, Schumpeter (Ricketts, 2008) associated this with the concept of the entrepreneur as a “revolutionary innovator” and labelled entrepreneurship as a process, which embeds simultaneously creativity and destruction in view to reach capitalist progress.

Rajitha (2012, p. 35) perceived the entrepreneurship as facilitating the

“independence of thoughts and action”.

Whilst, Parker (2009) argued that the

entrepreneur is an individual who recognises an opportunity, and emphasised that venture creation is key factor for entrepreneurship. Moreover, Parker (2009) claimed that SMEs are not similar with entrepreneurship, which is a risk-taking activity. The school of thoughts on entrepreneurship can be classified according to the groups of theorists and groups of issues or periods (Ricketts, 2008). Furthermore, Ricketts (2008) noticed that the role and the meaning of entrepreneurship began to shape in the late fifteenth century when the monarchs of France, Spain and England started to embrace the characteristics of entrepreneurship within their governments, in order to accumulate treasure and increase the state power. However, Ricketts (2008) highlighted that the main role, in creating an image for the entrepreneur, had the industrial and agricultural revolution of the eighteenth and nineteenth centuries. Thus, “the small scale trader, the self-employed craftsman, the innovator, the founder of new technologies and industries” were all considered as entrepreneurs (Ricketts, 2008, p. 38). Moreover, the characteristics of the entrepreneurship were: “...strategic insight, tactical awareness, personal energy, power of leadership, organisational flair, ruthlessness and determination...” (Ricketts, 2008, p. 38) 49

Parker (2009) argued about the existence of many determinants, which had impact on the entrepreneurship over the years. These determinants, he said, were earnings, the desire of the independence, job satisfaction, human capital, social capital, demographic characteristics, the nascent entrepreneurship and firm characteristics. According to Wilken (1979), other factors influencing the entrepreneurial appearance were mobility, marginality, the social stratification system, the need of achievement, motives and the withdrawal of status and respect. Entrepreneurship was characterised by Wilken (1979) as dynamic and expansive, whilst the entrepreneurs as able to change policies in the state as “major actors” of the era. Other authors who characterised the entrepreneurs were Scase and Goffee (1982). These authors revealed a theory, which differentiated between entrepreneurial element and the labour force. They stated that the salaried force, are individuals who are selling their labour, whilst the entrepreneurs are individuals who are buying. Additionally, the entrepreneurs have both capital and labour force for the purpose of economic gain or profit.

Richard Cantillon in his book “Essay sur la nature de

commerce en general” published in 1755 defined the entrepreneur as: “...an individual who operates under condition where the expenditures are known and certain, but the incomes are unknown and uncertain” (Binks and Vale, 1990, p. 9) For an improved understanding of the entrepreneur and his/her role, Global Entrepreneurship Monitor (GEM) provided a more holistic approach of the entrepreneurship, and defined this as follows: “Any attempt, at new business or new venture creation, such as self-employment, a new business organisation, or the expansion of an existing business by an individual, a team of individuals or an established business” (GEM, 2012, p. 9) Professor of Economics, Jean-Baptiste Say regarded the entrepreneur as a phenomenon able to bring together the components of the production process. In the same manner, Leibenstein regarded the entrepreneur as an individual who synchronizes inputs, whilst Drucker saw the entrepreneur as a person who provides competitive advantages (Binks and Vale, 1990, p. 11).

The word “entrepreneur” comes from the French word

“entreprendre” meaning “to do something” (Swedberg, 2000, p. 11).

It is important to acknowledge and emphasise a book of resonance for the world of entrepreneurship, by Drucker (2015) and entitled ‘Innovation and Entrepreneurship’. Entrepreneurship, according to Drucker (2015, p. 31) is based on the ‘theory of economy and society’. It is the perpetual change brought by the entrepreneurial process, which affects both economy and society.

What defines both the entrepreneur and

entrepreneurship is “the entrepreneur searches for change, responds to it, and exploits it as an opportunity” (Drucker, 2015, p. 33). It is suggested that changes come through innovation such as new technologies. He also argued that “knowledge-based innovation is the ‘super-star’ of entrepreneurship” (Drucker, 2015, p. 131). Drucker (2015) speaks about the knowledge-based innovation that can be embedded into technology and places emphasis on the role of computers. In conclusion, there is significant number of definitions for the terms ‘entrepreneurs’ and ‘entrepreneurship’, together with all inconsistencies and misunderstandings regarding these two concepts. This thesis considers a dual perspective: (a) Drucker’s (1985; 2015) perspective on innovative enterprise, and (b) Penrose’s (1960) perspective on growth and management with the corresponding schools of thought represented by Jean-Baptiste Say and Joseph Schumpeter. The rationale for preferring these perspectives is that, these interpretations of the meaning of entrepreneurship allow the researcher: (a) to explain the role and impact of the Digital Platforms & ICTs and Learning on WES and (b) the empirical analysis of WES and business growth. These perspectives also, allow the author to create a link to women’s entrepreneurship, Digital Platforms & ICTs and CoPs & networking. 2.1.6 The Phenomenon of Women’s Entrepreneurship In 1956, Harvard Business Review published for the first time a gendered article entitled “Successful Wives of Successful Executives”, which emphasised the social status and focused on the career opportunities for a particular segment of women population, such as the wives of vice presidents, presidents and board chairmen (Warner and Abegglen, 1956). It follows that very few women had the chance to choose their careers, let alone the opportunity to become entrepreneurs.

Accordingly, Brush (2008) argued that

entrepreneurship was a “man domain” and a range of definitions characterised the entrepreneur as “captain of industry” (Schumpeter, 1934); “heroes who perceive gaps” (Liebenstein, 1968) and “key man” (Collins and Moore, 1964). In spite of this reality, 51

two decades later, articles on female entrepreneurs started to emerge and the first remarkable pioneering article written by Eleanor Brantley Schwartz (1976) appeared in the 1970s: “Entrepreneurship, a New Female Frontier”.

The article highlighted

similarities between men and women entrepreneurs’ motivation to start up a business. This was followed by further articles written by Hisrich and Brush (1983, 1984, 1985, 1986 and 1987) who depicted the characteristics of women entrepreneurs, and Watkins and Watkins (1983) who conducted a research on biases against women in the UK (Brush, 2008). Brush (2008) stated that the increase in the number of publications regarding women entrepreneurship was the result of the spectacular rise of this phenomenon in the US, the world leader in women’s entrepreneurship. Thus, according to several American publications (The Bottom Line, 1978; A Report of Bureau of Labour, 1979; Hisrich and Brush, 1986) within an interval of twelve years (1972 -1984) the number of self-employed women increased from 1.5 million in 1972 to 3.5 million in 1984. Furthermore, about 700.000 women who owned businesses in 1977, in the US, generated $41.5 million in revenues. Further research such as that conducted by the Centre for Women’s Business Research (2005) provided information regarding the increase in number of women-owned firms to 10.6 million out of a total of 22 million firms in the US, bringing a contribution of $ 2.5 trillion in sales and employing 19.1 million employees (Brush, 2008). Although the rise in the number of women entrepreneurs was considered a phenomenon, a number of studies focused on the extent of research on women entrepreneurs, and concluded that, this kind of research was rather lacking comparability with the research conducted on their male counterparts (Brush, 1992; Brush, 2008). In the last years, the Diana Project assessed seven important journals on entrepreneurship across the years, and found that only about four percent of all articles concerned women entrepreneurs (Gatewood et al., 2003; Brush, 2008). Brush (2008) stressed three possible explanations of the lack of research studies on women entrepreneurs: (a) the rise in women entrepreneur was still considered a new phenomenon (1980s); (b) the presumption that there were no differences between men and women entrepreneurs; (c) the lack of institutional support and funding. Additionally, there is a general truth that the US is a global leader in women’s entrepreneurship and there has been more interest in female entrepreneurs in the US and Canada than in the UK (Gertner, 2013).

Besides the significance of women’s entrepreneurship phenomenon, equally important is the effort in providing a general definition of women entrepreneurs. Thus, Sara Carter and Tom Cannon provided the first recognised definition of the term “female entrepreneur”: “...includes women in a wide variety of industrial sectors, using different forms of ownership structure with contrasting personal experience” (Carter and Cannon, 1986, p. 3) Similarly, Carter and Shaw (2006) defined a female entrepreneur as being a woman who owned the whole or majority of the business. Carter and Shaw (2006) stated that women entrepreneurs are talented, however, overlooked groups of entrepreneurs with a significant contribution to the economy. According to these authors, statistics indicated that women-owned businesses covered 16% of the business stock and 27% of the selfemployed population in the UK. However, Burns (2011) stated that, there was no generally accepted definition of the term “entrepreneur” or for the “female entrepreneur”. Nevertheless, the “female entrepreneur” concept is difficult to define. This concept has been associated by Penrose (1959, p. 33) with “...the temperament or personal qualities of individuals”.

By contrary, to understand and define the concept of “female

entrepreneur” it needs to emphasise what Chell (2001) suggested. Thus, Chell (2001) recommended the need to acknowledge the role of women within the post industrial revolution. There were also disputes regarding women’s subordination in capitalism (Ramazanoglu, 1989) and differentiation in the meaning of ‘woman’ concept, according with the historical context (Bradley, 1996). In other words, the post industrial revolution placed women within the domestic environment. Consequently, this led to employment segregation and gendering of work, thus limiting women choices of jobs to the lowest paid sectors of economy. Chell (2001) highlighted words such as “homework”, “clandestinely”, “tough”, “inequality”, “invisibility” and “exploitation” when referring to first women entrepreneurs and the first type of homework: sewing and embroidery. Further, Chell (2001) emphasised the extreme difficulty encountered by the first business women when breaking through the social and cultural barriers to enter the business world of men. In 1978, the article “A Look at the Female Entrepreneur” published by the American Journal of Small Business, acknowledged that it was the goal of the American

national commitment that “...the equality finds expression in the business world” (Burr, 1978, pp. 1-4). Thus, women became entrepreneurs in order to avoid low pay, escape supervision and the “glass ceiling” phenomenon that created vertical segregation (Birley, 1988; Mattis, 2004). Similarly, Knorr (2011) stressed on the existence of a vertical segregation and claimed that, there were still barriers for women in the top management career, such as: stereotyping, discrimination, existence of male dominant cultures within organisations, less access to career development and exclusion from networking. These premises, they suggested, led women to entrepreneurship. Female motivations when entering entrepreneurship were: job satisfaction, independence and achievement, career or income options (Gertner, 2013). They proved to have a high degree of self-confidence, social charm, the willingness to take risks, immense curiosity, ability to think clearly, keen intuition, and were articulate, more energetic, socialcompetitive, perfectionists, goal oriented (Taylor, 1988, p. 17; Hisrich and Ozturk, 1999). Bolton and Thompson (2013) advocated a “performance triangle” as the requirement for any entrepreneur: talent, temperament and technique. Despite the rise in the number of women entrepreneurs over the last 20 years, it is argued that, there are still many premises within the social context of every country that actually have been neglected by the research and policy makers. Since 1976, several authors (Carter and Cannon, 1992; Carter et al., 2001; Burns, 2011) have confirmed the increase in the number of women in the labour force. Similarly, the European statistics (EC, 2011) demonstrated that female employment rate rose to 12.5% and the proportion of female entrepreneurs was 33%. The application of the European Directive (EU, 2011) should remove the barriers that women entrepreneurs face. However, the position of women in the labour force remained unchanged and they still faced social conditions, which could be considered hostile, such as: low-paid, unskilled or semi-skilled positions; employment was mainly part-time and concentrated in the retails and service sectors (Carter and Cannon, 1992; Carter et al., 2001; Burns, 2011). Research indicated that women were placed in two main sectors: distribution, hotel, catering, and other services. About 41.8% of female self-employment was concentrated within the distribution, hotels and catering, whilst 30.5% was located in other services (Carter and Cannon, 1986). In 2006, research carried out by Carter and Shaw (2006) 54

provided further overview of the social context of women’s entrepreneurship. The selfemployment situation is provided in the Table below (Table 2.3): Table 2.3: Self-employment situation/categories Skilled Trades(M) Managers and Personal Services Senior (F) (%) Officials (%) Male Female

39.4 19.6

Associate professional and technical (%)

Professional occupations (%)

13.5 19.6

13.1 11.8

16.3 22.1

Adapted from Carter and Shaw (2006, p. 6)

Compared to the US which is the world leader in female entrepreneurs, in the UK, in the last decade, there was a static process regarding the female share of self-employment (2627%), whilst in the US female share of self-employment has increased constantly reaching about 39.6% of the total self-employment (Carter and Shaw, 2006). Accordingly, there was a rapid recognition of the position of women entrepreneurs within the labour market, society and economy (Carter and Shaw, 2006). 2.1.7 Business growth and women entrepreneurs’ success Coulter (2000) defined entrepreneurship as the process where individuals search for opportunity to create new products and services by innovation. The entrepreneur is depicted by Coulter (2000) as an individual who starts and operates a venture, displays a high level of determination, assertiveness, and accepts risks in order to achieve success. In Coulter’s (2000) view, entrepreneurial growth is associated with the increase in level of outputs. Nevertheless, Coulter (2000) describes another aspect of growth, which comprises enthusiasm and energy. There is no standard definition of growth. A robust definition was provided by Cardozo, Harmon and Ardishvili (1995, p. 4) who considered growth as “a change in size or magnitude from one period to another”. However, a study by Dalborg, von Friedrichs and Wincent (2012) emphasised that women entrepreneurs have a different perspective on growth. In other words, they perceive business growth as related to a good reputation and people’s appreciation of their effort and contribution. Consequently, there is a preference for qualitative growth, rather than quantitative growth. A different hierarchy of needs for women entrepreneurs supports this affirmation.

For instance, women

entrepreneurs wish to have firstly, business survival and stability (Dalborg, von Friedrichs

and Wincent, 2012) and this is followed by self-development or self-actualization (Maslow, 1934; 1993). According with Schumpeter (1934, p. 93) and Dalborg, von Friederichs and Wincent (2012), women and men entrepreneurs are motivated in their efforts of business growth by the â&#x20AC;&#x153;joy of creatingâ&#x20AC;?. These statements confirm research by Brush et al. (2004) and Costin (2012) who also, discovered that women entrepreneurs have the inclination to measure business growth based on criteria such as: quality of products and services, and quality of the relationships with customers and entrepreneurs. It infers that, besides the general accepted definition of business growth (increase in profit and sales), most of women entrepreneurs, have an additional perspective on growth, placing emphasis on non-economic side of the concept: the quality of the service, reputation, helping others, satisfaction, creating harmony and caring for the employees (Costin, 2012). Many authors (Carter and Cannon, 1986; Reese and Aldrich, 1995; McClelland et al., 2005; Bogren et al., 2013) gathered around a very debatable issue, such as, networking. They explained entrepreneurial networking and flexibility as a crucial factor for business growth and survival, whilst other authors (Gunther McGrath, 2012) provided recipes for growth, such as speed and adaptability. From a gender perspective, a research conducted by Roomi, Harrison and Beaumont-Kerridge (2009) and Mitchelmore, Rowley and Shiu (2014) indicated a few factors impacting the growth of small businesses owned by women entrepreneurs: networking, successful website, entrepreneurial training, entrepreneurial competences, business and management, the right location, marketing and selling skills, etc. Indrupati and Henari (2012) confirmed that social networking is at the heart of both entrepreneurial success and business growth. Digital platforms development such as Linkedin and Facebook offer businesses a unique advantage. McClelland et al., (2005) in their study on female entrepreneurs across six countries found both a strong business social orientation and an altruistic desire of women entrepreneurs to contribute to community and society. In the same way, a previous study (Barkham et al., 1996) conducted a research on the relationship between the owner managerâ&#x20AC;&#x2122;s characteristics (educational background, work experience and motivations) and business growth, and discovered that education, prior managerial experience and age, were considered

determinants for business growth. This research supports the theory of “human element” or individual’s capabilities as key factor for business growth (Penrose, 1959). There are a number of suggestions regarding growth measure. The most common are financial measures such as increases in sales or revenues (Coulter, 2000). Nonetheless, there are a few more recommendations regarding additional methods of measuring growth: the numbers of customers, location, product development, number of employees (Coulter, 2000). An alternative measure of growth, is recommended by Cressy (2008), and originated from Bolton’s (1970) definition of small businesses (location, employment and output). In Cressy’s (2008) view, variables such as employment, sales and assets are solid, and they should be expressed “as a rate per annum”. Nevertheless, for some authors (Reijonen and Komppula, 2007) business growth is not a business objective neither a measure of success. The author of this research uses ‘sales’ and ‘profit’ as measures of growth. This study endeavours to explain the meaning of further terminology employed by the research: women entrepreneurs’ success.

What are the definition and the meaning of

success? The term “success” was defined by Bartlett (1988, p. 48) as “the achievement of a given objective” or “the degree of accumulation of wealth...”. A recent study by Gimson and Mitchel (2008) provided another perspective and defined success as being a belief in what one can do. Although the monetary reward is a key measure of capitalism, Bartlett (1988, p. 50) suggested a second definition by designing an equation with only two terms: “success” “equals” “growth”, but growth in his opinion implies “size”. In other words, if the research talks about increase in self-confidence and enthusiasm, it highlights ‘success’ which is however, equalled to ‘growth’. Nevertheless, when the research introduces the term “size”, then it emphasises the second aspect of “success”, the growth. Consequently, growth is an aspect of the concept ‘success’. Authors like Weber and Geneste (2014) described ‘success’ as having a dual aspect ‘intrinsic and extrinsic’, according to the dual aspect of the concept ‘motivation’, which is ’intrinsic and extrinsic’ (Kuratko et al., 1997). A definition of success, based on the financial aspect only, it seems to be insufficient and inadequate. Consequently, based on the research by Kuratko et al., (1997), Weber and Geneste (2014) suggested a more holistic definition which incorporates both aspects: intrinsic and extrinsic, or in other words, financial and non-financial aspects, where the non-financial aspects refer to ‘style 57

of life’, ‘time flexibility’, ‘work-life balance’, ‘achievement’, ‘time for self and family’ (Weber and Geneste, 2014). A study by Foley and Green (1989) produced a list of criteria for success. Between these criteria, it could be mentioned: job satisfaction and independence, creativity and innovation, acquiring business skills, the opportunity to create jobs and customer satisfaction (Foley and Green, 1989). Similarly, Reijonen and Komppula (2007) found corresponding meters of success: job satisfaction and customer satisfaction or good customer relationship (Reijonen and Kompulla, 2007; Taylor and Murphy, 2004). A recent study conducted on women entrepreneurs in Wales and England by Mitchelmore, Rowley and Shiu (2014) highlighted the following competences for business success: desire to succeed, perseverance, passion, communication and interpersonal skills, confidence, customer relationship and understanding, and management. The prescription for success contains the following components: knowing the route and direction, perseverance, capability to find opportunities and matching the needs of the enterprise with the resources and self-discipline (Bartlett, 1988). From a non-gender view, Taylor and Murphy (2004) pinpointed a few success factors for e-business growth and success. Between these, it is worth to mention owner experience, managing growth, innovation, resources (money, technology and people) and acting in a growth market. One of the latest gendered research depicted entrepreneurial success as “satisfaction with one’s career” or “personal happiness”; the component elements of women success were discovered to be: “entrepreneurial outcome, attitudes, personal and social adjustment, health, and of course, the growth in sales and number of employees” (Sullivan and Meek, 2012, p. 432). Additionally, these authors introduced a new approach to research on women entrepreneurship, by initiating five categories of successful results: successful enterprise launch; psychological and health outcomes; increase in owner’s income; enterprise growth and enterprise survival (Sullivan and Meek, 2012, p. 450). Again, this is a new approach to women entrepreneurs’ success, just by considering business survival or improved health and even though the launch of a business, are together matters of success. Maslow (1998, p. 9) defined “happy people” as “the ones who are working well at something they consider important”.

According to the principles of utopian society, the business community created by women entrepreneurs should be based on trust, information, achievement, friendship, morality and honesty (Maslow, 1998). Maslow (1998, p. 1) defined ‘work’, as a psychological and psychotherapeutic process, where individuals “assimilate their work into [their] identity, into the self” and “[they] grow toward self-actualization”.

Barriers to women

entrepreneur development and success, according to Lockyer and George (2012) were the following: location, the region lacking participation in higher education and entrepreneurship, lack of marketing and business skills and some personal barriers such as family and care responsibilities, lack of business support network and the absence of role models. The results of the literature review conducted by the author on this section, strengthened the idea that women entrepreneurs are an ‘untapped resource’ and further research should be carried onto women owned businesses (Lawton, 2010).

There are no

theoretical business models for WES (Brush, deBruin and Welter, 2009). There is no sufficient research on women’s perspectives regarding the performance of women entrepreneurs (Carter, 2000). Factors that affect business growth and success it seems to be studied in isolation and not in relationship with other factors (Reijonen and Kompulla, 2007). Furthermore, there is insufficient literature developed on women entrepreneurs and research produced by women researchers – lack of PhD dissertations on women entrepreneurs (Mattis, 2004). Particularly important is the fact that, there is no methodological design rigor, and combined inductive and deductive approaches are few (Hirsch and Drnovsek, 2002). The next section approached in this chapter refers to Learning. 2.2 A PERSPECTIVE ON LEARNING This is a new perspective upon learning concept, which endeavours to replace the concept of Education Entrepreneurship (EED) with Learning, for the purpose of this research only.

Education is the foundation of national economy and therefore, the section

emphasises the role of learning as a means for women’s opportunity and selfemployment. Further, the concept of learning is presented in this thesis as embedding two main components: (1) learning for entrepreneurs; (2) training to create an enterprise. This study explores learning from two perspectives: a) the woman as a learner, and b) the learning process. Therefore, within this chapter the focus is on women entrepreneurs as 59

learners, and the entrepreneurial learning process. The section introduces information regarding women’s opportunity, the learning process, methods and styles of learning, models of learning and entrepreneurial learning, from different perspectives. The chapter ends with a summary, presenting the essence of the chapter. 2.2.1 Learning and Women’s Opportunity Schumacher (2011) brought to attention, the importance of meta-economics which studies the man [sic] and his environment and argued that “the man” is who provides the main resource of the economic development, and this is “the human mind”, whose strength comes through “education” or “learning”. Maslow (1998, p. 2) saw education as the process of “reaching the whole human species”. Whilst, Schumacher (2011) stated that “education” with its learning component, is the most important resource and “the key” of survival, in order to cope with the change, for the benefit of man [sic]. Dewey (1921) described learning as a necessity of life with a social function.

emphasized the role education and learning play in the continuity of life, and within the communication of ideals and values of society. Bloom (1964) argued that individuals could not learn indeed, unless they use the time dimensions. In other words, women entrepreneurs gain and improve their business/managerial capabilities through learning, over a long period. In addition, Watkins and Watkins (1995) found that, the reasons for women adopting an entrepreneurial career were either family history, having fathers/mothers who were also entrepreneurs, or educational background. The majority of female entrepreneurs based their businesses on educational process, even though this was not relevant for their career (Watkins and Watkins, 1995). Cooper and Davidson (1982) argued that women faced the pressure of inflation, the women’s movement and the psychological need to create their new identity. They were also influenced by work overload, by being undervalued by their male counterparts, and by the lack of managerial skills, or even by the culture trap; as well as the above, there were barriers to socialization and sex stereotyping. All these affected women and determined them to engage within full time career and education. Although, there were various governmental initiatives to encourage and give women opportunity to start businesses, Marlow and McAdam (2010) claimed that, their number was limited and there was still a lack of successful women entrepreneurs.

Similarly, a recent study conducted by Davis (2012) discovered the lack of learning, training and professional development for women entrepreneurs. Moreover, Gertner (2013) noticed the existence of a positive relationship between education and entrepreneurship and higher education strengthened women opportunities to become entrepreneurs. Since the 1990s, Allen and Truman (1991) highlighted a demand for female counsellors, in entrepreneurial agencies, trained to understand women entrepreneurs’ needs, and the training support required by them, eventually, the necessity of single sex training. Additionally, De Faoite et al. (2004) indicated the effectiveness of mentoring and networking along with entrepreneurial support from different institutions and academics. 2.2.2 Learning Process. Methods & Styles of Learning Learning is an ‘acquisition’ of knowledge and a life-long process (Honey and Mumford, 1992). According to Kolb (1984) learning is the process of human adaptation, which can provide “bridges” such as school and work. According to Dewey (1910), the learning process comprises two components: direct understanding, called apprehension and mediated understanding, called comprehension. Learning is the process where the development occurs (Kolb, 1984, p. 132). The characteristics of learning are as follows: a) learning is a continuous process based on experience; b) it requires a solution for the conflict between different modes of adaptation to the world; c) a holistic process of adaptation to the world; d) involves transaction between the individual and the environment; e) a process of creating knowledge (Kolb, 1984). The benefits of learning are competence development, career prospects improvement, personal satisfaction and financial rewards, plus psychological and social rewards (Mumford, 1995). Lovell (1980) drawing on Maslow’s research, suggested that individuals need to be motivated towards the satisfaction of their basic needs. As a result, the catalyst, for both learning and satisfaction of their needs, is the self-concept, which includes three components: self-image, ideal-self and self-esteem. In other words, the impression individuals have about themselves, the way they would like to be, and the perception of the self, or their achievement.

Additionally, socio-cultural theories (Higgins and

Aspinall, 2011), pointed out the relationship between individual learning and social identity and defined learning as the acquisition of knowledge and identity. Therefore, they saw learning as the way of “being in the world”. Lovell (1980) stated that, the way 61

individuals learn is dependent of both own abilities and previous experience. Thus, Kolb (1984) demonstrated that people learn from experience. Subsequently, all universities and colleges accepted experience-based education.

Moreover, this theory offers the

foundation for the lifelong learning process. Yet, this theory has its own critique. Nevertheless, Kolb’s (1984) theory assists the presumption that women’s development and progress are based on education and learning. Bandura and Walters (1963) noticed another method of learning, social learning, based on observation.

They developed the theory that learning takes place through the

observation of high-reputation models. In other words, the learners develop a similar performance through the observation and acquisition of models’ behaviour. The next method of learning, considered by the thesis is the adult learning. In line with this, Fontana (1995) enquired how learning takes place. He described it as a very complex phenomenon, and argued that many aspects are affecting learning. Fontana (1995) highlighted that within the learning process, the learner himself/herself changes as a result of the learning experiences he/she encounters, and as a result of his/her actions, within that environment and upon the environment.

In other words, the learner suffers also,

some kind of changes or transformations. Learning, as described by Fontana (1995) produces an immediate and irrevocable benefit, which can lead to success. According to Maslow (1970) there are discussions regarding the proximity to ‘survival level’, which can affect upon the urgent need to learn. It infers that, the adult individuals should be treated differently and according to their learning needs and in relation to their phase in the business cycle. Conform to Maslow (1993), every individual has embedded within, the desire of growth in order to achieve the level of his/her full potentiality. He named this concept as “full humanness” instead of ‘self-actualization” (Maslow, 1993, p. 27). Further, he stated that self-actualizing people are “very good perceivers of reality and truth” (Maslow, 1993, p. 117). It infers that, this demand of self-actualization is achieved by learning. Another aspect of adult learning, highlighted by Jarvis (2004), is the knowledge and its relativity. This infers a demand for permanent access to learning and continuity in learning, or lifelong learning (Jarvis, 2004) as a solution to disparities in the global market in which the entrepreneurs activate. The adult learning implies not only thinking, ‘which goes beyond the observation’ (Dewey, 1910, p. 3), but also involves reflection, which ‘aims at knowledge, belief, facts and truths’ and suggests the creation of a link between 62

these elements (Dewey, 1910, p. 3). Besides this, the adult learning implies an experience of thinking, and higher-order mental skills and capabilities, which involve more than application of the knowledge, gathered in the learning process. Thus, adult learning comprises analysis and evaluation (Jarvis, 2005). It is important to place accent, on not only age, gender and maturity (wisdom) of the learner, but also, on the styles of learning adult individuals employ within the learning process (Fontana, 1995). It is also important to mention the components of adult learning. The adult learning comprises both formal and informal learning. The formal learning includes internal and external courses, projects, task groups, reading and being coached. The informal learning includes also, besides many other elements such as, (1) learning from ‘errors’, (2) being mentored, (3) learning from everyday life, (4) meetings, (5) attending and participating in conferences, associations and (6) networking (Mumford, 1995). These are major elements of learning taxonomies (Bloom, 1960) and elements of the cognitive domain (Reece and Walker, 2007). Moreover, in adult learning, the process of ‘learning’ is a basic human need (Jarvis, 2004; Maslow, 1993). In addition, within the learning process, there are additional classifications of the styles of learning. Honey and Mumford (1992) described four principal styles of learning: activist, reflective, pragmatist and theorist. Activists emerge themselves into new experiences, generate ideas and involve others in solving problems. Reflectors, considers the problems from all angles, observe and think before taking decisions or actions. Theorists, combine observations and theories, and follow a logical thinking. Pragmatists, experiment ideas and theories in practice, always planning ahead (Honey and Mumford, 1992). 2.2.3 Models of Learning A model of learning is a framework, designed by experts in the field of pedagogy and andragogy, for teaching and learning purposes, in view to combine learners’ needs, and teachers’ approaches to knowledge delivery, in a holistic and coherent manner (Reece and Walker, 2007). The pedagogical approach to teaching and learning is a teachercentred technique, with a low level of participation from students. The andragogic approach is rather a student-centred approach, and is about the methods used by professionals, to teach adults. In other words, ‘andragogy is how adults learn’ (Reece and Walker, 2007, p. 112). The adult learners select a self-directed and individual approach to learning, whilst teachers have the responsibility to assist them in developing 63

this capability, by enhancing their participation, and by helping them to evaluate and reflect on their learning (Knowles, 1970; Mezirow, 1981; Reece and Walker, 2007). The characteristics of adult learning are as follows: (1) the acknowledgement of the need to learn; (2) the ‘self-concept’ notion, which allows them to develop their own directed learning; (3) the experience; (4) the motivation to learn; and (5) the orientation towards learning, as a request for life and business (Knowles, 1981). There are various classifications of the learning models. In the next lines, the author enumerates a few models of learning: teacher centred and student-centred models; objective and process models; serialist and holist models; the continuum learning models. This thesis discusses the continuum learning models, such as behaviourism, cognitivism and humanism (Reece and Walker, 2007). Behaviourism is founded on the ‘stimulus response’ approach, and leads to teacher control. Cognitivism is based on the idea that learning occurs by consistent presentations of information, through case studies, debates and readings. Humanism is rooted in the theory that, ‘learning is individual’ and selfdirected (Reece and Walker, 2007). A charter for Andragogy, designed by Mezirow (1981), presents the main features of Andragogy: (a) organises learning according to student needs; (b) encourages decision making and self-evaluation; (c) facilitates problem solving; (d) encourages self-concept; (e) focuses on experiential methods; (f) decreases teacher dependency; (g) helps students to find their needs and (h) defines learning objectives (Reece and Walker, 2007, p. 114). From the analysis of the chart, it is obvious that, a humanistic model is more relevant for the adult learning (Reece and Walker, 2007). In line with the main features of the Andragogy, this thesis presents also, Kolb’s (1984) experiential learning model. Kolb’s experiential learning model is very important for the design of the final andragogic model of learning for women entrepreneurs, and for the interpretation of the results of this research. Thus, Kolb (1984) highlights that, at the foundation of the approaches to experiential learning theory, are three main models of learning: Lewinian model of action research, Dewey’s model of learning, and Piaget’s learning and cognitive development model. According to the Lewinian model of action research, the learning process includes four stages: (1) concrete experience, (2) observations and reflections, (3) formation of abstract concepts and generalization and (4) testing implications of concepts in new situations. The second model is Dewey’s model of learning, which describes how learning transforms the impulses of concrete experience into action. The last model is Piaget’s model of learning, in which the 64

dimensions of experience and concept, reflection and action, are the foundation for the development of adults’ thought (Kolb, 1984). Based on these three models of learning, Kolb (1984) designed his experiential learning model. According to Kolb (1984) the characteristics of experiential learning are: (1) learning is a continuous process; (2) learning is rooted in experience; (3) learning is a holistic process of adaptation to everyday life; (4) learning asks the learner to change, according with the requirements of the context and environment; (5) learning involves negotiations between the person, and the environment; and (6) learning is the process of producing knowledge. The experiential learning cycle comprises four types of learning experience: (1) concrete experience, (2) reflective observation, (3) abstract conceptualization and (4) active experimentation (Kolb, 1984). 2.2.4 Entrepreneurial Learning “...very few empirical studies ...examine learning in entrepreneurship...” (Marvel, Davis and Sproul, 2016, p.611) There was a change in perceptions of the British Government, towards the encouragement of SMEs, and reinforcement of policies, which support the development of SMEs. Thus, in order to equip the country, with an entrepreneurial capability, able to adapt to the changes in the market and the new technologies, the British Government placed emphasis on training and policies, which are required, in order to ensure the entrepreneurial development (Matlay, 1999). Nevertheless, comparing with other European developed countries, the British labour force lacked education and training, and the knowledge of entrepreneurship was still a paradox (Matlay, 1999). It is also well known that, small firm growth is an intricate and gradual process, which demands persistently, knowledge and information along the life cycle of the business (Deakins and Freel, 1998). The economic input of women entrepreneurs is worldwide recognised, and women’s entrepreneurship is rapidly evolving (Jamali, 2009; Davis, 2012). However, almost two decades later, there is still a lack of entrepreneurial training, and research indicates the need of business skills training, for women entrepreneurs, based on training needs analysis (Davis, 2012). Research conducted by Davis (2012), discovered also that, a number of studies carried across the globe, indicated the global lack of business skills for women entrepreneurs. Recent research (Tynan et al., 2009) indicated that, gender-neutral 65

training for women entrepreneurs, lacks substance, and gender is an essential factor for entrepreneurial learning (Ettl and Welter, 2010). Therefore, research highlighted the necessity to consider also, when conducting the training needs analysis, the barriers women entrepreneurs encounter: prejudice, gender, stereotypes, patriarchal culture, and life work balance (child rearing) (Davis, 2012). “Learning is a process, whereby knowledge is created through the transformation of experience” (Kolb, 1984, p. 38). Some authors (Kitching, 2008) stated that learning is ‘tacit’ and that most of the learning is the result of ‘on-the-job’ training, which is part of the skills policies within any employment. Entrepreneurial learning refers to knowledge, informations, and business skills such as: sales, marketing, finances, IT, negotiation, and communication acquired by women entrepreneurs, within the formal and informal types of learning (Davis, 2012; Kolb, 1984). According with Boeren (2011) there are three types of adult learning: (a) formal learning, which takes place within the formal educational system and leads to certification (Czerkawski, 2016); (b) non-formal learning, which takes place outside of the educational system; (c) informal learning, which takes place within the daily life activities, and involves: conversations, informations from radio and television, computers, libraries and learning centres. This type of informal learning is not assessed (Czerkawski, 2016). Entrepreneurial informal learning activities emerge from women entrepreneurs’ participation in networks and business associations (Davis, 2012). A type of non-formal learning, for women entrepreneurs is the ‘experiential learning’ and ‘learning by doing’ with reflective practice (Sarri, 2011). There is an additional classification of learning offered by Kyrgidou and Petridou (2013). This includes mentoring, e-mentoring and learning networks for mentees.

Thus,

mentoring is a special relationship created between mentors and mentees, with regard to the knowledge and skills, mentees acquire from their mentors along a period of time. Ementoring is a dual relationship and a common e-database, beneficial for both sides, that leads to learning networks creation (Kyrgidou and Petridou, 2013). An assessment of the effectiveness of mentoring training program of experienced entrepreneurs, in view to mentor women entrepreneurs as mentees, for business start-up and development, provided evidence regarding the benefit for both mentors and mentees (Sarri, 2011). Authors (Son, 2016) argued also about a second benefit of the mentoring program, which 66

leads to mentee’s socialization and introduction to formal networking within their field of activity. Furthermore, mentoring, is learning from the experience of others (Sarri, 2011), not only from own experience or ‘trial-and-error’. Recently, Dixon (2017) suggested that virtual teams facilitate learning, by creating an organisational learning environment with routines, which facilitates distance learning and collaboration between individuals. In addition, a similar type of learning, regarded as a dynamic capability of the firm, is the social networking (Pedler and Burgoyne, 2017). Learning networks (Czerkawski, 2016) refers to social connections by means of technology, which facilitates formal and informal learning. The positive impact of CoPs & networking is highlighted by many research studies across the globe (Davis, 2012). Czerkwaski (2016) argued that most of the adult learning is informal, rather than formal. Moreover, Czerkwaski (2016) mentioned the role of the lifelong learning, as a continuous learning process, essential for the rapid changing society. Austin and Nauta (2016) investigated the entrepreneurial role-model exposure of women entrepreneurs, their number, and the intensity of women entrepreneurs’ interaction with their role models. The results indicated benefits from the exposure to a large number of role models. Further, the sex and the intensity of interaction, was not significant for women entrepreneurs. Dixon (2017) highlighted the role of learning, and the ability to learn, in the information society, where keeping the pace with knowledge and information is critical for the survival of individuals and businesses. The author of this thesis discovered the following factors which can be considered, when assessing women entrepreneurs’ learning and training needs: (1) pitching the women’s training at the correct level; (2) flexibility (duration and time); (3) the sex of the role models; (4) marketing campaign and terminology, appropriate for women entrepreneurs; (5) structure and content of the learning program; (6) gender and sex concepts; (7) digital platforms, mobile technologies and virtuality of learning; (8) geographical location; (9) access to information and networks; (10) women’s confidence; (11) adult learning approach; (12) sector of activity; (13) glass ceiling barriers; (14) patriarchal cultures (Tynan et al., 2009; Boeren, 2011; Kyrgidou and Petridou, 2013; Dixon, 2017; Kzerkawski, 2016; Davis, 2012). This section indicated a positive relationship between learning and entrepreneurship (Gertner, 2013). Furthermore, learning is the acquisition of identity and creation of knowledge (Higgins and Aspinall, 2011; Honey and Mumford, 1992) which produce 67

development (Kolb, 1984) that could lead to success. The section pinpointed to various methods of learning. Between these, the author enumerates the most significant: experience-based (Kolb, 1984), lifelong learning (Jarvis, 2004), and adult learning (Bandura and Walters, 1963; Fontana, 1995).

These methods of learning have the

capability to produce benefits for the learner and to provide self-actualization, which is a ‘human need’ within the Hierarchy of Needs’ and a qualitative perspective on women entrepreneurs’ success (Maslow, 1993; Fontana, 1995). Various styles of learning such as informal, non-formal, and experiential (Sarri, 2011; Davis, 2012; Boeren, 2011) go beyond the observation and involve reflection, analysis, participation, networks and virtuality (Dixon, 2017; Czerkawski, 2016; Austin and Nauta, 2016).

The section

highlighted that the main Model of Learning is Andragogical, learner-centred approach (Kolb, 1984; Reece and Walter, 2007). The literature review on entrepreneurial learning revealed a lack of empirical studies on learning needs for women entrepreneurs, and women’s perspective on styles of learning (Edwards and Muir, 2005). There is also need for efficient active learning within a firm (Farr-Wharton and Brunnetto, 2009). Further, Higgins and Aspinall (2011) highlighted the lack of research on methods of learning. In addition, Petridou, Sarri and Kyrgidou (2009) emphasised that a focus should be placed on entrepreneurial learning and learning needs for women’s success. The next section of particular importance, to be discussed it refers to CoPs & networking. 2.3 COMMUNITIES OF PRACTICE AND NETWORKS 2.3.1 Introduction This section introduces the concepts of Communities of Practice and Networks, and explains the role of knowledge, and its transmission by means of CoPs & networking. Knowledge is an essential resource for entrepreneurial process, leading to women entrepreneurs’ success. Moreover, knowledge and information are communicated with unprecedented speed and therefore, knowledge can become a perishable (Drucker, 1967) item if is ‘static’; but a shift from knowledge to ‘knowing’ as a dynamic process, leads to economic growth. The section emphasises the role of CoPs & networking in knowledge creation, transmission and sharing.

Schumacher (2011) argued that education is the transmission of ideas that allow man [sic] to select between things, and the knowledge is an essential element of education and learning. In 1964, Drucker stated that knowledge is a “universal social resource” instead of a business resource and described this as a crucial resource. This statement was reinforced by Higgins (2009) who depicted knowledge as a social expanding process. Drucker (1967, p. 140) defined the right knowledge as “the knowledge needed to exploit the market opportunities”.

Furthermore, Drucker (1967) questioned the quality of

knowledge and how effective the “right knowledge” was used. Correspondingly, Zenger (2013) developed a further theory and indicated that entrepreneurs [sic] need to use their knowledge and experience to find valuable resources, which can lead to success. Research has found that the knowledge is either the consequence of the “negotiation” (transaction) between social knowledge and personal knowledge, or the result of a multitude of experiences within the learning process (Kolb, 1984). Hayek (1994, p. 260) stated that knowledge “is not given to anyone in its totality” and Drucker (1967) noticed, “knowledge is a perishable commodity”. Other authors such as Higgins and Aspinall (2011) highlighted the shift from “knowledge” to “knowing” within the process of understanding knowledge in the small businesses. They stated that, knowing could not be understood as a static thing, but as a dynamic process. According to the economic perspective, knowledge is associated with economic growth, and consequently, the education is related to growth (Metcalfe, 2008). Knowledge and ideas are communicated with “unimaginable” speed and “people” [sic] within this process and “their power of learning is at the heart of the changing world” (Browne, 1998, p. 5). By contrary, Metcalfe (2008, p. 71) stated that the “knowledge does not appear in the public domain, but is always tacit”.

This perspective was strengthened by Spender (2007) who

considered the “tacit knowledge” as noticeable within professions and businesses. Nonaka and Takeuki (1995) differentiated knowledge from information. These authors viewed knowledge as being judgement, action and meaning, whilst they saw information equal to ‘significance and interpretation’. Abell and Oxbrow (2001, p. 59) argued the necessity of a change in culture from “information is power” to “knowledge sharing builds power”. As a result, many authors emphasised the essential role of formal or informal communities of practice, networks and groups with the same aim, to share informal knowledge and speed the learning and business globalisation processes (Davenport, 1999; 69

Abel and Oxbrow, 2001; Borzillo et al., 2012). The idea of communities of practice (CoPs) was embedded at the beginning, within education, organisations and research (Akkerman, Petter and de Laat, 2008). Recently, CoPs received much consideration by groups of women entrepreneurs (Tomos et al., 2016). The concept of Communities of Practice (CoPs) was defined as the number of people who join in groups, in order to create and share knowledge, to have a sense of identity, to learn from each other, interact and create general accepted rules for that community (Wenger, 1998; Lave and Wenger, 1991; Akkerman, Petter and de Laat, 2008). According to Wenger, McDermott and Snyder (1952) CoPs is an old phenomenon, which can be small or large, visible or invisible.

Moreover, individuals belong to various CoPs at work,

school or home (Wenger, McDermott and Snyder, 1952). Furthermore, it was suggested that CoPs are an inspirational style of learning by participating, practicing and sharing within communities (Lave and Wenger, 1991).

According to Wenger (1998), a

community of practice (CoP) is defined by three main components: (a) a field of knowledge or activity; (b) a group of people sharing common interests; (c) the profession or capability of people from within the community of practice, indicated by common knowledge, perspective, interpretation and guidance that help that community to work and develop. Despite that community is characterised by a common culture, distinction should be made between community and culture, as the culture places accent on values, whilst the community focuses on â&#x20AC;&#x2DC;aspects of communicationâ&#x20AC;&#x2122; (Stullerova, 2014). There are various types of CoPs. An example of CoPs is (1) the external communities of practice, which are communities of customers or clients and employees, having common interest and attempting to share tacit knowledge and learning to improve products and services (Dewhurst and Cegarra Navarro, 2004). A second type of CoPs are (2) the global communities of practice, which are depicted as groups of individuals belonging to different areas of knowledge and different parts of the globe, who exchange, discuss or share ideas, best practices, originate rules of conduct and who by periodical meetings create professional and personal associations (Gillard et al., 2007; Meyer and Xia, 2012). Network was defined by Molony (2006) as local, national and international interactions between individuals. Barr (2000) defined social capital as a combination of both trust and networks (Molony, 2006, p. 70). Furthermore, Bourdieu (1993) equalled social

capital with “who you know” (Molony, 2006, p. 70). Whilst, Hardwick et al. (2012) recognised networking as the principal means to enhance knowledge. According to Snowden (1998), knowledge management has two dimensions. The first aspect of knowledge management requires looking at knowledge as an asset that can be shared within the community. Consequently, the main asset of CoPs is the knowledge. The second aspect of knowledge management is to provide a means helping the transmission of knowledge, in other words sharing the knowledge effectively, for example by creating intranets and networks (Snowden, 1998). It is suggested that, knowledge management features are equalled to CoPs. Additionally, based on Wilmott’s work (1998) it could be said that although knowledge is “key asset”, by using information communication technologies (ICTs) and lately virtual communities (Archer-Brown et al., 2013), small businesses can change the way knowledge is created, shared and evaluated: Digital Platforms & ICTs + Knowledge + Business Networks = Virtual CoPs (Inspired from: Wilmott, 1998; Archer-Brown et al., 2013) Marlow and McAdam (2010) and Tomos et al. (2016) argued about the importance of CoPs and networks for women entrepreneurs, and the advantages from sharing the information. 2.3.2 How women learn and how digital platforms support learning A study conducted by Rui, Cuervo-Cazurra and Un (2016) emphasises the role of learning –by-doing in updating knowledge. Conform to the research there are four learning phases: (1) integration; (2) trial and error; (3) repetition; (4) extension (Rui, Cuervo-Cazurra and Un, 2016). Consistent with these findings, Loibl and Leuders (2019) confirm that learning from error and failure is a cognitive process, which is essential for learning. Martin’s (2001) research on SMEs owned by women entrepreneurs, and organisational learning, argue about the impact of gender on organisational learning. Furthermore, organisational learning can be regarded as equal to learning with CoPs & networking. Results indicate that, the reason of internal communication for women, is learning within an organisation. According with this study, learning within an organisation is also impacted, by women management styles (Martin, 2001). Hence, there are two factors, which affect women’s organisational learning: (1) internal communication and (2) managerial process.

Moreover, networking activities and external links help achieve 71

organisational success and innovation, through knowledge creation and development (Martin, 2001). According to Martin, Lord and Warren – Smith (2018) women learn by interaction. Furthermore, organisational learning is community based, a social process, in which women acquire knowledge by means of contacts and social networks, and shared information (Wenger, 2000; Senge, 2014; Martin, Lord and Warren-Smith, 2018). Sharafizad (2018) states that women business owners learn informally, by means of networking, and employ only basic formal training to start-up their businesses. Sharafizad (2018) discovered the following emergent themes, which are consistent with other studies: women prefer informal learning, having their own approach to learning, and networks, which could be face-to-face or virtual, by means of digital platforms, mediating informal learning. The majority of women entrepreneurs have supportive heterogeneous networks, which have a positive impact upon enterprise success (Bogren et al., 2013). In the last two decades, the number of women using digital platforms and ICTs increased (Etkowitz et al., 2010). In this sense, LinkedIn and Facebook are considered major digital platforms, which mediate networking and virtual learning (Indrupati and Henari, 2012).

Consistent with the argument (Bandura, 1986) that

participation in networks improves knowledge, Gertner (2013) confirms that online participation enhances learning. Recent studies (Eisner and O’Grady, 2009) discovered that in the age of information technology the barrier of “a glass ceiling” as defined by the Wall Street Journal (1986), is still present for young women belonging to “Y Generation. Considering the age of the ICTs users in the millennium, there are two generations: Generation X (Gen X) and Generation Y (Gen Y) (Lissitsa and Kol, 2016). According to Lissitsa and Kol (2016), Gen X refers to individuals (male and female) born from 1961 to 1979. Further, Gen Y, called also ‘Millennials’, applies to users of ICTs born from 1980 to 1999. Internet access and connectivity is higher for Gen Y than for Gen X.

They also have a higher

participation in online communities (Guran, 2012; Lissitsa and Kol, 2016). It seems that digital platform & ICTs prevent barriers, and support communication and learning through participation and sharing. The section indicated the role and importance of knowledge, its perishable aspect (Drucker, 1967), and the imperative of lifelong aspect of learning (Browne, 1998), as well as the essentiality of CoPs & networking (Borzillo, et al., 2012).

How women

entrepreneurs learn and how digital platforms & ICTs support learning is discussed in 72

this section. In the conclusion of this section, knowledge sharing within CoPs and networking, means power and success (Oxbrow, 2001; Tomos et al., 2016). The author emphasised a lack of women’s perspective on the CoPs and knowledge acquisition (Higgins and Aspinall, 2011) and a lack of research on knowledge sharing within SMEs and its impact on business success (Metaxiotis, 2009). The next section to be discussed is named Digital Platforms and ICTs. 2.4 DIGITAL PLATFORMS & ICTs 2.4.1 Introduction This section discusses the role of Digital Platforms & ICTs for SMEs, women entrepreneurs and their learning. The section introduces information regarding the internet, mobile technologies, virtualization, computerised enterprise, gender, learning, and global communication technologies, web-based technologies for communication, data sharing technologies and networking technologies. The author of the thesis argues that ICTs has facilitated the increase in the number of businesses with women entrepreneurs working from home. There is an emphasis on the impact of networking and distance learning by means of technologies, upon women entrepreneurs. The section describes the new era, called ‘web 2.0 era’ as a revolutionary era, which allows women to learn and start-up businesses.

Furthermore, this allows the development of

communities of practice. The latest technological innovation, which can make easier entrepreneurial learning, mobile access to learning or mobile storage of information, is the growth of cloud computing – a virtual digital platform.

In spite of some

disadvantages, the new computing technology opens the doors to mobile learning and possible economic rejuvenation. 2.4.2 ICTs, Digital Platforms and M-learning for women entrepreneurs Brush (2000) highlighted that since 1990s, women business owners increased in the USA. The powerful jump was apparently caused, as Brush (2000) stated, by the development of information technology, which made easier for women to start their own businesses from home. This opportunity was also sustained by the availability of education and training for women to improve their business planning skills. Most of the courses, even for undergraduate and MBA were distance learning courses, with the help of information

technology. Moreover, the appearance of resources from specialised networks such as Women’s Network facilitated the start of a business from home by many women. Therefore, in order to survive and develop, both educational sector and businesses need to embrace change. There are two main global issues affecting the world, and these are the ICTs and globalisation, which cause both disputes and opportunities such as: exchange of information across the globe, partnerships and networks, mobile and virtual offices (Abell and Oxbrow, 2001; Dicken, 2011). Moore (2004) highlighted the role of web-based technology and the impact that these have on the real time communication and transmission of information within the entrepreneurial process and finally for business growth and development. Molony (2006) explained the ICTs by means of internet and mobile phones and described them as principal drivers for world development. According to the International Telecommunication Union there are 3.3 billion mobile phones users [sic] across the globe (Ilahiane and Sherry, 2012). It was also argued that ICTs are tools for social change and economic advancement through globalisation (Etzkowitz et al., 2010; Ilahiane and Sherry, 2012). Recently, Meyer and Xia (2012) emphasised the innovatory role of global communication technologies such as: video conferencing, web-based technologies for communication (e.g. Skype), data-sharing technologies (e.g. Drop box, Google Docs) and networking technologies such as: Linkedin, Facebook and Twitter. Additionally, the outcome of the research (Jones, Borgman and Ulusoy, 2015) indicated that social media has a positive impact on business success, and the increase in business’ online presence was decisive for the increase in sales (Jones, Borgman and Ulusoy, 2015). Digital platforms are paths for interacting, learning, collaborating, communicating and sharing with family, friends, customers, suppliers and other entrepreneurs (McCann and Barlow, 2015).

In this context, and for the purpose of the research, the author of the

thesis defines Facebook, Twitter, YouTube, Instagram, Pinterest, Linkedin, Google and Cloud Platforms, as digital platforms. Although, Facebook, Twitter and Youtube, were considered by Smith (2009) as key “vehicles” for information and communication transfer, the author emphasised that the tomorrow “vehicle” for information and communication is the smart phone e.g. iPhone, Blackberry (Smith, 2009). These were defined by Smith (2009) as mobile devices, cost effective, with increased popularity and the potential to reach customers across the world. 74

The Institute of Management Services (2012) noticed the growth of cloud computing and the positive effect of the increase in use of mobile devices such as: laptops, tablets, computers and smart phones, together with an increasing range of applications and software. Wang et al. (2010) defined cloud computing as “a set of network enabled services providing scalable, guaranteed, normally personalized, inexpensive computing platforms on demand in a simple and pervasive way” (Alshamaila, Papagiannidis and Li, 2013, p. 251). Cloud computing is a more than a digital platform, is“on-demand network access to...computing resources” such as: networks, servers, storage, applications and services (Mell and Grace, 2011, p. 2; Doherty, Carcary and Conway, 2015). Alshamaila, Papagiannidis and Li (2013) suggested that the beginning of cloud computing was the virtualisation. Recently, Pocatilu, Boja and Ciurea (2013) emphasised a new service provided by cloud computing, such as cloud data storage, which is now available on any mobile platform. According to Pocatilu, Boja and Ciurea (2013) mobile devices act as clients who subscribe for cloud storage, to cloud storage providers (CSP) such as: Dropbox, Skydrive, Google Drive Box, etc. However, Pocatilu, Boja and Ciurea (2013) highlighted both advantages of cloud storage (solution for disaster recovery, virtualised storage, flexibility, synchronisation and cost saving) and disadvantages (security threats, privacy, little control over, how data is stored). Recently, Butoi, Tomai and Mocean (2013) discovered that further research recommended a new direction for cloud technologies, such as inventing mobile learning tools, which are placed on the cloud. Even though cloud computing is a new phenomenon there is evidence of its adoption by SMEs and benefits. Thus, besides benefits, following cloud computing implementations within small businesses, there are also barriers encountered by the entrepreneurs, such as: security concerns, lack of trust in provider, data protection, compliance, lack of standards, internet connectivity and delay in data transfer (Doherty, Carcary and Conway, 2015). This study searches for evidence of embedding ICTs and digital platforms including cloud computing within small businesses owned by women entrepreneurs. Furthermore, Butoi, Tomai and Mocean (2013) investigated an innovative interdisciplinary approach with view to develop a cloud-based m-learning tool and to provide a fourth layer of cloud computing architecture, called Learning as a service model (LaaS). With the mobile learning (m-learning) the learning takes place anytime, anywhere and for everyone, including women entrepreneurs (Pal, 2011). The findings of 75

this research suggested that the evolvement of this learning tool requires special methods, based on the pedagogical principles and technical concerns (Butoi, Tomai and Mocean, 2013). Recently, Hurbean and Fotache (2013) described the new learning platform, named cloud-based application, marked by mobility. The new environment, depicted by Hurbean and Fotache (2013) as an increase in the number of users with smart phones, requires services to be delivered to student [sic] and enterprises in a mobile cloud computing model. Hurbean and Fotache (2013) also highlighted the increase in social networking through digital platforms as the principal method of interaction, collaboration and sharing. However, there are differences between the way women entrepreneurs as adult students, learn with computers and mobile technologies. Writing in 1993, Kruger discovered the sharing and collaborating learning method and argued that young students think and solve problems more effectively in pairs than alone (Underwood and Underwood, 1999, p. 10). Moreover, Johns and Gratton (2013) acknowledged the development of virtual world with three phases, called waves. According to their opinion the world is witnessing the third wave of developing “virtual co-workers”. They emphasised the need to build upon and employ the existent opportunities: virtual freelancers, virtual businesses and virtual coworkers. The focus it appears to be on mobile platforms and interactive technologies which apparently, facilitate collaboration and sharing fast pace information (Johns and Gratton, 2013; Lilleker, 2013). Consequently, it could be concluded that adults, such as groups and networks of women entrepreneurs, can collaborate effectively and learn from each other to increase performance of their businesses by means of mobile technologies. Research conducted by Barrantes Cáceres, Agüero and Cavero (2012) explored the impact of mobile telephone technologies on micro and small enterprises and discovered a real benefit. A similar study conducted by Pavaloaia (2013) on mobile software applications, demonstrated also an increased benefit for both enterprises and education system. Recently, Alshamaila, Papagiannidis and Li (2013) explored the adoption of cloud computing by SMEs in the north east of England and assumed that the virtualisation trend was the reason for embracing such novel processes. This section highlighted the innovative role of Digital Platforms & ICTs for global development, learning and businesses (Etzkowitz et al., 2010; Ilahianne and Sherry, 2012; Meyer and Xia, 2012), and their benefits for businesses and learning (Butoi, Tomai and Mocean, 2013; Doherty, Carcary and Conway, 2015; Pavaloaia, 2013). In addition, 76

the section emphasised the support role of Digital Platforms & ICTs for CoPs & networking (Hurbean and Fotache, 2015) and for virtual co-workers (Johns and Gratton, 2013; Lilleker, 2013). In summary, this section discovered a lack of research into the role of ICTs in networking for entrepreneurial process (Moore, 2004) and economic development (Etkowitz et al., 2010).

There is little research and that is studied in

isolation, focused on single issue, and not viewed in relationship with other factors (Andersson and Tell, 2009). There is no research into the effect of digital platforms and ICTs (Meyer and Xia, 2012; Ilahiane and Sherry, 2012) and their impact on business success (Smith, 2009; Jones and Borgman, 2015). 2.5 Summary of the Literature Review In the Literature Review chapter, the author of the thesis conducted a comprehensive review of relevant studies on the following: SMEs, entrepreneurs, women’s entrepreneurship phenomenon, business growth and WES, Learning, Digital Platforms & ICTs and CoPs & networking. In the literature review process, the author of the thesis conducted two reviewing procedures. The first procedure was based on the systematic manual review of hard copy issues of major journals and relevant books, essential for the success of this thesis. The second set of research was conducted into the electronic databases such as: Ebscohost, Business Source Premier, Emerald, etc., by using computerised key words such as: women entrepreneurs, small businesses, knowledge, learning, models of learning, networks, communities of practices, entrepreneurship education, new emerging technologies/digital platforms and information communication technologies, business growth and success. The entire thesis contains four hundred articles from about 80 significant highly rated and relevant journals, and more than two hundred books. Following the comprehensive literature review and the gaps in knowledge revealed by this process, the author of this thesis addresses the gaps highlighted by the literature review, by undertaking the following steps: •

The thesis contributes a new perspective on women entrepreneurs’ success, yielded by a woman researcher (Carter, 2000; Madsen, Neergaard and Ulhøi, 2003; Mattis, 2004; Lawton, 2010);

•

The thesis considers the lifelong learning and adult learning theories (Knör, 2011);

•

The thesis studies the impact, and the relationship between factors affecting WES, and employs MMR to assure methodological rigor (Hirsick and Drnovsek, 2002; Reijonen and Kompulla, 2007; Andersson and Tell, 2009; Knör, 2011);

•

The thesis highlights the importance of CoPs & networking for women entrepreneurs (Metaxiotis, 2009; Higgins and Aspinall, 2011);

•

The thesis informs the Government, HEIs and policy makers with regard to women entrepreneurs’ learning needs and advices on methods and styles of learning (Roomi, Harrison and Beaumont-Kerridge, 2009; Edwards and Muir, 2005; Petridou, Sarri and Kyrgidou, 2009);

•

The thesis provides a theoretical business model for WES (Brush, deBruin and Welter, 2009);

•

Contributes to the initiation of a learning program for women entrepreneurs to achieve success (Dafna, 2008);

•

The thesis considers women entrepreneurs’ perspective on entrepreneurial success, as part of the entrepreneurship process;

•

The thesis undertakes a holistic view of women’s entrepreneurship phenomenon.

Chapter two included five sub-sections and provided a comprehensive literature on small businesses, definitions and the economic context in the UK, Wales and particularly in the South-East Wales.

The first section introduced information regarding women

entrepreneurs, labour segregation, business growth and the meaning of women entrepreneurs’ success. Section two of the chapter presented information regarding women’s opportunity, learning process, methods and styles of learning, models of learning and entrepreneurial learning.

Section three of the chapter introduced the

concepts communities of practice and networks, its role in learning, and sharing knowledge and information. The fourth section of chapter two defined Digital Platforms & ICTs and presented their benefits for learning and businesses. The chapter concluded with a summary, the gaps and the steps taken by the author in view to address these gaps. The next is chapter three on the theoretical and conceptual research frameworks.

CHAPTER THREE: RESEARCH FRAMEWORKS This chapter (Figure 3.1) contains two sections and discusses about the theoretical and conceptual research frameworks. This chapter introduces the research path and the main theories and philosophies.

Figure 3.1: Chapter Three CHAPTER THREE RESEARCH FRAMEWORKS

THEORETICAL FRAMEWORK & CONCEPTUAL RESEARCH FRAMEWORK

-ENTREPRENEURSHIP THEORY -THEORIES OF LEARNING -SOCIAL CAPITAL THEORY -THEORETICAL RESEARCH FRAMEWORK -CONCEPTUAL RESEARCH FRAMEWORK -RESEARCH HYPOTHESES -RESEARCH PATHS

3.1 Introduction to Chapter 3 This chapter has two phases and integrates a substantial amount of literature review on the following research topics: WES, entrepreneurship and business growth, Learning, Digital Platforms & ICTs and CoPs & networking. The outcome of this blending process, leads the author to design a novel, thorough and multifacets conceptual research framework. The first phase of this chapter presents the entrepreneurship theory, theories of learning, social capital theory, and generates the theoretical research framework of the thesis. The theoretical research framework provides the theoretical basis for the rest of the thesis. There is a review of entrepreneurship theoretical development, which guides the author of the thesis towards identifying gaps in the knowledge, and producing clear hypotheses. Moreover, the substantial review discovers emergent research themes, and the main direction for further research into entrepreneurship. The second phase of the chapter generates a multifacets conceptual research framework.

The aim of the

conceptual research framework is to allow the researcher to define the main components of the research, to portray the relationship between the components, to design the hypotheses, and to explain the meaning of the results, which enhances understanding (Sotiropoulos, 2014). The rationale of this chapter is to connect together the literature and the aims of the thesis. In the figure below (Figure 3.2), the author presents a diagram with the detailed structure of this chapter:

Figure 3.2: The Structure of Chapter 3

Ideas/Concepts/various Hypotheses

Introduction to

Effectiveness Phase One

Theory of entrepreneurship/ learning theory/social capital

Applicability to women entrepreneurs & SMEs

The Design of the Theoretical Research Framework

Developing the Conceptual Research Framework PURPOSE Explains the relationships Concepts/Constructs Phase Two

Generates Hypotheses

Source: ÂŠ F. Tomos, 2016 (inspired from Sotiropoulos, 2014)

3.2 THEORETICAL RESEARCH FRAMEWORK 3.2.1 ENTREPRENEURSHIP THEORY According to Parker (2009), early theories about entrepreneurship can be grouped into four categories. The first group of theories presents the entrepreneurship as decision, which bears risk and uncertainty. Richard Cantillon (1755) belongs to this group of theoreticians. He describes the entrepreneur as “a speculator” who takes a risk to buy at a certain price and sells at uncertain price. His theory is a ‘risk theory’, where the entrepreneur has a central role within the economy. The economist Richard Cantillon defines the term entrepreneur as “go-between” or “between taker” (Coulter, 2000; Parker, 2009).

Moreover, Blaug (1997) highlights that Richard Cantillon, recognises the

disparities between demand and supply in the market, which creates not only opportunities but also disequilibrium and labels the entrepreneur as the person who brings back the economic equilibrium. Further researches belonging to the same group of theories were developed by Kirzner (1973, 1985), Gifford (1998) and Knight (1921). Kirzner (Ricketts, 2008) belongs to the modern Austrian school of thought, which encompasses also, other writers such as Shackle (1972, 1982) and Hayek (1945, 1978). Thus, Kirzner (1973, 1985) and Gifford (1998) stress the role of the entrepreneur as an individual with alertness to profitable opportunities and managerial capability.

While, Knight (1921) estimates that, an

entrepreneur has limited resources available to work with, and incomplete information about the consumer demand, which can change, determining thus, the fluctuation of the output prices, and the profit.

In other words, as Ricketts (2008) stresses, Knight

emphasised the role of uncertainty for profit achievement, rather than risk relation to profit creation. Similarly, and based on previous theories of profit, Blaug (1997) explains the profit as a return to a new factor of production process, named “entrepreneurship”, which incorporates risk taking. Based on the writings of the economist Adam Smith, Blaug (1997) describes the net profit as the management wage after deduction of opportunity costs. Further, Parker (2009) describes a second group of theories, according to which, entrepreneurship is defined as the process of co-ordination of all the factors involved in the production. The most representative theoretician of this group is Jean-Baptiste Say (1828). He believes that the entrepreneur, by co-ordinating the factors of the production, 82

is placed at the centre of the economic system, and is characterised as an experienced and perseverant individual. Coulter (2000) explains that the nineteenth century economist, Jean Baptiste Say, emphasised the distinction between the interest earned by the owners of the funds, and the income earned by those who use their managerial abilities within the production process. By contrary to the above theories, based on the theory of the British Economist Adam Smith, Blaug (1997) claims that the entrepreneur is a factor of the production process, however, separated from the other factors of production such as land and capital. The third group of theories depicts entrepreneurship as an innovative and creative process (Parker, 2009). Joseph Schumpeter (1934, 1939) argued that entrepreneurship requires innovation. The theoretical roots of this thesis (Figure 3.3) are embedded into the theory of entrepreneurship and the school of thought represented by Joseph Schumpeter (1934; 1939). This school of thoughts describes the entrepreneurs as innovative, creative people who introduce new products or methods of organisation (Parker, 2009). This is the first focal theory of this thesis (Phillips and Pugh, 2000). The entrepreneur, according to his opinion, is the person who introduces new technologies (Parker, 2009).

The entrepreneur, in Schumpeter’s opinion, is an innovator who

“creatively destructs” and entrepreneurship is the process of replacing old processes, products and ideas with the newest ones. Schumpeter describes ‘innovation’ as follows: “...the introduction of new technical methods, new products, new sources of supply and new forms of business organisations” (Blaug, 1997, p. 446) According to Schumpeter, ‘the innovator’ is the “entrepreneur” and “the source of dynamic change in an economy” (Blaug, 1997, p. 446).

Schumpeter defines the

entrepreneur as “the pivot on which everything turns” (Ricketts, 1987, p. 44). Moreover, the entrepreneur is the person who discovers opportunities, initiates and operates the venture (Coulter, 2000). This group of theories is supported by the latest research in the field, and is applicable to women’s entrepreneurship and small businesses, and consequently, to this thesis. Women entrepreneurs are creative, and adhere to novelty and innovation, specifically to Digital Platforms & ICTs. A second perspective upon the entrepreneur as ‘the innovator’, regards the new knowledge as innovation, leading to firm growth and entrepreneurial success. Drucker (2015) links innovation with technology and argues about the knowledge-based innovation and its 83

usage in technology. He defines the technology as the new knowledge embedded in new products, new services and new production processes. In other words, the blending process of technology and new knowledge results in innovative products, services and processes which finally leads to business growth and entrepreneurial success. The innovation consists of learning (education) and acquiring new knowledge (education), which is embedded into technology. Consequently, education and technology lead to innovation, business development and growth. Drucker (2015, p.136) speaks about “the convergence ...of several different kinds of knowledge” which means multiple knowledge from all domains, which in the last decades contributed to innovation, which finally leads to business growth. Additionally, Drucker (2015) emphasises the need of entrepreneurial management, which again leads to education. Similarly, the author of this thesis bases this study on the presumption that women entrepreneurs learn entrepreneurial management and new knowledge, as well as, the usage of technology, in order to achieve entrepreneurial success. The fourth group classified by Parker (2009) are theories grouped under the title: ‘leadership and motivation’. Leibenstein explains that, the entrepreneurship process brings product changes due to the leadership capability of the entrepreneur who is highly motivated and able to take risk, and to solve crises successfully (Parker, 2009). Finally, the last group of theories belongs to theoreticians such as Barretto (1989) and van Praag (1999) who associated entrepreneurship to personal, innate traits or characteristics belonging to the entrepreneur. Many authors (Lucas; Leibenstein; Casson) found that the origin of entrepreneurship is the individual human capital (Parker, 2009). However, these models suffered over time, severe criticism. Swedberg (2000) emphasises that, indeed, the founder and the main personality in the literature of entrepreneurship is the economic theorist Joseph Schumpeter who has a holistic approach to the theory of entrepreneurship. Despite the limits of his theory of entrepreneurship, Schumpeter formulates three typologies of entrepreneurial behaviour. Moreover, economist Adam Smith considers that, the capitalist has an identical signification with the entrepreneur. Similarly, Blaug (1997) stresses that the economist Adam Smith in the “Wealth of Nations” does not differentiate between the capitalist, as the provider of the capital, and the entrepreneur, as the decision maker. Nonetheless, there were French classical writers who distinguished between the interest on capital, and 84

the profit, which is the income received by the entrepreneur (Ricketts, 1987). Frank Knight in his book “Risk, Uncertainty and Profit” describes the entrepreneurial profit as a gain, coming from “handling uncertainty”. More theories about entrepreneurship were developed by social sciences. Max Weber highlights the role of change and identifies entrepreneurship with charisma, which functions as an important motor for change. He thinks that people with charisma, persuade people to follow them. Finally, Rosabeth Kanter, developes theories on intrapreneurship and gender (Swedberg, 2000). As a result of the historical perspective on the economic thoughts, regarding the beginning and the development of the theories about entrepreneurs and entrepreneurship, and their significance along the history, Deane (1991) suggests the following four benefits: pedagogical benefits, new ideas regarding why and what will succeed, insights in patterns of thought, and a comprehension of the development of scientific ideas. Beside all these theories, feminist critique to sociological theories focuses on the effect of political factors, state policies and culture, spatial location and professionalization of entrepreneurship (Hurley, 1999). Herbert and Link (1988) who defines the entrepreneur as a risk taker carry on, further studies on entrepreneurship. This thesis considers Penrose’s (1980; 2009) and Drucker’s (1985; 2015) views on entrepreneurship and growth/success. Penrose (2009, p. 8) defines the firm as “the basic unit for the organisation of production” and the growth as “the opportunity for expansion” (ibid., p. 127). Furthermore, the firm “is both administrative organisation and a collection of productive resources” (Penrose, 2009, p. 28). Kregel (1972, p. 39) in its book ‘The theory of economic growth’, explains ‘growth’ from the entrepreneur’s perspective as ‘a net increase in capital’, followed by an ‘increase in sales’. According to Penrose (1980), growth of the firm is perceived as a process with successive and developmental phases. Consequently, the various stages of the growth must show the growth.

In my view, growth is both a tangible and an intangible indicator (Penrose,

2009). It follows that, the phases of the growth need to explain, and to interpret the growing process, and the outcome, which in most of the cases, are tangible (profit; money). Another perspective, discussed by Penrose (1980) regards the growth of the firm by expansion. In this sense, the opportunity for firm’s development, depends very much of the resources belonging to the enterprise, ‘own resources’ and ‘acquired resources’ 85

(Penrose, 2009, p. 28). At their turn, the internal resources of the firm determine the type of opportunities that can be considered, their practicality and feasibility. In my view, the resources of the firm considered together as a whole, both tangible and intangible, project the firm’s holistic capability to undertake successfully the opportunity of growing. This is the second focal theory (Phillips and Pugh, 2000). Here comes the input of EED and Digital Platforms & ICTs, as ‘own resources’ that enhance and affect the process of growth. It infers also that, success is a larger concept, incorporating the concept of growth. In other words, the success of engaging in such an opportunistic act to try expanding the firm depends very much on all the resources of the firm, including educational and technological capabilities of the firm. I see the entrepreneur as part of the enterprise, contributing and taking part actively, creatively and perseveringly within the growing process. Further, Penrose (1980) argues that, there are small firms for which growing is appropriate and possible. However, there are firms for which growth is irrelevant. The firms from the second category have to stay small or, as Penrose (1980) stated, grow very little and try to coexist with the large companies in the business world. In my view, it is possible to portray the growth for the small businesses as an intangible growth, reaching success by lasting across a long period of time, and having the expertise in certain fields, and sectors of activity. Furthermore, the increasing quality of providing products and services, as well as expertise of the entrepreneur, can be classed as intangible growth for SMEs. Drucker (2015) views the entrepreneur, as the ‘innovator’ and considers the embedment of innovation within both, the production process, and the thinking of the entrepreneur. There are new approaches to opportunities, new perceptions of entrepreneurship, and new, revolutionary knowledge, ready to have an impact upon the growth and success of the businesses. In Drucker’s (2015) opinion, there are innovations leading to growth, but also innovations, which bring more risks than success (Drucker, 2015, p. 159). The author of the thesis considers two perspectives only, and discusses the following: (1) the change in perception, as innovation, and its opportunity to affect upon growth and success, and (2) the new knowledge, which can bring success, and business growth. Drucker (2015, p. 127) defines success as “a change in perception and meaning” and compares with failure as being the opposite term of success. Further, he explains that, in reality, the truth about something did not change; only the interpretation given by 86

individuals and firms, to that ‘truth’ has changed (Drucker, 2015). In other words, the individuals place significant importance upon things or events, which in the last decades were not significant. It infers that, it is a change in the order of priorities and standards which affects the increase in value, and hence the change in the meaning of the phenomenon. Thus, ‘success’ is a complex term, attracting different interpretations, which develops at a velocity equalled to the changes in the culture and society. In the famous book ‘Maslow on Management’, Maslow discusses the role of the entrepreneur in society, and suggests that, the reward of the entrepreneurship is not only money, as a tangible reward, but it is more than ‘money’ (Maslow, 1998). “If only for theoretical purposes, it is well to recognize that the entrepreneur, the organizer, the spark plug, the active leader upon whom everything depends, can be rewarded in other ways than money.” (Maslow, 1998, p. 232) Similarly, Drucker (1998, p. 67) discussing management, argues, “the business enterprise, is not a phenomenon of the nature, but one of society”. It seems that, by being embedded within society, it is obvious that, the enterprise should be assessed in its relation to the society (Drucker, 1998). 3.2.2 LEARNING THEORIES The author of the thesis, in Figure 3.3, presents theories of learning. What is the meaning of learning? Webster Collegiate Dictionary defines ‘To learn’: “To gain knowledge or understanding of, or skills in, by study, instruction or experience” (McFarland, 1969, p.1). Borger and Seaborne (1966) argued about the learning capacity, and the transformation, that learning brings to the learner. Regarding learning, Jarvis (2004) focused on four categories of knowledge: data, information, knowledge and wisdom, which change continuously. The author defined knowledge as the “information that is learned and accepted” (Jarvis, 2004, p. 9). Referring to the adult learning, Jarvis (2004) emphasised the social character of the learning, and highlighted that, education helps people to adapt to the ever-changing society. Similarly, through education, women entrepreneurs can adapt quickly to the changes within the business environment and society. Dollard and Miller (1950) acknowledged that human behaviour itself is learned rather than innate. Particularly important, they highlighted that human behaviour could be 87

learned by a person, male or female within either a nation, or a social class. It infers that, women entrepreneurs learn within an entrepreneurial environment. Moreover, Dollard and Miller (1950) emphasised a few factors, which are very important for human learning, such as drive (motivation) and reinforcement (reward). Therefore, it is beyond question that, certain strong drives are principal factors of female entrepreneur’s success. In order to understand different types of learning, and provide an insight into the learning women entrepreneurs employ, this research discusses the main schools of learning and the development of learning theory, as described by Petty (2009): cognitivist, behaviourist and humanistic schools of thoughts and its perspectives: sociological (Kolb, 1984), social (Bandura and Walter, 1963), interrelational (Sappleton, 2009) and contextual (Jarvis, 1998). The first school of thought, which contributed to the development of learning theory, is the cognitivist school. The theorists belonging to this school of psychology believe that learners have to construct their own interpretation and be able to explain new concepts based on previous learning and existing theories or concepts (Petty, 2009).

The

cognitivist theory was called “constructivism” and suggests that learning takes place by doing, asking and applying their learning within the real life. The most known theorist of this school of thoughts is Piaget, who discussed the process of cognitive development, and associated this with the process of child development (Jarvis, 2004). A second influential theorist is Vygotsky, who postulated that the developmental process does not happen at the same time with the learning process. He also discovered the ‘zone of proximal development’. Other perspectives on learning were developed by Bruner and Gagné who highlighted the role of the memory in the learning process (Jarvis, 2004). The second school of thought was initiated by the behaviourist psychologists and was called the behaviourist school. According to this school of thought, in order to have effective learning, teachers focus on praising and encouraging their students, thus, reinforcing learning. A positive feedback determines students to further their learning (Petty, 2009). The behaviourist theory has two forms: connectionism and conditioning. Connectionism is known as ‘trial and error’ form of learning and was represented by Edward L. Thorndike (1874-1949) (Bower and Hilgard, 1981; Petty, 2009). Bower and Hilgard (1981) in their analysis of Thorndike’s work, explained ‘trial and error’ as the choice of a response out of a range of feasible responses and the acceptance of the 88

outcome, or the consequences. Thorndike also postulated that ‘success’ or ‘failures’ are the outcomes of learning, and the consequences of choosing a suitable response to learning (Bower and Hilgard, 1981). The classical conditioning theory was represented by the Russian psychological researcher Ivan Petrovici Pavlov (1849-1936) (Borger and Seaborne, 1966; Bower and Hilgard, 1981). Pavlov originated the theory of ‘conditioned stimulus’ and ‘conditioned reflex’. His important contribution to the theory of learning consists of originating and introducing the terminology and concepts of learning, such as: reinforcement, extinction, generalization and differentiation. His major contribution resides in introducing the model of ‘associative learning’ in which Pavlov suggested that ‘conditioned reflex’ assumption is the origin of learning (Bower and Hilgard, 1981, p. 72). Another influential early behaviourist theorist, belonging to this school of thought was Guthrie (Bower and Hilgard, 1981) who left a few viable learning principles as follows: (1) learning increases by repetition; (2) motivation impacts upon learning; (3) learning can be embedded into new circumstances, as a result of the link between the old and new components; (4) learning becomes permanent when is enhanced with new learning. Another theorist was Clark, L. Hull (1884-1952) who was inspired by Pavlov’s research on ‘conditioned reflex’, and Thorndike’s ‘law of effect’, and originated the ‘Principles of behaviour’ (1943) in an empirical quantitative configuration, as a mathematical expression. He is considered one of the most important theorists due to his ‘systematic behaviour theory’ (Bower and Hilgard, 1981). The last theorist presented in this chapter is B. F. Skinner who tried to define behaviour based on a range of experiments in laboratory. His presumptions, on behaviourist methodology, are complex and his main contribution consists of developing the theory of ‘conditioned reinforcement’ or ‘conditioning learning theory’ and the factors affecting ‘the operant conditioning’, such as: emotions and drives (Bower and Hilgard, 1981; Jarvis, 2004). The third school of thought was called the humanistic school and was based on emotional factors that the individual needs for growth and development.

This thesis uses the

humanistic school of thought, with its three perspectives, to develop the study, and to interpret the results of the research. This is the third ‘focal theory’, of this thesis (Phillips and Pugh, 2000). This school of thought contains three perspectives: sociological, social/holistic and experiential (Petty, 2009; Jarvis, 2004). The theorists of this school of thought suggested that the purpose of the school is to meet the individual needs of any 89

learner (Petty, 2009). Petty (2009) mentioned also another type of learning that is not taught, called “social learning”, based on modelling and the role of teachers as “models”. This type of learning called “social learning”, was also highlighted by Higgins and Elliott (2011, p. 348) as crucial for entrepreneurial education and was defined as a “holistic [and] dynamic learning” based on trust, information and intuition. The entrepreneurship was “learned through experience, ‘trial’ and ‘error’ “, whilst the small firms were built through social interactions (Higgins and Elliott, 2011, p. 350). The social character of learning was discussed by two theorists belonging to this school of thought: Vygotsky and Bandura. Vygotsky believed that learning happened by imitation or adopting role models’ behaviour. Bandura postulated that learning takes place through observing other individuals (Jarvis, 2004). Conform to Bandura (1977) the learner is an active actor and interacts with the learning environment. Furthermore, there is a dynamic process, which involves a dual reaction between the learner and the environment. Thus, Bandura (1977) sees social learning as an interactive process. Additionally, arguing for observational or role model learning, (in line with the social theory), Bandura (1977) suggested that human behaviour is acquired through observation. In other words, women entrepreneurs have the capability to learn through observation, by means of attention, retention, reproduction and motivation (Bandura, 1977). The second type of humanistic school is the sociological school and its theorists are Kolb, and Maslow. The main theorist of experiential learning theory is Kolb who created the ‘learning cycle’. Conform to Kolb’s (1984) view, the learning process starts with the concrete experience and goes through observation and reflection on learning, which is followed by conceptualization and generalization, and ends by incorporating learning into new real life situations (Jarvis, 2004). Petty (2009) emphasised the importance of the “whole brain”, the holistic technique within the teaching process and the effectiveness of these for all kind of learners. “To know is to be able to do...” (Revans, 1988, p. 655). In Petty’s (2009) view, the learning concept was substituted by the “whole brain” learning theory, which suggested that learners employ consistently holistic and creative, social, visual and experiential learning techniques. In other words, individuals use within their learning, strong techniques such as: reviews, demonstrations, examples, models, diagrams, mind-maps, visual interesting websites, animations, importing images from internet, creating intranet websites, as well as, learning kinaesthetic strategies such as: managing information, making a model, using computers, phones, doing demonstration, 90

giving a demonstration or an explanation, etc. (Petty, 2009). The sociological school of thought also includes theories originated by Maslow. A major contribution to the field of education is Maslow’s hierarchy of need. According to Maslow, every human being needs to ensure firstly the basic, fundamental physiological and safety needs. These are followed by the need for love and right at the top of Maslow’s Pyramid, are ‘self-esteem’ and ‘self-actualization’ needs, which automatically require the need to learn and develop (Jarvis, 2004). Similarly, Jarvis (2004) highlights the need of individuals to learn. Assessing Maslow’s pyramid of need, Jarvis (2004) added another element to the pyramids of human need. This element is ‘learning’ and it was added before the last two elements of the pyramid (self-esteem and self-actualization). In the last decades, another trend began in education, and scholars originated the fourth school of thought named adult and lifelong learning school of thought. This is the last line of thought to be introduced within this chapter (Jarvis, 2004). Also, this school of thought is the fourth ‘focal theory’ for this thesis (Phillips and Pugh, 2000). The main theorists of this school are: Paolo Freire, Robert Gagné, Malcolm Knowles, Jack Mezirow and Carl Rogers (Jarvis, 2004). The most famous theorist is Malcolm Knowles, named as ‘the father of andragogy’ (Jarvis, 2004, p. 124). Knowles differentiated between adult learning and child learning. The author claimed that adult learners are independent (selfconcept), have experience (skills and knowledge) and are motivated (the readiness to learn, and the orientation to learning) (Jarvis, 2004; Jordan, Carlile and Stack, 2008). The second theorist is Jack Mezirow, who postulated that, learning changes when the learner reflects upon the learning experiences. Furthermore, the reality changes in order to reflect the learner’s experience (Jarvis, 2004). Consequently, adult learning is a complex process that requires reflection and involvement, creativity and application. The terminology of ‘adult education’ evolved to ‘recurrent education’ and to ‘lifelong learning’ (Jordan, Carlile and Stack, 2008). 3.2.3 SOCIAL CAPITAL THEORY Social capital theory refers to entrepreneurs’ capability (female/male) of obtaining benefits from personal, and social relationships, and from their membership to various associations and CoPs (Felício, Couto and Caiado, 2014). Furthermore, the social capital theory recognises the essential role of relationships and groups and communities for women entrepreneurs (Roomi, 2009; Tan, Zhang and Wang, 2015). Social capital encompasses ‘flow of information’ (Tan, Zhang and Wang, 2015), personal relations and 91

social ties, based on trust and values, providing support for the entrepreneur, and embedding crucial resources for business growth and success (Tsai and Ghoshal, 1998; Manolova et al., 2007; Roomi, 2009; Ottósson and Klyver, 2010). In other words, the social capital generates informal learning and knowledge, and assists businesses and entrepreneurs to grow, by means of networks (Roomi, 2009). Furthermore, the social capital is a ‘goodwill’ incorporated within the social relations (Alder and Kwon, 2002; Roomi, 2009). The concept of social capital focuses on the benefit of relationships, groups and communities and networks of relationships, for women entrepreneurs and business development, by eliminating constraints, barriers and discrimination in accessing resources (Brush et al., 2002; Roomi, 2009; Sappleton, 2009). Sappleton (2009) highlighted the contribution of social capital to women’s entrepreneurship. The concept of social capital was also defined as the level of trust and integration within a community, which leads to networking and sharing resources between the members of that community (Sappleton, 2009). Social capital provides a ‘multilevel lens’ (Marvel, Davis and Sproul, 2016). According to some authors, the social capital is determined by the number of relationships and the strength of the ties, their frequency and quality, and their reciprocal benefits (Granovetter, 1973; Lutter, 2015). Sappleton (2009) argued that the social capital is a non-tangible asset incorporating the following eight elements: social networks, social participation, social resources, social norms, legitimacy and influence, social support, trust in others, and social activity. Granovetter (1973) specifically emphasised the crucial role of networks. Moreover, social capital is a component of entrepreneurship capital (Audretsch and Keilbach, 2004). The main promoters of the social capital theory were Bourdieu, Coleman, Putnam and Durkheim (Roomi, 2009; Portes, 1998). It is argued that social capital theory is embedded in the sociological theory, with consequences for the entrepreneur and community (Portes, 1998). Further, the social capital, as a non-monetary form of capital, is a manifestation of ‘power influence’ (Portes, 1998). According to Bourdieu, the social capital has benefits for the individual, through participation in groups.

Whilst

Durkheim’s (1984) theory of integration, established the role of social structures, members and reciprocity, Coleman (1988a; 1990) and Putnam (1995) defined the social capital as a combination of social structures and reciprocity, based on trust, by means of networking in different contexts (Tsai and Ghoshal, 1998; Portes, 1998; Roomi, 2009).

As well as having positive benefits such as: social control, family support and networks, helps entrepreneurs to grow the business, provides learning opportunities and management skills; the social capital has also negative impacts like ‘strong ties’ that provide advantages for community members only (Portes, 1998; Dawson et al., 2011). Tonge (2008) identified 17 barriers to women’s networking. Between these, I enumerate the following: psychological barriers (negative perceptions of networking; low expectations), situational barriers (low position; discouraging consultancy culture; family commitments) and social barriers (age; gender; appearance; ethnicity) (Tonge, 2008). Despite the assumption of networking being beneficial for men and women entrepreneurs, the research provided evidence of gender differences in networking, barriers and constraints to resources, lack of access to appropriate formal networks, as well as different perspectives of women entrepreneurs on the growth process (Brush et al., 2006; Roomi, 2009).

It seems that the labour market affects the establishment of the initial

entrepreneurial networks for men and women. However, it is argued that, in the later business stages, women’s entrepreneur network tend to be similar to men’s entrepreneur networks (Klyver and Terjesen, 2007). In addition to these, Roomi (2009) discovered differences between women entrepreneurs’ perceptions of the meaning of social capital, which oscillates according to the sector of activity, industry, form and stage of the business. Dawson et al. (2011) noted different perceptions on networking. Thus, women entrepreneur have positive perceptions of networking phenomenon, which, in their opinions, helps with improving management skills. The structure of women’s entrepreneur social networks contains: family, friends, colleagues, mentors, educational organisations, business and professional advisers, charities, women-only groups, mixed-gender groups, suppliers, distributors and bankers (Roomi, 2009). According to Roomi’s (2009) findings, the concept of social capital is wider than the concept of networking, including also the process of creating and sustaining networks, as well as norms, values, status and complicity (Felício, Couto and Caiado, 2014). In addition, Roomi (2009) stated that, women-only networks proved to be effective, by providing encouragement and solutions, in the early stages of the business. Certainly, the social capital is a catalyst for development and business growth (Roomi, 2009). Originated in Granovetter’s (1992) research, Tsai and Ghoshal (1998) discussed about three dimensions of the social capital: (a) structural and (b) relational, and (c) cognitive 93

dimension. The structural dimension of the social capital regards the social interaction between the members of the network, whilst, the relational dimension refers to the main characteristic of the relationship, which is the trust (Granovetter, 1992; Tsai and Ghoshal, 1998). The cognitive dimension of the social capital refers to the shared code and value, and common practices of the network (Tsai and Ghoshal, 1998). Tsai and Ghoshal (1998) argued that the social capital leads to value creation by product innovation. Consequently, the social capital, through its three dimensions, determines business development and growth. Social capital theory confirmed the role of the networks and the impact of this upon entrepreneurial success (Tsai and Ghoshal, 1998). A research conducted by Sappleton (2009) on women entrepreneurs and social capital, confirms that social capital is a complex concept, which is difficult to operationalize and measure. The concept is defined by trust and social integration in order to allow collaboration between women entrepreneurs (Sappleton, 2009). Such definition of the concept permits the author (Sappleton, 2009) to measure social capital by means of the following aspects: frequency of interaction, levels of trust, membership of associations and degree of cooperation. This thesis, measures the social capital (CoPs & networking) by means of women entrepreneurs’ membership to various associations. There are a few perspectives regarding the theory of social capital. The first is the classical perspective and regards network structures as components of the social capital. According to such perspective, entrepreneurs with high level interaction are more probably to develop trust and cooperation (Coleman, 1988; Lutter, 2015). The second perspective on social capital argues that, individuals with weak ties adhere to heterogeneous communities and benefit more from the social capital – the strength of weak ties theory (Granovetter, 1973; Lutter, 2015; Sullivan and Ford, 2014). Women tend to have strong ties, with networks comprising family and friends they know well, whilst men benefit from weak ties and better opportunities to resources (Dawson et al., 2011). ‘Weak ties’ are characterised by “infrequent interactions, a short duration of relationship and a lack of a close socio-emotional bond”, whilst ‘strong ties’ have “frequent interactions, a long duration of relationship and a close socio-emotional bond” (Granovetter, 1973; Sullivan and Ford, 2014, p. 553). In this regard, by adhering to homogenous networks, women entrepreneurs suffer from gender inequality (‘closure penalty’) and encounter constraints to accessing formal male networks which have a better ‘status’(Lutter, 2015). 94

A third perspective is provided by Dawson et al. (2011) through the network theory. One area of this perspective refers to the social networking approach (Dawson et al., 2011). The social networking perspective, explore ‘how’ resources, knowledge and information are provided to the entrepreneur (male/female) by means of his/her existing relationships (Dawson et al., 2011). Besides this approach, Slotte-Kock and Coviello (2010) argued about additional schools of thought: business network perspective and entrepreneurial network perspective (Greve, 1995). Both social and business network perspectives focus on social process, aimed to helping entrepreneurial process, and regard network as (a) independent variable and (b) dependent variable (Slotte-Kock and Coviello, 2010). A fourth perspective discussed here is the social exchange theory, originated from the trust within the relationships and based on sharing and reciprocity (Blau, 1967; Dawson et al., 2011). Networking is highlighted here as leading to women entrepreneurs’ success (Carter and Cannon, 1992; Dowson et al., 2011). The last theoretical perspective is the holistic perspective of social capital theory (Portes, 1998; Félicio, Couto and Caiado, 2014). This theory emphasises the role of multiple networks (work, business, family, friendships and relationships, gender, professions) and the crucial role of communication of knowledge and information, as part of education, essential for achieving success. This theory highlights the essential role of entrepreneurs in benefiting from their membership to CoPs & networks (Teece, 2005; Dewey, 1921; 1933; Ulhøi, 2005). This thesis considers a holistic perspective of social capital theory, embedding network perspective, as the root of CoPs & networking, where women entrepreneurs participate within faceto-face CoPs & networks, or virtually through Digital Platforms & ICTs. This perspective builds on the presumption that entrepreneurship is affected by the social relationships and trust (Granovetter, 1973, 1985; Portes, 1998; Félicio, Couto and Caiado, 2014; Teece, 2005; Dewey, 1921; 1933; Ulhøi, 2005). In contrast to the social and business network perspectives (Slotte-Kock and Coviello, 2010), this thesis proposed a conceptual research model with ‘CoPs & networking’ as a controlling variable. 3.2.4 THEORETICAL RESEARCH FRAMEWORK Based on the focal, background and data theories, and the literature review, the author designed below the Theoretical Research Framework for this thesis (Figure 3.3). Also, the author of the thesis considers an integrated perspective upon the phenomenon of women’s entrepreneurship and learning, combining elements of these trends and 95

perspectives, in a creative and innovative manner (integrated). The theoretical research framework comprises three types of theories (Phillips and Pugh, 2000): (a) focal theories (entrepreneurship theories, learning theories), background theory (social capital theory) and (c) data theories (positivist, interpretivist and MMR theory). The following are the focal theories: (1) entrepreneurship theory with two perspectives, (a) innovation and change (Penrose, 1980; Drucker, 1985; 2015; Burns, 2011; Pall, 2011; Meyer and Xia, 2012; Parker, 2009) and (b) success theory (growth) (Penrose, 1980; Bosworth, 1989; Greene, 2000; Chell, 2001; Gimson and Mitchel, 2008; Parker, 2009); and (2) learning theory, with three perspectives, (a) social (Bandura and Walter, 1963; Bandura, 1977; Jarvis, 2004; Petty, 2009), (b) sociological and holistic (Kolb, 1984; Maslow, 1970; Petty, 2009), and (c) adult and lifelong learning (Jarvis, 2004; Parker, 2009). The background theory is social capital theory with its holistic perspective (Granovetter, 1973; Dewey, 1921; 1933; Portes, 1998; UlhĂ¸i, 2005; Teece, 2005; FĂŠlicio, Couto and Caiado, 2014). The data theories are the following: positivist, interpretivist and Mixed Methods Research. The designed Conceptual Research Framework follows along the study (Figure 3.4, p. 101).

Figure 3.3: Theoretical Research Framework Research Topic: The Impact of Learning and Digital Platforms & ICTs on Women Entrepreneurs’ Success, and the Context of CoPs & Networking THEORIES

Innovation & Change Theory (Penrose, 1980; Drucker, 1985; Parker, 2009; Drucker, 2015; Birley, 1982; Burns, 2011; Pall, 2011; Meyer and Xia, 2012)

Focal Entrepreneurship Theories

Background Social Capital Theory

Data Theories

Growth Theory & Success Theory (Penrose, 1980; 2009; Maslow, 1998; Greene, 2000; Chell, 2001; Gimson and Mitchell, 2008; Parker, 2009; Drucker, 2015)

Social Capital Theory (CoPs): Holistic Perspective of Social Capital (Granovetter, 1973; Dewey, 1921; 1933; Portes, 1998; Ulhøi, 2005; Félicio, Couto and Caiado, 2014)

Positivist/ Interpretivist/Mixed Methods Research (Saunders, Lewis and Thornhill, 2012; Trafford and Leshem, 2008; Collis and Hussey, 1999, 2003; McDonald et al., 2015; Bryman and Bell, 2015; Patton, 2002; Zikmund et al., 2010; Smith, Flowers and Larkin, 2009)

School of Thoughts: Humanist (a) Social Learning Theory (a1) (Petty, 2009; Jarvis, 2004; Bandura and Walter, 1963; Bandura, 1977; Higgins and Elliott, 2011)

Focal Learning Theories

School of Thoughts: Humanist (a) Sociological & Holistic Learning Theories (a2) (Kolb, 1984; Maslow, 1970; Petty, 2009)

Adult Learning Theory & Lifelong Learning (Freire, Gagné, Knowles, Mezirow, in: Jarvis, 1983; 2004; Petty, 2009)

3.3 CONCEPTUAL RESEARCH FRAMEWORK In view to enhance the evidence regarding gaps in the knowledge, and to generate the research hypotheses, as well as building the Conceptual Research Framework (Figure 3.4), this section continues with the analysis of a limited number of articles. Based on the analysis of twenty selected articles, the author presents a short perspective with significant information, which leads to producing the Conceptual Research Framework (Figure 3.4). The Conceptual Research Framework is the skeleton on which this thesis is elaborated. A thorough analysis, of the small sample articles, indicates various approaches and perspectives on success, which is a complex concept. Studies approaching the concept of success (Sandberg, 2004) highlight variations between perceptions of men and women entrepreneurs. Reijonen and Komppula (2007) draw attention to the intricacy of this phenomenon and highlight its mulptiple perspectives, which can be affected by women entrepreneurs’ goals. Reijonen and Kamppula (2007) present the situation of both financial and non-financial (time, flexibility and satisfaction) measures of business success. It is argued that, the financial measures for business success are the following: growth, sales, profit and efficiency. However, until present, there are no definitions on growth, hence is very difficult to compare results from different studies (Andersson and Tell, 2009). In some authors’ views, business survival is considered a success (Burns, 2011). In others’ opinions, growth should be measured financially and non-financially (Costin, 2012). Mattis (2004) emphasised that, women who worked previously in corporations and had work experience, started their own businesses based on the prior experience. In other words, women received business education through experience-based learning. In line with this argument, Metaxiotis (2009) linked knowledge (skills and experience) to business success. Furthermore, this argument is strengthened and confirmed by FarrWharton and Brunetto (2009) who emphasised the need of learning within the firm, and labelled this as the ‘entrepreneurial learning practice’. However, Roomi, Harrison and Beaumont-Kerridge (2009) enumerated the main factors affecting business growth: entrepreneurial learning and skills (marketing, sales, and business), digital platforms and ICTs, and effective networking (Metaxiotis, 2009). Further evidence in support of education and learning being crucial for business success is provided by Petridou, Sarri and Kyrgidou (2009). 98

Additionally, it is suggested a lack of Business Models to disentangle the complexity of the phenomenon, and help entrepreneurs to achieve business growth and success. Here is where this thesis comes, proposing a novel Theoretical Business Model for Women Entrepreneurs’ Success. This is accompanied by a creative ‘Andragogical Learning Model’ for women entrepreneurs. After 2000, research started to consider the entrepreneurship phenomenon as an interrelated phenomenon, with other elements. Thus, Keogh, Mulvie and Cooper (2006) discussed about the need of learning models and Matlay (2006) founded a link between ‘learning and entrepreneurship’. Additionally, Martin Cruz et al. (2009) linked learning to business success. Furthermore, Matlay and Carey (2007) discovered a lack of agreed definition on entrepreneurship, and no gender approach to entrepreneurship definition. Originated from these fundamental assumptions, two essential postulations are as follows: ‘there is a link between entrepreneurship and learning’ and ‘there are gender differences and various perspectives on this relationship’.

A second assumption was

provided by Pérez Estébanz, Urquìa Grande, and Muñoz Colomina (2010) and refers to users’ opinion concerning a link between ‘IT introduction in SMEs and business management development’. In addition to this opinion, Hashi and Krasniki (2011) postulated that ‘there is a positive impact of technology, innovation and networking upon business growth’, and Davis (2012) stated “there is a positive relationship between education and business outcome”. Whilst, Knör (2011) argued that women’s experience led them to entrepreneurship, where education and training are ‘key factors’ to success (Center for Women Business Research, 2008). Thus, despite that, women entrepreneurs are “an untapped resources” (Lawton, 2010), and their training is essential for business growth (Rajitha, 2012), there is a lack of research on methods of learning, Communities of Practice and knowledge acquisition (Higgins and Aspinall, 2011). Andersson and Tell (2009) argues about a relationship between business growth and the management of a small business. In other words, they said, managers have an impact upon business growth. Research by St-Pierre and Audel (2011) claim a relationship between education and business performance, where growth is considered an element of performance. Moreover, there are other factors (Peris Bonet, Rueda Armengot and Galindo Martin, 2011) influencing business growth/success such as: networking and multiple learning (Andersson and Tell, 2009).

Other authors notice a relationship

between knowledge, learning and the manager of the firm (Higgins and Aspinall, 2011). 99

In other words, there is a lack of research on women entrepreneurs (Roomi et al., 2009; O’Caroll and Millne, 2010), gaps in educational entrepreneurship research (Neergaard et al., 2009), lack of studies on factors influencing business growth (Roomi et al, 2009) and little research on gender and business growth (Carter et al., 2001; Mitchemore and Rowley, 2013). Following the above assumptions, and the outcomes of the literature review (Brush, 2000; Drucker, 1985; Abell and Oxbrow, 2011; Illahian and Sherry, 2012; Etkiwitz et al., 2010; Meyer and Xia, 2012; Harris, 2009; Davis, 2012; Gertner, 2013; Indrupati and Henari, 2012), the author contributes to knowledge, by linking the assumptions to the gaps in the literature, and formulates the following hypotheses: “H1: There is a significant relationship between Learning, Digital Platforms & ICTs and WES”. “H2: Learning has a positive impact on Women Entrepreneurs’ Success”. “H2.1: The Impact of Learning on WES is controlled by CoPs & networking”. “H3: Digital Platforms & ICTs have a positive impact on WES”. “H3.1: The Impact of Digital Platforms & ICTs on WES is controlled by CoPs & networking” “H4: There is a correlation between Learning, Digital Platforms & ICTs and WES. The Conceptual Research Framework incorporates two independent variables (IV) – Learning (EED) and Digital Platforms & ICTs (NET & ICTs), and one dependent variable (DV) – Women Entrepreneurs’ Success (WES). Additionally, the research framework has a controlled variable (CV) - CoPs & Networking. Below, the author presents the Conceptual Research Framework (Figure 3.4) and the Research Path (Figure 3.5). Chapter three introduced the main theories of the research and designed the theoretical research framework. These were followed by the identification of gaps in the literature with the main findings supporting the research concepts. Finally, the chapter ended with evidence supporting the Conceptual Research Framework, Research Path, and the generation of the hypotheses for this thesis. Next, Chapter four presents the Research Design & Methodology.

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Figure 3.4: Conceptual Research Framework for Women Entrepreneurs’ Success

Communities of Practice & Networking -Membership -Type of Participation

Learning

-Educational Background -Entrepreneurial Knowledge -Entrepreneirial Training -Entrepreneurial Competences -Styles of Learning -Methods of Learning -Learning Needs -Learning Preferences

H4 Women Entrepreneurs’ Success

Financial measures: -Increase in Sales -Increase in Profit

Digital Platforms & ICTs

-Digital Platforms -Information Communication Technologies (ICTs)

Non-financial measures: -Networking & CoPs -Social recognition -Customer loyalty/satisfaction -Quality of products & Services -Health -Survival -Enjoyment

Source: © F. Tomos, 2016, 2019 (Based on the literature review)

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Figure 3.5: The Research Path STAGE ONE:

STAGE 1 Successful

Literature Review Research Methodology & Design Conceptual Research Framework Variables of the Research

STAGE 2 Successful

Conference Papers

STAGE TWO: Unsuccessful

A. Research Instruments Questionnaires Design: Survey, Focus Group and Interviews Piloting the Research B. Data Collection: Online survey in Wales & England Fieldwork: Survey with Questionnaires in South East Wales, UK Focus Group & Interviews in South East Wales, UK C. Data Analysis/ Mixed Methods Research Preparing the Coding Book (Quan/Qual) & Data Processing Quantitative Data Analysis with SPSS Qualitative Data Analysis: Interviews & Focus Group Transcriptions and Coding Interviews Analysis with IPA Focus Groups/Interviews Analyses with Thematic Analysis, Template Analysis & IPA, CA

STAGE 3 Successful STAGE THREE: Writing Draft Chapters, Discussions & Conclusions Making Corrections Conference Papers, Article & Book Chapter Final Writing & Thesis Submission Source: F. Tomos, 2016 (Inspired from Ramdani, 2008)

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CHAPTER FOUR: RESEARCH DESIGN & METHODOLOGY Figure 4.1: Chapter Four CHAPTER FOUR METHODOLOGY AND RESEARCH DESIGN

METHODOLOGY AND RESEARCH DESIGN

QUESTIONNAIRES DESIGN & DATA COLLECTION

-RESEARCH PROBLEM AND PHILOSOPHY -RESEARCHERâ&#x20AC;&#x2122;S PHILOSOPHICAL PERSPECTIVE -RESEARCH APPROACH & DESIGN -SAMPLING TECHNIQUES, SAMPLES AND DATA COLLECTION -ETHICAL CONCERNS -DATA COLLECTION -PILOT STUDY -CODING AND PROCESSING THE DATA

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4.1 Introduction to Chapter 4 The research design is a general plan prepared in order to answer the research questions, linking the research problem to the empirical research, and supplying a framework for data collection and analysis, with ultimate purpose of knowledge enhancement and theory construct (Ghauri and GrĂ¸nhaug, 2005; Zigmund et al., 2010; Saunders et al., 2012). The structure of the chapter (Figures 4.1; 4.2); introduces the flow of this part of the thesis. The chapter presents the research problem and the research philosophy that form the basis of this study, together with the research purpose, approach and types of research. Further, the author discusses the research methods, in a comparative and critical manner, the importance of using mixed methods, and the rationale of such choice. Next, the author argues about the methodology, sampling techniques, defines samples, explains the reasons for choosing certain approach, techniques and methods and closes with ethics and their importance in conducting research. The last section of the chapter concerns the research design and the main phases of the research. Before starting to discuss the structure of this chapter, the author discusses the findings of the analysis of 30 relevant articles on the research methods used in the field of entrepreneurship, and published in Entrepreneurship Theory & Practice (ET&P) across a period of twenty years. This indicated the lack of complex methodologies used in the field of entrepreneurship, a single method analysis, and a research design simplistic and irrelevant for such an intricate phenomenon as entrepreneurship. The findings discovered that only 30% of the articles used empirical research, and this was limited only to quantitative (survey with questionnaires) method. Furthermore, 69% of the analysed articles employed literature review, and 1% of the articles used secondary data. Only one per cent of the studies recommended a change of entrepreneurship research direction, and argued the lack of complex methodologies. These results are confirmed by further analysis of relevant but limited number of articles regarding the state of the research methodology (Table 4.1): Table 4.1: Research Methodology (the analysis of twenty relevant articles) Total articles

Theoretical articles

Total

Qualitative

20 100 %

6 30 %

14 70%

4 20%

Source: F. Tomos, 2016 (Based on the literature review)

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Empirical Articles Quantitative Quantitative (Secondary (Primary Data) Data) 4 4 20% 20%

Mixed Methods 2 10%

From this succinct analysis (Table 4.1), it is clear that only 20% of the total selected number of articles is based on quantitative methods with primary, raw data analysis and 10% of the total number of articles employed the Mixed Methods Research (MMR), such as Survey, Focus Group, Interviews and Life Biography. There is a strong predisposition (about 50%) towards theoretical and secondary data analysis (databases or data sets). Additionally, only 30% represents articles, which focus on women owned small businesses. There is a lack of MMR and thematic analysis, which are adequate for the empirical studies on womenâ&#x20AC;&#x2122;s entrepreneurship. Although, entrepreneurship is a young discipline (Jennings and Young, 1990), from the analysis, it was clear that, the research on entrepreneurship was lacking complex methodologies, relevant to such a compound field as entrepreneurship (Scherrer et al., 1989). Consequently, authors (Plaschka and Welsch, 1990) highlighted the need of a shift in entrepreneurship research, towards complex research design, with complex methods, usage of large samples and complex conceptual research framework, leading to the advancement of the field. However, other authors, like Herron, Sapienza and SmithCook (1992) argued that, the usage of qualitative methods, such as interviews with rich data and small samples, as well as the theoretical basis employed by other disciplines, was the main solution for advancing the field. Besides these discussions, Bygrave and Hofer (1991) recommended a holistic approach to entrepreneurship and holistic entrepreneurial models, together with focusing on the entrepreneurial process and the embedment of the entrepreneur within the context and entrepreneurial process. This argument supported previous research by Gartner (1989), and it seems to be relevant for this field. Furthermore, later research by Hofer and Bygrave (1992) emphasised the demand for good quality research and provided the main factors required to assure a good design for the theoretical model and high quality research, no matter that the findings include negative outcomes. Therefore, the rationale of this thesis is to provide a complex research design and conceptual research framework, with large sample and complex methods, originated in the above findings. Below the author of this thesis presents a complex structure of this chapter (Figure 4.2).

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Figure 4.2: The Structure of Chapter 4

POSITIVIST PHENOMENOLOGICAL Paradigms

Assumptions: Epistemology Ontology Axiology Rhetorical Methodology

RESEARCH PHILOSOPHIES (PARADIGMS)

Research QUESTIONS

Exploratory

RESEARCH PURPOSE

Descriptive

Explanatory 4 RESEARCH METHODS 3

Deductive

Qualitative

RESEARCH APPROACH Quantitative

Mixed

Inductive

RESEARCH DESIGN ETHICS

Research Phases

SAMPLING

Source: F. Tomos, 2016 (inspired from Satiropoulos, 2014 & literature review)

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4.2 Research Problem & Philosophy An empirical research is conducted in view to answer the research questions (Ghauri and Grønhaug, 2005). The research problem under clarification, within this study, is whether learning and Digital Platforms & ICTs affect WES in the context of CoPs & networking. The research design is explanatory, exploratory and correlational. Further, the research develops hypotheses regarding the relationship between variables, in view to testing a designed conceptual research framework, as a possible theoretical model for generalisation (Ghauri and Grønhaugh, 2005). In the text, hypotheses are estimates explaining outcomes, consequences, relationships between concepts; variables are evaluations of constructs regarding qualities, objects or processes; theories are statements, which, could be tested in order to find out relationships between phenomena (Zigmund, et al., 2010). The study ensures that the research questions are both descriptive and exploratory, and have clear, interconnected, achievable objectives, which, are linked to the research questions (Saunders, Lewis and Thornhill, 2012). This study is a paradigm-driven approach, which according to Punch (2009) starts with the assumption that learning and Digital Platforms & ICTs impact upon WES; further, the paradigm uses various methods in view to answer the research questions. To emphasise, the philosophical standpoint of the thesis is mixed paradigm, with a predominant Positivist view. As a result, in the first phase, this research tests the theory (Saunders, Lewis and Thornhill, 2012; Trafford and Leshem, 2008). Based on the literature review, the researcher conceived the conceptual research framework, in order to explain the relationships between the variables of the study. Consequently, the author starts with the ‘theory – first’ and deduces the hypotheses (Bell, 2005). In other words, the author designs the conceptual framework and tests the following hypotheses: “H1: There is a significant relationship between Learning, Digital Platforms & ICTs and WES”. “H2: Learning has a positive impact on WES”. “H2.1: The Impact of Learning on WES is controlled by CoPs & networking”. “H3: Digital Platforms & ICTs have a positive impact on WES”.

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“H3.1: The Impact of Digital Platforms & ICTs on WES is controlled by CoPs & networking” “H4: There is a correlation between Learning, Digital Platforms & ICTs and WES. Philosophy is described by the Oxford Dictionary (1999) as “the study of the fundamental nature of knowledge, reality and existence”, or “the study of the theoretical basis of a branch of knowledge”.

A paradigm is “a world view underlying the theories and

methodology of a scientific subject” and an assumption is “a thing that is assumed as true” (Oxford Dictionary, 1999). According to Collis and Hussey (2003) a paradigm is the advance of science based on individuals’ philosophies and hypotheses regarding the world and knowledge. Collis and Hussey (1999) argued about two main research paradigms: positivist and phenomenological. Consequently, this research uses a mixed paradigm: positivist and phenomenological. According to their argument, the positivist paradigm is traditional, objective, quantitative and based on experiments, whilst the second paradigm, the phenomenological perspective, is viewed by Collis and Hussey (1999) as subjective, qualitative, humanistic and interpretivist. A review conducted by McDonald et al. (2015) on five high ranked entrepreneurship journals, between 1985 and 2013, indicates that the positivist paradigm is the main research philosophy used by the authors. However, there is a change in the trend of research, towards an increase in conceptual studies, and a decrease in surveys as the main research methods. According to Collis and Hussey (1999) each of these two paradigms/philosophies (positivist and phenomenological) has five corresponding assumptions: ontological, epistemological, axiological, rhetorical and methodological. However, there are other views on the main philosophical positions. Following a study by Guba and Lincoln (1994), who discovered four essential paradigms in social science research (positivism, postpositivism, critical theory and constructivism), Eriksson and Kovalainen (2008), suggested the following paradigms: positivism and postpositivism; critical realism; interpretivism

and

constructionism;

hermeneutics;

and

postmodernism

and

poststructuralism. These philosophies emphasise the way individuals or groups of people interpret and understand the phenomena. It follows that the philosophical root of interpretative/constructionist research are hermeneutics and phenomenology and the technique in achieving a good interpretation is by means of text or language and people’s 108

common values as a group (Eriksson and Kovalainen, 2008). Consequently, the reality is shaped not by singular acts, but by “complex and organised patterns of ongoing actions” (Eriksson and Kovalainen, 2008, p. 20). In addition to these philosophical perspectives, there is another view, developed by Saunders, Lewis and Thornhill (2012). Conform to their opinions, there are four major philosophies: pragmatism, positivism, realism and interpretivism.

According to

Durkheim (1983), pragmatism is connected to a new form of empiricism, which requires change. In other words, pragmatism “sees as solely important not...principles, but practical consequences” (Durkheim, 1983, p. 59). The first pragmatist principle is that “the truth...must be a useful truth” (Durkheim, 1983, p. 50). As opposed to this, Schmidt characterised ‘positivism’ as the school of thoughts where “...the method of the various single sciences is taken absolutely as the only valid method of knowledge”. (Ropper, 1969, p. 299) In order to discuss the assumptions related to each of these two philosophies, we need to introduce the new terms and to understand the meaning of these new concepts: ontology, epistemology, axiology, rhetoric and methodology and to define them (Eriksson and Kovalainen, 2008). Ontology refers to whether the researchers should define the subject of research as factual or real, and external to individuals or should be considered as the perceptions and actions of the individuals (Bryman, 2001; Bryman and Bell, 2011). “Ontology is concerned with nature of reality” (Saunders, Lewis and Thornhill, 2012, p. 130). Other views on ontology define this as the opinion regarding the rapport between individuals and the world (Eriksson and Kovalainen, 2008). Epistemology evaluates the knowledge, and answers the question regarding to ‘what is the confirmed knowledge in a field’ (Collis and Hussey, 1999; Bryman, 2001; Bryman and Bell, 2011). The axiological assumptions refer to values and whether the researcher regards the research process as external and hence value-free or it is biased (Collis and Hussey, 1999). Rhetorical assumptions involve the accepted style and the standard of the research language (Collis and Hussey, 1999). Methodology regards the entire research process, which mainly is established by the research paradigm (Collis and Hussey, 1999; Bryman and Bell, 2011). Methodology is “a system of methods used in a particular field” (Oxford Dictionary, 109

1999). Methods “refer to various means by which data can by collected and/or analysed” (Collis and Hussey, 2003, p. 55). Alternatively, the second paradigm is the phenomenological paradigm/philosophy. According to Patton (2002, p. 9) the main purpose of phenomenology is to have “a deeper understanding of the nature or meaning of our everyday experiences”. In a phenomenological paradigm, ontologically, the reality is subjective with multiple interpretations given by women entrepreneurs, as participants in the research (Collis and Hussey, 2003). Morever, the reality is based on various perceptions and these are dynamic, numerous and dependent on the context (Eriksson and Kovalainen, 2008). From epistemological standpoint, there is a relationship between the researcher and the subject of the research. As a consequence of this interpretation, axiologically, the results are biased. The research language is informal, whilst the research approach is regarded as inductive, with patterns and emerging themes, leading to theory development. The outcome of the research is assessed for reliability and validity (Collis and Hussey, 2003). 4.3 Researcher’s Philosophical Perspective From the ontological view of positivist philosophy, this research is an objective and independent perspective.

However, the subjectivist ontology is also considered.

According to this view (Saunders, Lewis and Thornhill, 2012) small businesses with women entrepreneurs are “social entities” created as a result of women actions as managers and leaders. Furthermore, it is argued that women managers attach their personal

characteristics,

skills,

knowledge

their

roles

entrepreneurs.

Epistemologically, the study focuses on the causal relationship between variables such as: learning, Digital Platforms & ICTs and WES. Additionally, the study considers an extraneous/controlled variable: CoPs & networking. As Saunders, Lewis and Thornhill (2012) mention, from the axiological view, the Positivist philosophy assumes that this research is undertaken in a “value-free way”, in other words, the researcher is independent of the data. Also, Saunders, Lewis and Thornhill (2012) argue that, the positivist view requires the use of a large structured sample as quantitative technique. This is a deductive approach, which starts with academic literature review and continues with theory verification. In this study, the deductive research approach investigates the relationships between variables, controls the validity of data, and uses the probability sampling technique in order to assure 110

generalisability of the results from the sample to the entire population with women entrepreneurs in the South East Wales, UK (Saunders, Lewis and Thornhill, 2012). However, my philosophical position resides in a combination of two paradigms: predominantly positivist philosophy, seconded by the phenomenological paradigm, which aims to enhance understanding, and expands the meaning of results of the research. The main research question of the thesis regards the impact of Learning and Digital Platforms & ICTs upon WES, the relationship and correlation between these three variables. The main research question is: ‘What is the impact of Learning and Digital Platforms & ICTs on WES, in the context of CoPs and networking?’ and the outcome is derived from testing the hypotheses, which is confirmed. Alternative research questions can be ‘How do Learning and Digital Platforms & ICTs affect WES in the context of CoPs & networking?’ or ‘In what ways do they impact WES in the context of CoPs & networking?’ The main question determines the philosophical standpoint, which is positivist. However, the author believes that the positivist philosophy is not sufficient for the understanding of the phenomenon, and the contradictory results or in depth, understanding cannot be interpreted unless involving a phenomenological paradigm as well. Therefore, in order to increase the research capability of results interpretation, the author of the thesis employs a second philosophy, phenomenology, which improves the understanding by providing rich and subjective data (Collis and Hussey, 2003). As Zikmund et al. (2010) highlighted, phenomenology has its roots within philosophy and psychology. According to their view, the human perceptions on a certain phenomenon are shaped by their relationships with the environment.

A further definition on

phenomenology is provided below: “Phenomenology represents a philosophical approach to studying human experiences based on the idea that human experiences itself is inherently subjective and determined by the context in which people live.” (Zikmund et al., 2010, p. 137) The main research approach to interpreting and understanding phenomenology is hermeneutics, which means the analysis of the text and the extraction of the meaning by linking ‘text passages to one another or to [created] themes’ designed by the researcher (Zikmund et al., 2010, p. 138). Additionally, based on the formulation of the hypotheses of the research and the arguments provided by Collis and Hussey (2003, p. 53), in the above citation (b), this is an exploratory research, testing the hypotheses which predict 111

the manifestation of the phenomenon and therefore is predominantly a positivist paradigm. The research questions of the thesis incorporate explanatory elements and therefore the research requires a second paradigm, a phenomenological paradigm. Thus, the thesis requires an understanding of ‘how women entrepreneurs learn and acquire knowledge in the context of CoPs & networking and Digital Platforms & ICTs’. The researcher needs to understand how women interpret and measure entrepreneurial success and the reasons of enjoying entrepreneurship. This is a complex research question, which implies that significant attention has to be paid to the participants’ view, regarding how women learn and acquire knowledge in the context of CoPs & networking and Digital Platforms & ICTs. The emphasis here is on the subjective aspects of the phenomenon by placing the accent on the meaning and interpretation of the answers given by the respondents, instead of the measurement of the phenomenon (Collis and Hussey, 2003). Further interpretation is required for the meaning of the key terms of the research from the participants’ views. The researcher can understand the phenomenon within its complex context and as embedded within women entrepreneurs’ perceptions, and this can be achieved by considering the additional paradigm, the phenomenological paradigm with an Interpretative Phenomenological Analysis (IPA) (Collis and Hussey, 2003; Langdridge, 2007; Smith, Flowers and Larkin, 2009). The two paradigms come together and strengthen the results of the research. In the first part of the research, the reality is objective and separate from the researcher. From a positivist standpoint, this reality is shaped by testing four hypotheses and answering the main research questions with regard to the impact of Learning and Digital Platforms & ICTs upon WES, in the context of CoPs & networking. Epistemologically, the researcher is independent from women entrepreneurs and entrepreneurial success.

The study

produces quantitative precise data, uses a formal research language and the research is value-free and unbiased. Methodologically, this research is a deductive research process, which allows possible generalisation and prediction. The results of the research are assessed for reliability and validity (Collis and Hussey, 2003). The expected outcome is that Learning and Digital Platforms & ICTs have an impact upon WES. In addition, there are both, a relationship and a correlation between the variables of the research. In the second part of the research, the reality is subjective, with multiple interpretations given by women entrepreneurs to learning and acquiring knowledge, measuring and defining WES and business growth, women’s entrepreneurship and women 112

entrepreneurs. The researcher interacts with women entrepreneurs and probably the outcome may be biased. However, the researcher employs methods triangulation, and as a result, the evidence from one method comes to strengthen the other method, validating the results. The qualitative data is based on the personal interpretation provided by women entrepreneurs.

The research language for this time is informal and the

methodology is based on the inductive process, categories, patterns and emerging themes. The entire process leads to theory generation. The results can be accurate and reliable if verified (Collis and Hussey, 2003). In conclusion, knowledge creation is based on both the reality of the world, and the participants’ personal views and perceptions of the phenomena. A dual approach to research philosophy can enhance and strengthen the outcome of the research. Theories have a certain degree of truth and the results of research are not absolute. There is a probability that Learning and Digital Platforms & ICTs impact upon WES. There is probably a relationship between the variables of the research and the reality (relationship, correlation) is probably predictable. The aim of the thesis is to investigate whether there is a relationship, and correlation between the variables of the research, and whether learning and Digital Platforms & ICTs impact upon WES, in the context of CoPs & networking.

Moreover, there is an implicit purpose, to understand and interpret the

results and if possible, to find reasons. The research question of the thesis is a complex question, which requires an interdisciplinary approach to the field of women’s entrepreneurship. To answer such a complex question and to create knowledge, the researcher contributes to theory development by creating a Business Model for Women Entrepreneurs’ Success (Collis and Hussey, 2003). 4.4 The Rationale and implications of using Mixed Paradigms Articles published in high ranked journals such as Entrepreneurship Theory and Practice (ET&P) and Journal of Business Venturing (JBV) (Molina-Azorìn et al., 2012) indicated two main paradigms used within the entrepreneurship research: positivist and interpretive paradigms (Table 3.8; Kirkwood and Campbell-Hunt, 2007). Despite the contradictions, researchers need to consider both perspectives in order to have a holistic understanding of the entrepreneurship phenomenon.

Thus, the interpretive paradigm explains

phenomena in order to understand, and concerns the interpretation of phenomena and theory building. The positivist paradigm tests the hypotheses regarding phenomena, and deals with relationships between variables, in view to ensure generalisation of the results 113

(Gioia and Pitre, 1990; Pittaway, 2005). Conversely, an emphasis on positivism leads to an increase in role of the scientific element, and the decrease in the role of the human element (Pittaway, 2005). Moreover, it was argued that the positivist paradigm was moved from the natural sciences to social sciences and then imported into the entrepreneurship field. Consequently, there are concerns regarding its suitability for this research field and also there are arguments denying its comprehensiveness (Kirkwood and Campbell-Hunt, 2007). Other authors (Kirkwood and Campbell-Hunt, 2007; Gioia and Pitre, 1990) argued about an overlapping area between the two paradigms that requires discussions and the use of both paradigms in view to understand a phenomenon. Furthermore, Berglund (2015) confirms the complementary feature of phenomenology paradigm, by adding value to the interpretation of phenomena and ensuring contribution to practice and policy. Entrepreneurship phenomenon is characterised by creativity, therefore, the richness of the meaning and the individual experience brought as an additional element by the interpretive paradigm is classed as valuable (Berglund, 2015).

As mentioned by Ahl

(2006), the current entrepreneurship research has a narrow focus, is fragmented and needs a change in direction. Consequently, by using both paradigms, it yields a holistic view of the phenomenon. In line with this assertion, Refai, Klapper and Thompson (2015) suggested that the holistic view of the entire phenomenon is more significant than the addition of all individual parts studied in isolation. In line with the above, the mixed method research (MMR) assisted the author of this thesis in generating theory and testing theory in a simultaneous manner. Thus, the analysis of the transcripts from the interviews and focus group, informed the researcher to design a theoretical business model for WES, and several pioneering theoretical models. Further, MMR helped the author to construct thorough, complete and holistic answers to the research questions (Molina-AzorĂŹn et al., 2012). MMR implies that the researcher has high level capabilities and knowledge in using and interpreting various methods, and also involves longer time for collecting, transcribing, analysing and interpreting the data (Molina-AzorĂŹn et al., 2012). As a consequence of using such method, which is complemented by visual frameworks of the process of data collection and analysis, the researcher provides rigorous results and is also able to enhance the validity of the findings (Molina-AzorĂŹn et al., 2012). In conclusion, equally important is to apply phenomenology philosophy not only within the social science field, and the 114

domain of pedagogy (Berglund, 2015), but also within the field of women’s entrepreneurship, and find out their perceptions and opinions regarding the meaning of entrepreneurship, in order to establish appropriate parameters for measuring WES. 4.5 Research Purpose & Types of Research The central research question of the thesis offers details regarding the general aim of the research (Sotiropoulos, 2014). Additionally, the purpose of the research is associated with the type of research undertaken by the researcher. Thus, there are three main types of research: exploratory, descriptive and explanatory research (Zikmund et al., 2010). In view to explain the purpose of this thesis, the author needs firstly to introduce and define each type of research. Robson (2002) and Saunders, Lewis and Thornhill (2003) define exploratory studies as attempting to answer the question: ‘What is happening?’ and search for in depth interpretations and new meanings. Descriptive studies are defined as a description of individuals and situations, whilst the last category of studies, the explanatory or causal studies are reported as focusing on the problem to discover and justify the relationship between the variables of the research. It follows that, according to such opinions (Robson, 2002; Saunders, Lewis and Thornhill, 2003), this thesis is both an explanatory (causal) and exploratory research study. Considering that the study is hypotheses testing and hence confirmatory, and the hypotheses are clearly defined, it infers that this is the best description of the main research purpose of the thesis (Zikmund et al., 2010). However, the author of this thesis suggests that the purpose is predominantly hypotheses testing and predictive. Additionally, the research is also a combination of another two types of research, embedding exploratory and interpretative elements (exploring women entrepreneurs’ perceptions about the entrepreneurial success) and descriptive elements (entrepreneurial profile/entrepreneurial activity/models of learning). The causal relationship, implying ‘a cause’ and ‘effect’, leads to the definition of theory. The Oxford Dictionary (1999) defines theory as “an idea accounting for, or justifying something”, or “a supposition or a system of ideas intended to explain something”. A well-formulated definition of theory is that provided by Martella, Nelson and MarchandMartella (1999): “...a theory may be a simple guess where the person stating the theory is making some prediction or explanation”. 115

(Martella, Nelson and Marchand-Martella, 1999, p. 8) Martella, Nelson and Marchand-Martella (1999) define the theory as follows: (a) a guess; (b) a model designed to enhance understanding; (c) a structure, which shows the collected data before theory being originated. In line with these authors, this thesis undertakes a combination of purposes: prediction of impact and correlation; improvement of methods of learning; creating innovative business & learning models; explaining and describing the phenomenon from women’s perspective. Finally, this is a cross-sectional study of the phenomenon: ‘the impact of learning and Digital Platforms & ICTs on women entrepreneurs’ success, in the context of CoPs & networking’ at a particular time: June September 2015. 4.6 Research Approach and Design The theoretical approach for this research is a combined approach: entrepreneurship, learning, social capital and data theories. These theories are exhaustive and thorough theoretical perspectives that allow analysing the impact of learning and Digital Platforms & ICTs on WES, and the role of CoPs & networking, subject to the particular research approach. Thus, the theories used in this thesis are made clear in the design of the research, as well as within the theoretical research framework (Figure 3.3) (Saunders, Lewis and Thornhill, 2012). In other words, the theories of the research led to the research design of this thesis. In order to understand the next few lines of this chapter, the author needs to explain ‘What is empiricism?’ Empiricism is a research approach to reality that advocates that only knowledge acquired by means of experience and perceptions is adequate (Bryman, 2001). Some authors defined empiricism as the way of gaining knowledge by observation, investigation, examination and survey (Martella, Nelson and Marchand-Martella, 1999). However, there are two types of theories: (1) the first type of theories leads to research questions formulation and further to data collections and data analysis; (2) the second type of theories is that originating after partial or whole data collection and analysis. This kind of relationships between theory and research, impacts upon the class of theories we have: deductive or inductive (Bryman, 2001). Martella, Nelson and Marchand-Martella (1999) argued about two forms of logic: the ‘inductive’ that goes from specific to general and the ‘deductive’, that goes from general to specific. Moreover, they said, the researchers attempt to demonstrate their hypotheses and predictions, instead of bringing something new. In addition to this, the deductive 116

conclusions are an enlargement of former knowledge (Martella, Nelson and MarchandMartella, 1999). According to Eriksson and Kovalainen (2008, p. 22) deduction is based on the assumption that ‘theory is the first source of knowledge’. It follows that the hypotheses are deducted from the theoretical basis and then are analysed empirically, whilst in the inductive approach, the process starts with the empirical analysis, which is followed by theoretical outcomes (Eriksson and Kovalainen, 2008). Besides deductive and inductive theories, there is a third type of theories, called abductive theories, which are defined as the process of progressing from the ‘descriptions and meanings’ provided by individuals, “...to categories and concepts that creates the basis of understanding or an explanation to the phenomenon described” (Eriksson and Kovalainen, 2008, p. 23). As a consequence of the following facts: (1) the way the research questions of the thesis and the focal research question are formulated; (2) the research involves hypotheses testing; (3) the study uses large data sample, it infers that this research is predominantly based on a positivist paradigm, which is the dominant paradigm in business research (Collis and Hussey, 2003).

Further, the research follows a hypothetico-deductive

approach by predicting: (1) the relationships between learning, Digital Platforms & ICTs and WES; (2) the impact of learning on WES; (3) the impact of Digital Platforms & ICTs on WES, and by deducing the hypotheses from the entrepreneurship theory and its perspectives

(growth/resource-based:

entrepreneurship

education;

innovation/technology) (Penrose, 1980; Drucker, 2015). “In general, no single model of scientific research is used, as the whole research process most often consists of various forms of reasoning.” (Eriksson and Kovalainen, 2008, p. 23) The second paradigm that I used within the thesis is the phenomenological paradigm (Collis and Hussey, 1993), which became adequate in business research, specifically in the field of women’s entrepreneurship, which requires a specific research approach. This is not considered as a reaction to the positivistic paradigm, but instead comes to explain and enhances the results from the positivist paradigm (Collis and Hussey, 2003). According to Collis and Hussey (2003), phenomenologists believe that the reality is subject to human thinking and mind. Therefore, the research approach has a tendency 117

towards an â&#x20AC;&#x2DC;inductiveâ&#x20AC;&#x2122; research approach, which is more oriented towards the description and interpretation of the meanings (Eriksson and Kovalainen, 2008). In the inductive research approach, the collected data is employed in an exploratory manner, in order to establish patterns and themes, which are verified and used to create theory (conceptual model) (Saunders, Lewis and Thornhill, 2012). This research approach is employed not entirely but partially in view to assist the research in interpreting the outcomes from the positivist paradigm, and to answer further research questions of qualitative substance. Thus, the research approach of this thesis considers the occurrence of patterns, concepts and emerging themes leading to a better understanding of the meaning and the interpretation of womenâ&#x20AC;&#x2122;s entrepreneurship phenomenon and the factors leading to WES, and finally, to theory generation (Saunders, Lewis and Thornhill, 2012). My standpoint, concerning the philosophical background, considers a combination of two paradigms, which is supported by Collis and Hussey (2003), and Eriksson and Kovalainen (2008). From the literature review of the latest articles on women entrepreneurs and business research methodologies, published in high ranked journals, there is a clear trend towards multiple and MMR usage, and this requires new, appropriate and innovative philosophical perspectives and philosophical views combination (Tomos et al., 2015). The research design of this thesis is a combined design, embedding exploratory, explanatory and descriptive elements. As elucidated in the research design (Figure 4.5) the research process contains a chain of progressive research phases. The design of this thesis incorporates four phases. (Figure 4.5). In Phase One, the researcher proceeded to literature review. This led to the following: conceptual research framework, extraction of the aim and objectives, hypotheses and variable defined. In the Second Phase, the author designed the research instruments for the survey, interviews and focus group, conducted pilot study and the fieldwork. In the Phase Three, the researcher completed the missing data, designed the Coding Book, processed and analysed the data with SPSS. In addition, the author transcribed the Focus Group and 37 Interviews and analysed the themes. Finally in the Phase Four, the author proceeded to data analysis in a holistic manner, started writing the findings, interpretations, discussions and conclusions.

118

4.7 Research Methods & Methodology Methodology concerns a holistic approach of the research process, from theoretical support to data collection and analysis (Collis and Hussey, 2003). Methodological theory explains the methods used within the research (Punch, 2009). The methodological approach (Saunders, Lewis and Thornhill, 2012) for this research is the mixed method complex characterised by both quantitative and qualitative methods. Saunders, Lewis and Thornhill (2012) explained that, quantitative research relates to numerical data, and uses questionnaires for data collection, whilst qualitative research deals with non-numeric data, such as words, and uses interviews for data collection. Collis and Hussey (2003) defined methods as being research techniques. Furthermore, authors argued that the advancement of entrepreneurship theory as well as the use of appropriate and complex research methods assists the validation of entrepreneurship field (Molina-Azorìn et al., 2012). Although, there are various perspectives on mixed methods research (MMR), in author’s opinion, MMR blends qualitative and quantitative methods together, in view to collect, analyse and interpret the data. Nevertheless, there are contradictory arguments regarding the incompatibility of these methods, as a consequence of the incongruity of the paradigms (positivist and phenomenological) (Howe, 1988; Molina-Azorìn et al., 2012). According to the selected research approach, this study undertakes the following research strategies: a Survey with 450 Questionnaires in Wales and England, a Focus Group with five women entrepreneurs in the South East Wales, and 37 interviews with women entrepreneurs in the South East Wales, the UK. The mixed method approach assumes that, quantitative research leads to theory verification, and qualitative research leads to theory generation (Punch, 2009). However, as Saunders, Lewis and Thornhill (2009) argued that, the reason, for using the mixed approach within this research, is the enhancement of research meaning. Based on the research philosophy, research strategies used by this study (survey, focus group and interviews) are required by the characteristics of the research paradigm. Ghauri and Grønhaug (2005) defined the Survey as a method that uses the Questionnaires or Interviews as techniques to record the answers from the respondents. The third research strategy employed by the study is the Focus Group, which is described by Ghauri and Grønhaug (2005) as the method of gathering a few respondents at the same time to discuss 119

on a chosen topic. This research employs also, interviewing techniques with semistructured face-to-face individual interviews (Fontana and Frey, 2000). Why use mixed methods in this study? To answer this important question, the author considered the rationale presented by Saunders, Lewis and Thornhill (2009). According to their views, mixed methods provide the following benefits for the research: (1) triangulation, which means the combination of two or more data collection methods to support the research findings; (2) usage of different data collection methods to complement each other; (3) using qualitative data to explain the relationship between the variables of the research and interpret the findings of quantitative data analysis; (4) using the second method of data collection to explain the controversies from the results of the first method; (5) assessment of opposing aspects: macro aspects (quantitative) and micro aspects (qualitative) (Saunders, Lewis and Thornhill, 2009). Because this research employs triangulation for both data collection and data analysis, it is essential to define the concept of ‘triangulation’. Thus, a very clear and concise definition is presented by Jancowicz (2000, p. 214), who stated that triangulation is the approach that allows, “to use the results from one method to cross-check the results from another”. Nevertheless, Bryman and Bell (2011) engaged into a critical stand point, besides the use of MMR, claiming their lack of superiority to any other research method. The main concerns raised by Bryman and Bell (2011) were the following: (1) they argued that each research procedure, technique or instrument belongs to a particular view of the world and hence, is bound to that line of thoughts, or to a particular interpretation and accepted knowledge; (2) quantitative and qualitative are completely different paradigms, which in conclusion, leads to rejecting each other. Despite the critique of this type of methods, an assessment conducted by Bryman (2009) on the articles published on MMR across the last decade, demonstrated a considerable increase in the number of research focusing on mixed methods approach, plus an emergence of a specialist handbook by Tashakkori and Teddlie (2003), and specialist journals such as the Journal of Mixed Methods Research and the International Journal of Mixed Methods for Applied Business and Policy Research (Bryman and Bell, 2011). This advancement in the field of business research methods demonstrate that the MMR is a valid and confirmed method recognised by researchers across the world. Further, the outcomes of such analysis strengthen and support the author of this thesis, in her choice to use MMR, and in providing a solid rationale for selecting such a method. 120

How to use MMR in this study? There are a few suggestions from different authors (Morse, 1991; 2003; Tashakkori and Teddle, 2003; Cresewell, 2003; Johnson and Onwuegbuzie, 2004; Molina-Azorìn, et al., 2012), with regard to carrying out data collection and the priority in data collection and analysis. According to Johnson and Onwuegbuzie (2004) the author of this thesis uses (1) a combination of mixed methods design: ‘QUAN+QUAL’, ‘QUAN to QUAL’ which is equivalent status and simultaneous, and (2) a sequential design for data collection, and (3) ‘QUAN to qual’ which is dominant status with sequential design for data analysis.

Although, in this

research, the quantitative method is predominant, this thesis uses the mixed method either simultaneously (in parallel) or sequentially. In other words, the author uses mixed methods for data collection, in a parallel manner (Teddlie and Tashakkori, 2009; Johnson and Onwuegbuzie, 2004). The rationale for using parallel mixed methods is for the benefit of both, the participants and the researcher.

The author collected data by survey with questionnaires and

employed in parallel or sequentially the interviews and the focus group. However, for the data analysis, the researcher used the MMR in a sequential manner, starting with quantitative data analysis using SPSS and progressing with qualitative data analysis by using Thematic Analysis. The author of the thesis used a technique, called template analysis (TA) created and supported by King (1998).

This technique supports

phenomenological perspective (Langdridge, 2007) and is blended with interpretative phenomenological analysis (IPA) (Smith, Flowers and Larkin, 2009) in a very innovative and creative way, and designed by the author of this thesis. The methodological and methods framework is presented in the figures below (Figures 4.3; 4.4).

Although, there are many attempts to emphasise various philosophical

perspectives (paradigms), as appropriate for the MMR, however, there is not yet established a specific paradigm as the foundation for MMR. As a result, a proposed mixed paradigm as the foundation for conducting this research is appropriate, subject to the rationale provided, the benefits and the validation, based on the outcomes from the methods involved, which supports and assists their use. This is in line with the writing by Creswell and Creswell (2005) who supports the point of view of both, single and multiple paradigms. The author used two types of survey with 450 questionnaires: online/emailing questionnaires to almost 300 women entrepreneurs in England and Wales, and face-to121

face survey with 150 questionnaires distributed to women entrepreneurs in South East Wales. Despite the fact that the electronic survey was unsuccessful, the face-to-face survey with questionnaires proved to be a success. The lack of success, encountered with the online questionnaires, limited the research to South East Wales, only. Nevertheless, ad-hoc, unplanned and planned interviews with women entrepreneurs followed successfully the survey with face-to-face questionnaires, and the researcher gathered also, 37 interviews with women entrepreneurs varying between 20 minutes to one hour the longest interview. The data collection phase was enhanced by a focus group with five women entrepreneurs, participants to a networking event, in South East Wales. In summary, this research employed MMR for both data collection and data analysis, based on the researcherâ&#x20AC;&#x2122;s philosophical standpoint, which is two paradigms combination: positivist and phenomenology.

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Figure 4.3: Methodological and methods framework

PHILOSOPHIES/PARADIGMS

POSITIVIST

PHENOMENOLOGY

METHODOLOGY

MIXED METHODS RESEARCH (MMR)

Qualitative Methods Quantitative Methods

Data Analysis

Data Analysis FG TRIANGULATION

SPSS

Data Collection Descriptive IPA SURVEY

Face-to-Face

Inferential Online

Modelling

Thematic Analysis

Data Collection

Survey (Open Questions)

Factor Analysis Regression

Correlation

Source: Â© F. Tomos, 2017

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Interviews (Is)

Focus Group (FG)

Figure 4.4: Mixed Methods Research Framework

MIXED METHODS

DATA COLLECTION

DATA ANALYSIS

Mixed Methods

Multi-Methods TRIANGULATION

Sequential Methods

Parallel Methods

PHASE 1: Quantitative Data Analysis Interview

Focus Group SURVEY

Survey

SPSS

PHASE 2: Qualitative Data Analysis TRIANGULATION

CA SURVEY Open Questions IPA

FOCUS GROUP

TA PHASE 3: Qualitative Data Analysis TRIANGULATION

Thematic Analysis INTERVIEWS

Thematic Analysis

IPA

Source: Â© F. Tomos, 2017

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CA TA

4.8 Sampling techniques, Samples & Data Collection This section of the chapter approaches the research techniques used for data collection, sampling techniques and samples. Saunders, Lewis and Thornhill (2012) argued about two main sampling techniques: probability or representative sampling techniques and non-probability sampling techniques. Probability sampling group of techniques are as follows: simple random, systematic random, stratified random and cluster random. The second group of techniques are: quota, purposive, volunteer and haphazard (Saunders, Lewis and Thornhill, 2012). By contrast, Ghauri and Grønhaug (2005) accepted the above argument regarding the existence of two main categories of sampling procedures: probability and non-probability, however, their classification of non-probability sampling technique is different.

Ghauri and Grønhaug (2005) classified the non-probability

samples into: convenient or accidental samples, judgement samples, quota samples and snowball samples. Consequently, based on the above opinions, and in order to ensure a significant sample, reliable data and results (Saunders, Lewis and Thornhill, 2012; Ghauri and Grønhaug, 2005), this study started with stratified random sampling (Saunders, Lewis and Thornhill, 2012) and continued to use a probability random simple sampling technique (Kumar, 2005). Based on Ghauri and Grønhaug (2005), Kumar (2005) and Saunders, Lewis and Thornhill (2012), this study employed a simple random sampling technique, where each unit of the population has the equal chance to be included within the sample. Furthermore, in order to ensure the statistical probability and the lowest error in generalising the results to the population, the study decided on a large sample size, such as 450 women entrepreneurs (Saunders, Lewis and Thornhill, 2012). Punch (2009) placed emphasis on the need to collect information through primary sources. Similarly, Saunders, Lewis and Thornhill (2012) argued that the data collected for a significant research should be primary data. According to Saunders, Lewis and Thornhill (2012) this thesis used as principal data collection technique, the questionnaire, such as online questionnaires, telephone questionnaires or self-completing, and interviewer completed questionnaires. Other collection methods mentioned by these authors (ibid. 2012) are observation, semi-structured interview and unstructured interview.

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In order to achieve a good quality research, the author of this thesis considered the design of the questionnaire and the order of the questions, conducted a pilot testing, formulated and sent a covering letter to the participants, and assessed reliability and validity of data (Saunders, Lewis and Thornhill, 2012). However, in order to decide upon the data collection methods, researchers need to know first, what type of data is required by the study and various expert opinions upon this matter. Consequently, this study uses both categorical and continuous variables and employs both quantitative and qualitative methods (Punch, 2009). This is supported by Saunders, Lewis and Thornhill (2012), who classified the data types in two groups: categorical and numerical. According to their opinions, the categorical data refers to data whose values cannot be measured numerically, however, can be arranged in sets or in rank order (Saunders, Lewis and Thornhill, 2012). According to Punch (2009) the main difference between the quantitative and qualitative research studies is that the quantitative methods use measurements, whilst the qualitative do not use these. However, as Saunders, Lewis and Thornhill (2012) mentioned above, researchers can code the data collected through interviews, to allow statistical analysis (Punch, 2009). Furthermore, qualitative methods, as Ghauri and Grønhaug (2005) argued, place accent on the understanding from the respondent’s view, giving an insight of a personal comprehension, whilst the quantitative methods place the focus on testing and verification, adopting a more critical approach, based on hypotheses testing and generalisation of the results. Zigmund et al. (2010) defined sampling, as the technique that produces conclusion based on measurements of a proportion of the population. Further, these authors defined operationalizing, as the process that identifies measurement scales in order to assess the variables of the research. As Ghauri and Grønhaug (2005) mentioned, a measurement is a rule for allocating numbers to characteristics or properties in order for these to be evaluated or analysed; in other words the measurement is “the link” between the theoretical and practical. According to Ghauri and Grønhaug (2005) there are four scales or levels of measurement: nominal, ordinal, interval and ratio. This study uses the following three scales: nominal, ordinal, and interval scales, which assesses the success of women entrepreneurs (Ghauri and Grønhaug, 2005).

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Another important factor to be discussed within this study is the validity and reliability issues in measurements, in other words to assess the quality of the research, as measurements can carry errors. Basically, reliability means consistency or stability of the measure. On the contrary, the validity deals more with theoretical requirements or expectations (Punch, 2009; Ghauri and GrĂ¸nhaug, 2005). According to Punch (2009) there are three main aspects of validity: content validity, criterion validity and construct validity (construct validity shows how a measure conforms to theoretical requirements). Further, in Punchâ&#x20AC;&#x2122;s opinion (2009) reliability is presented as the measure of consistency and presents two aspects: consistency in time, called stability, and internal stability showing whether the variables are working in the same directions. The internal validity is considered the best technique used to measure the quality of the research by calculating the Coefficient-Alpha (Cronbach, 1951 in Punch, 2009) and is employed by this study. In order to find out as much information as possible, this thesis uses within the Survey Questionnaire open and closed questions. Further, different types of closed questions were considered by the researcher: categorical responses (Yes/No), check list responses, ranked responses (by ranking the preferences), scale responses (used to measure responses) and Likert scale (choosing the statement answer that correspond better to respondentâ&#x20AC;&#x2122;s opinion) (Guthrie, 2010).

This research employs the semi-structured

interview, telephone (partial), and face-to-face, as a modality of interaction with the participants (Punch, 2009). Given the characteristics of women entrepreneurs, discussed in the literature review, in this study, the unit of analysis is the woman entrepreneur, either self-employed or the woman entrepreneur owned a small business, with employees or without employees. Furthermore, the study considers all types of women entrepreneurs, both successful women entrepreneurs with years of business experience and women entrepreneurs who just started the businesses, and had a few months since they launched their businesses. In view to have a holistic perspective and understand women entrepreneurs in South East Wales, the researcher considered a variety of women of all ages from 18 years of age to 75 years old or more. These were selected from all kind of fields and activities: retail, manufacture, textile, fashion, arts and crafts, beauty, cosmetics, hairdressing, coffee shops, catering and restaurants, food, construction, services and professional services, training, education, etc.

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Authors argue that, to conduct a survey of the entire population like that of women entrepreneurs, for instance, is expensive, involves long periods of time and is not realistic (Saunders, Lewis and Thornhill, 2009). According to them, sampling is less costly, takes shorter periods and is more suitable. A sample is the section of the population selected to participate within a survey or study (Bryman, 2001). However, before proceeding to data collection, the researchers needed to ensure that certain requirements are met. An essential condition is assuring the adequate sample size and representativeness. The second requirement is the choice of an appropriate sampling technique that allows the researcher to diminish the size of the sample to a group of individuals (Saunders, Lewis and Thornhill, 2012). According to the purpose of this research, this research employed probability sampling technique (Saunders, Lewis and Thornhill, 2003; Bryman, 2001). The author started the survey by e-mailing the questionnaires to 300 women entrepreneurs in England and Wales. The sampling technique, the author used in the first phase of the survey, was stratified sampling technique. Thus, the researcher created a sampling frame or a frame list with organisations, networks and associations with women entrepreneurs in Wales and England (Appendix B, Table 1). The researcher asked permission of organisations, women associations, conferences and women entrepreneurs to participate in the study. According to Saunders, Lewis and Thornhill (2009), a good sampling frame affects the generalisation of the results to women entrepreneur population. Consequently, the next requirement was to determine the sample size and to check the sample for representativeness, in other words to check if the sample represents correctly the population of women entrepreneurs (Bryman, 2001). A high response rate is assumed to secure the representativeness of the sample with women entrepreneurs (Saunders, Lewis and Thornhill, 2009). However, the survey by e-mailing questionnaires was unsuccessful, with only 3% response rate, and the researcher needed to proceed to the second phase: face-to-face survey with women entrepreneurs, with businesses located in the High Streets, commercial areas, and market places, or present at exhibitions and arts and crafts festivals. In view to ensure a successful outcome, in the second phase of the survey, the author of the thesis, limited the research to South East Wales, only, and proceeded to sampling selection criteria for women entrepreneur participants in the face-to-face survey with questionnaires. The selection criteria are enumerated in the table below (Table 4.2):

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Table 4.2: Sampling Selection Criteria for WE participants in the Survey, FG, Is Female owner/manager of a SME located on the High Street in the South-East Wales Women entrepreneurs with SME located in commercial areas in the South-East Wales Women entrepreneurs participants in networking events in the South-East Wales Women self-employed and women with businesses in the Market Place Women self-employed and business owners, participants in exhibitions Women entrepreneurs participants in art and crafts events, market events and fairs Age: 18-75 years old and over Women owned businesses set up at least six months before the survey Women self-employed working in professional services Women entrepreneurs working full/time or part/time Women entrepreneurs single owners or in partnership and family businesses Women belonging to groups, networks and associations Women who do not belong to any group Women entrepreneurs using Digital Platforms & ICTs Women entrepreneurs who do not use Digital Platforms & ICTs Women entrepreneurs working in any sector of activity and any type of business Women entrepreneurs highly educated Women entrepreneurs with basic education or no education Source: F. Tomos © 2016, 2019

In calculating the sample size there are a range of factors that the author of the research had to consider also: time, expenses, non-response rate, heterogeneity of women entrepreneur population and errors (Saunders, Lewis and Thornhill, 2009; Bryman, 2001).

In this thesis, within the section ‘Quantitative Data Analysis’, the author

proceeded to measure the variables of the research by means of Factor Analysis. Consequently, the author followed the recommendations provided by Tabachnick and Fidell (2007), which suggested a ratio of 1:5 in estimating the suitable sample size. It follows that, in order to be consistent, the author of the thesis considered the same principle and determined the sample size for a ratio of 1:4. Thus, there are 40 items that were used to measure ‘WES’ (TFA MSc) and applying the given ratio 1:4, there would be a minimum sample size of 150 women entrepreneurs. The author of this research provides below details regarding the response rate, and the actual sample size, calculated with the formulas provided by Saunders, Lewis and Thornhill (2012, p. 269):

nª =

n x100 re%

Where nª is the actual sample size, n is the minimum sample size and re% is the estimated response rate. Thus, the actual sample size that was randomly selected is: nª = 150 x 100/90 = 167 women entrepreneurs (Saunders, Lewis and Thornhill, 2009, 2012; Tabachnick and Fidell, 2007; Sotiropoulos, 2014). 129

Table 4.3: Data Collection and the Response Rate Data

Proposed

Invited to Participate

Achieved

300

450

Focus Group

Interviews

Collection Survey

Response Rate

150

Achieved/ Proposed 50%

Achieved/ Invited 30%

100%

>100%

93%

Source: F. Tomos, 2016 (Based on the literature review)

Further, the qualitative data for this thesis was collected by using interviews and a Focus Group. Whilst for the survey, the response rate was 50%, for the FG and interviews the response rate was 100% (Table 4.3). However, the main purpose for the qualitative data was to provide rich and valuable information, and to help the interpretation of the results from the quantitative data analysis, as well as to answer the research questions of the thesis. Consequently, the sample for the interview was designed by the same sampling technique, probability sampling, selected randomly sample, from the participants in the survey. The author gathered 37 respondents, which, considering the indepth technique of interviewing is a large sample. The last qualitative method of data collection was the Focus Group with five women entrepreneurs, selected by means of the purposive sampling technique (Saunders, Lewis and Thornhill, 2012), from women entrepreneur participants in a networking event. In conclusion, the sampling technique used for the qualitative data collection was probability random simple heterogeneous for the interviews and purposive homogenous for the focus group. The author of the thesis in the Appendix B. provides additional relevant information.

This is a cross sectional,

retrospective-perspective study (Kumar, 2005). The study population for this research, is made by women entrepreneurs in South-East Wales, the UK.

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4.9 Questionnaires Design and Data Collection: Survey, Focus Group, Interviews 4.9.1 DATA COLLECTION AND PILOT STUDY In order to meet the requirements of this thesis, the researcher designed the Questionnaire in a manner that answers the hypotheses and ensured a direct link to the elements of the conceptual research framework.

To assure a comprehensive and rich volume of

information, the author used a wide range of questions: closed and open, ranked and multiple-choice questions, trying to avoid leading questions, and to limit the number of possible errors in the design of the questionnaire (Oppenheim, 1992). The Questionnaire was divided into five sections, as follows: section one contains background and demographic data, section two comprises data about learning, section three contains questions which gather information on Digital Platforms & ICTs, section four is designed to find information regarding women entrepreneursâ&#x20AC;&#x2122; participation within CoPs & networking, section five, is designed to collect information about WES and business growth. The questionnaire is semi-structured, in the sense that it includes both open and closed questions, as well as dichotomous questions with only two types of answer: Yes/No and True/False.

Additionally, the questionnaire is designed to collect

predominantly categorical data (numerical and ordinal), but it also includes scale measurements in order to gather interval data, by having four summative multiple items statements within the questionnaire (Connolly, 2007).

Because, this is mainly a

hypotheses testing research, the three instruments and data collection techniques were shaped in such a manner that the researcher was able to gather information and bring evidence to affirm and support the hypotheses.

Furthermore, whilst the Survey

Questionnaire is semi-structured, both the Interview and the Focus Group are also semistructured (Saunders, Lewis and Thornhill, 2012). Before starting the main collection of data, the researcher conducted a pilot study with five women entrepreneurs from South East Wales. Following the Pilot study and based on the outcome of the analysis, the researcher adapted, corrected questions two and nine in section A, and question two in section B of the questionnaire. Further, the researcher designed two more questions, questions 13 and 14 in section E, in view to enrich and to get a better insight into the way women entrepreneurs interpret and define the entrepreneurial success. The results of the Pilot Study indicated a predisposition of women entrepreneurs towards networking, a predominant blended type of learning style, and a high level of agreement regarding the importance of Learning and Digital Platforms 131

& ICTs for WES. The researcher when shaping the final version of the questionnaire considered the Feedback on the questionnaire (Appendix B). According to the participantsâ&#x20AC;&#x2122; feedback, the length of each questionnaire in the pilot study was between ten to fifteen minutes per respondent. The researcher ensured that the participant will have full and complete information (Appendix B) concerning the purpose, the objectives of the research, and assisted them whilst completing the questionnaires, by providing additional information, as well as allowing them respectfully to complete the questionnaires themselves, when required (Gravetter and Forzano, 2009). The data collection spread across three months (July to September 2015), in order to allow the researcher to travel in South East Wales, the UK, and gather the required information for the analysis and completion of this thesis. The statistics of the outcome of the data collection are included within the Appendices (Appendix B), together with the Questionnaires for the Survey, Interviews and Focus Group; Interviews and Focus Group Registration Forms; Statement of Informal Consent for the Focus Group and Research Consent Form with Data Protection Act, 1998, for the Interviews. Additionally, also in the Appendices (Appendix B), the researcher included a comprehensive information and invitation form, providing the participant with an insight regarding the purpose, the reason, the framework and the main concepts of this research. 4.9.2 CODING AND PROCESSING DATA In view to meet both the requirements of the latest version of software, and computerised statistics SPSS 22, and those of the research literature on data coding, processing and analysis (Oppenheim, 1992), the researcher created a complex Code Book (Appendix C) with a completed list of variables with the level of measurement, a variable allocation document, a coding frame, and the main coding book with five sections. The Coding Book contains information regarding the following three elements, displayed as three main headings: Description of variable, SPSS variable name and Coding Instructions (Oppenheim, 1992; Pallant, 2007). According to Oppenheim (1992) the coding process is a component part of the phase of data processing. Nevertheless, coding data is a very complex and responsible process, apart from the data processing, and therefore it could be consider also, as a separate process, which must be clearly defined before starting data processing. As an alternative, it could be also regarded as the first stage of data processing, due to the ongoing 132

adaptation and changing process of the coding book, whilst still processing the data. It is also crucial for the researcher to know and be confident about the main types of the processed variables, as these is essential for the statistics involved in this research (Connolly, 2007). Another important issue, with which the researcher was confronted just before the data analysing phase, consisted of data cleaning (Oppenheim, 1992). In this instance, the researcher searched for errors and found a few omissions, which in turn attracted further mistakes. The researcher, found these by using the coding book and comparing the actual processed scores and numbers, with the real scores and numbers, from the coding book. Particular importance was given to the inconsistencies in the answers following a filter question, such as question 10, section B and question one, section D of the questionnaire, and to the missing data, which could have attracted biases in the data analyses (Oppenheim, 1992). 4.10 Ethical Concerns Saunders, Lewis and Thornhill (2012) argued that ethics are principles and values that any researcher needs to respect when conducting a research. The main ethical issues for this study was (1) the obtaining of the respondentsâ&#x20AC;&#x2122; agreement (verbal or written) for participation in the survey, interviews and focus group, (2) the way data is stored, in view to ensure data protection and confidentiality, as well as (3) the anonymity for the participants (Saunders, Lewis and Thornhill, 2012). Furthermore, Saunders, Lewis and Thornhill (2012) highlighted the need for (4) the participants to be aware of the research topic, and (5) the right to give or not his/her informed consent (Lincoln, 2009). More issues raised by the research process are as follows: avoidance of causing mental stress, depriving respondents of their rights, and creating a trustworthy relationship (Saunders, Lewis and Thornhill, 2012; Lincoln, 2009; Kitchener and Kitchener, 2009). Punch (2009) underlined the need of planning for the ethical issues, as well as the necessity of establishing principles such as: honesty and trust, integrity and equality, respecting standards (British Educational Research Association, 2004, cited in: Punch, 2009, p. 49). In addition to the above concerns, the author created the questionnaire of this thesis, based on the literature review, in combination with three other questionnaires designed by Professor Buckley (2011), Dr Grosch (2011) and Tomos et al. (2011). The author of this thesis collaborated on two distinct international research projects with the 133

above authors and wished to make a link between the previous research on new emerging technologies and communities of practice and the research topic of this thesis. In order to agree with the ethical standards, the author of the thesis required the written consents, for using these questionnaires, and attached to the thesis. 4.11 Summary of Chapter 4 This chapter introduced the research problem and philosophy, researcherâ&#x20AC;&#x2122;s philosophical perspective, research purpose, approach and design, research methodology, methods, sampling techniques, samples, data collection and ethical concerns. The next section introduces data analysis, particularly, the first part of the statistical analysis, which is the quantitative data analysis, based on the survey with questionnaires.

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Figure 4.5: Research Design Phases RESEARCH DESIGN PHASES

Phase 1: Literature Review Conceptual Research Framework Research Aim & Objectives Research Hypotheses Research Variables

Phase 2: Research Instruments Design: -Questionnaires Design for Survey, Interviews and Focus Group; Online Survey with Questionnaire (England & Wales); Piloting the study & correcting; Fieldwork: Face-to-Face Survey with Questionnaires, Interviews and Focus Group in South Wales, UK; Data Collection: Survey, Interviews, Focus Group.

Phase 3: Survey: Data Coding, Processing &Analysing quantitative data; Focus Group and Interviews: Transcription, Coding & Analysing qualitative data; Multi methods & Mixed Methods.

Phase 4: Analysis & Interpretation Complementarity Writing about Findings & Discussions Data Management & Storage Validity & Reliability Conclusions Contributions Recommendations

Source: ÂŠ 2017, 2019 Florica Tomos

135

CHAPTER FIVE: QUANTITATIVE DATA ANALYSIS Figure 5.1: Chapter Five CHAPTER FIVE DATA ANALYSIS

QUANTITATIVE DATA ANALYSIS

Source: F. Tomos 2016

5.1 Introduction to Quantitative Data Analysis This chapter (Figure 5.2) has the following sections (1) descriptive statistics, (2) correlation analysis, (3) regression analysis and (4) factor analysis. The chapter provides the rationale for choosing these methods of quantitative data analysis. First, the chapter introduces the descriptive statistics of 150 women entrepreneurs who participated in the survey with questionnaires. This is essential, because it offers a comprehensive holistic view of the categorical and scale data. Secondly, the correlation analysis employs statistics, which are able to test the directional relationships between the independent variables: learning and digital platforms & ICT and the dependent variable: women entrepreneursâ&#x20AC;&#x2122; success (WES) from hypothesis two and hypothesis three. Thirdly, the regression analysis provides statistics to analyse the multivariate relationship in hypothesis one. Finally, the factor analysis method provides statistics, which analyse the correlation between the three variables of the research in hypothesis four. Furthermore, the outcomes of the statistics are presented within each section with basic comments and interpretations. These techniques are invaluable tools that help the researcher to summarise and present the findings in a meaningful way, in view to answer the research questions, to test the hypotheses and yield relevant interpretations (Oppenheim, 1992).

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Figure 5.2: The Structure of Chapter 5 CHAPTER 5 QUANTITATIVE DATA ANALYSIS

DESCRIPTIVE STATISTICS

INFERENTIAL STATISTICS

CATEGORICAL VARIABLES SCALE VARIABLES

-LEARNING PREFERENCES -STYLES OF LEARNING -PARTICIPATION IN CoPs -IMPACT OF VARIOUS FACTORS ON BUSINESS SUCCESS

RELIABILITY AND VALIDITY

SIGNIFICANCE TEST

ANALYSIS OF RELATIONSHIPS BETWEEN VARIABLES

HYPOTHESES TESTING

ANALYSIS OF RELATIONSHIP BETWEEN CATEGORICAL VARIABLES EXPLORATORY RESEARCH ANALYSIS OF RELATIONSHIP BETWEEN SCALE VARIABLES PARTIAL CORRELATIONS ANALYSIS

-LEARNING -DIGITAL PLATFORMS & ICTs -CoPs & NETWORKING -WOMEN ENTREPRENEURSâ&#x20AC;&#x2122; SUCCESS

FACTOR ANALYSIS

CORRELATION AND REGRESSION

-MULTIPLE STANDARD REGRESSION ANALYSIS -CORRELATION ANALYSIS -PARTIAL CORRELATION ANALYSIS

TOTAL FACTOR EXTRACTION

Source: F. Tomos 2016 (Based on the literature review)

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5.2 Descriptive Statistics According to Voelkl and Gerber (1999, p. 27) statistical data sets are ‘collections of values of one or more variables’, and variables such as ‘words’ or ‘numbers’ are defined as categorical or numerical. The numerical variables at their turn can be either discrete or continuous. As an enhancement to their expert opinion, Connolly (2007) splits the variables into three categories: nominal, ordinal and scale (ratio and interval). The first two types of variables are named categorical, and are sub-categories with numbers assigned to them in view to originate a dataset (Connolly, 2007). There are divided opinions (Voelkl and Gerber, 1999; Connolly, 2007; Yockey, 2008), with regard to how data should be displayed and summarized, in order to achieve a comprehensive interpretation, and to answer the research questions. There are also, various technical procedures and mechanics in applying relevant statistics for data analysis (Foster, 2001; Pallant, 2007; Pallant, 2013; Argyrous, 2011). This study regards as appropriate ways of displaying data for categorical variables (nominal and ordinal), the frequency tables (Connolly, 2007, p. 66). According to the sub-category type of variables, for summarizing data, the research employs either percentages (nominal variables) or cumulative percentages (ordinal variables) (Connolly, 2007, p. 66; Pallant, 2013). With regard to scale variables, the study choses histogram (boxplot) for graphical representation and displaying the data, followed by statistics such as mean and standard deviation (if data normally distributed) or median and interquartile range (if data is not normally distributed) (Connolly, 2007). In the subsequent lines, this section endeavours to present a general and comprehensive view of categorical variables. 5.2.1 Displaying and Summarizing Categorical Variables In the next lines the author examines the main categorical variables (nominal and ordinal), (Figure 5.3 – Figure 5.8) and explains and interprets the results of the analysis in a meaningful manner, according to their relation to the research questions of the thesis. 5.2.1.1 DEMOGRAPHIC DATA Section A of the questionnaire contains answers regarding the demographic and background information. The analysis starts with the nominal variables and is followed by the analysis of the ordinal variables from section A. Thus, with regard to the legal form of the entrepreneurs involved in the survey, the output from the frequency table 138

showed 150 valid cases with no missing cases. According to the descriptive statistics (Appendix A2), out of 150 women entrepreneurs about 53.3% were sole traders, and 12.7% were family business (Appendix A2, T1A). Further, 72.7% (valid percent) of them were single owner, whilst 8.7% were partnership wife/husband (Appendix A2, T1B). Their predominant current position in the business was 60% as owner and 22% owner/director. The main sectors of the business, as indicated by the analysis, was 54% whole sales and retails, followed by 27.3% services, accommodation, cafes and restaurants (Appendix A2, T1H). The main types of business were 40.7% retails, 12.7% beauty and hairdressing, 8.7% catering and hotels and 5.3% arts and crafts (Appendix A2, T1G). What is really essential and it is good to be highlighted is the fact that 10.7% of the valid cases represented multiple businesses, meaning that about 16 women entrepreneurs were owners of more than one business.

In order to enhance the

presentation, the research presents below a few graphical representations (Figure 5.3 Figure 5.8). Figure 5.3: Legal form & Type of business

139

Source: F. Tomos, 2016 (SPSS)

There is also a trend toward the development of online businesses (national and international) showed by a cumulative valid percent of 9.3% (Figure 5.4):

Figure 5.4: Market area of the business

Source: F. Tomos, 2016 (SPSS)

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Considering that 27.3% represented partnerships, it is also essential to know that 74% were female only, and 18.7% male and female, discovering thus, a trend toward mixed gender collaboration, and husband and wife partnership. Whilst it was expected for the majority of the respondents to be Welsh, the analysis indicated indeed that 58.7% were Welsh women entrepreneurs, 23.3% English women entrepreneurs, whilst 5.3% belonged to ‘others’ category. Additionally, the ethnicity demonstrated that a high percent such as 68% of the valid cases (150) represented white British and 18.7% were white Welsh or English ethnicity. About 78% of the valid cases (149) responded ‘yes’ they had business management experience before starting their businesses, 29.5% had experience as a leader, 50.7% had entrepreneurship experience, and 38.9% of 149 had experience within the sector (Appendix A2, Table 2B, Table 2C, Table 2E). Whilst the nominal variables were analysed by means of the statistics table, frequency tables and valid percentages, the ordinal variables are explained by using statistics tables and mainly, the cumulative percentages from the frequency tables. The following are the ordinal variables: current size firm, year of creation, firm age, the age of the owner, years of ownership and the current annual sales/turnover. The current firm size (by number of employees) stays the same as at the creation of business. The analysis showed that 95.3% of the valid cases are small businesses with 0-9 employees and only 0.7% of them have 50-249 employees (Appendix A2, Table 1C). The majority of businesses in the sample, for instance 78.7% were created after 2000 and only 19.3% of the valid cases were created between 1971 and 2000 (Appendix A2, Table 1E).

For almost a third of them (35.3%)

the firm age was less than three years and only 19.3% have a firm age of 20 years or more. A cumulative valid percent indicated that for 67.3% of the cases the firm age was less than ten years. These results demonstrated that the majority of businesses in the sample under analysis were young firms. Besides these, 34.6% of the owners under survey belong to the age group from 18 to 40 y. o., whilst a cumulative percent of 52.7% of the owners were aged 41 to 61 or over (Appendix A2, T1D). Finally, a valid percent of 54.7% for the group of ‘0 to 5’ years of ownership, compared to 15.3% for the group ‘more than 20’ years of ownership. Also, very important is the annual turnover/sales figure, which for the majority of businesses (62%) is quite low. Thus, 62% of the valid cases (149 enterprises) had an annual sales/turnover figure of less than 100,000. Furthermore, only 15% of the small businesses showed an annual sales figure between

141

100,000 to 500,000. This could indicate that the success of a small business it is not specifically placed upon the increase in annual sales. 5.2.1.2 LEARNING Section B of the questionnaire comprises information regarding the entrepreneursâ&#x20AC;&#x2122; educational background, entrepreneurship training courses, entrepreneurship skills and competences, business learning needs, business knowledge, the role of networking, learning preferences and learning satisfaction. In addition to these, the survey endeavours to gather enough information to design a comprehensive definition of the following two terms: womenâ&#x20AC;&#x2122;s entrepreneurship and women entrepreneurs. According to the first categorical variable, educational background, 20.7% of the valid cases had an A level or College qualification and 40% of the entrepreneurs were graduate or postgraduate. Out of 150 women entrepreneurs 42.7% of them undertook management studies or various studies, related to the profile of their businesses (Appendix A2, Table 2A). Furthermore, 32% undertook entrepreneurship studies before starting the business, compared to 42% of the valid cases, which undertook these studies after starting the businesses (Figure 5.5; Appendix A2, Table 2E, Table 2F). This fact could very well demonstrate the women entrepreneursâ&#x20AC;&#x2122; interest in entrepreneurial learning and its role for WES. Figure 5.5: Entrepreneurship courses after starting the business

Source: F. Tomos, 2016 (SPSS)

Furthermore, a high percent such as 64.7% of the valid cases (150), illustrated that women entrepreneurs had multiple entrepreneurial competences and skills: management, sales, negotiation, marketing, promotion, accounting, facebook, etc. A good percent (20%) of 142

women entrepreneurs, indicated to be experience-based learners, whilst the majority (52.7%) selected multiple answers (experience-based learner, role-model based learner, doing/asking/applying learner) (Figure 5.6). Figure 5.6: Type of learner

Source: F. Tomos, 2016 (SPSS)

However, 15.5% of them (valid cases) indicated their learning needs for digital platforms and 16.9% for marketing, sales and promotion.

88% of the valid cases (women

entrepreneurs) saw themselves as interactive learners, whilst 50.7% (of 150) indicated that they were networking learners. Moreover, 72% of 150 confirmed that they acquired business knowledge after starting their businesses. Out of 150 women entrepreneurs, 74% affirmed that they used networking and 42% learned and acquired information by networking for business and for social purposes. 72.5% of the valid cases (149) answered ‘yes’ they learn from information, communication and sharing (Appendix 2A, Table 3B) when networking, and 88.6% of 149 valid cases affirmed that they use digital platforms & ICTs for learning (Twitter – 55.3%) and wireless connection (86.7%) for learning (Appendix A2, T3D). Women Entrepreneurs confirmed (74%) their usage of networking for learning, and the fact that, they were networking (50.7%) and interactive (88%) learners (Appendix A2, Table 2G, Table 2H, and Table 3A). A complete achievement was to gather enough information to shape two new definitions for the following terms: women entrepreneurs and women entrepreneurship. About 10% of the 143 valid cases, depicted women entrepreneurship as an ‘independent, innovative and creative process’, whilst 9.8% defined this as a ‘multitasking and hardworking

143

process’. Others, such as a percent of 6.3% of 143, said that women’s entrepreneurship is a process of ‘developing the businesses and seeking for opportunities’. 5.2.1.3 DIGITAL PLATFORMS & ICTs (NET & ICTs) The next section of the questionnaire, section C is provides information on the agreement of respondents with regard to their styles of learning with digital platforms & ICTs and their role for learning and doing business, respondents’ satisfaction with Digital platforms & ICTs for learning and business. Thus, 46.7% of the valid cases (150) used You Tube for learning, 75% of 150 used Facebook for learning, 75.3% of 150 used mobile phones for learning and 92% and 86.7% of 150 used internet connection at home, respective wireless connection for learning.

About 88% of 150 women entrepreneurs responded

‘yes’ they use Digital Platforms & ICTs (Appendix A2, Table 4A). The answers to Question three, demonstrated that 92.7% of 150 use mobile phones for business, 91.3% of 150 use mobile internet for business, 72.7% of 150 women entrepreneurs use mobile applications for business, 78.7% of 150 use Facebook for business, 90% use Google search for business and 96.7% of 150 use internet at home for business (Appendix A2, Table 4B, Table 4C, Table 4D, Table 4E, Table 4F, Table 4G). Additionally, 62.7% of 150 used Twitter for business and 50.7% of 150 used You Tube for business. These results demonstrated the role of Digital Platforms & ICTs for both entrepreneurial learning and businesses. 5.2.1.4 COMMUNITIES OF PRACTICE (CoPs & networking) The following section discusses is section D which provides information regarding the participation of women entrepreneurs in various groups, networks and business or professional associations, in other words, within Communities of Practices (CoPs). In addition, the section gathers information about the role and importance of digital platforms for women entrepreneurs’ participation within these associations. For instance, 66.7% of 149 valid cases affirmed that they belong to CoPs, 32.2% belong to business associations, 22.8% belong to professional associations and 51.3% are part of various networking groups (Appendix A2, Table 5D, Table 5E). According to this analysis, 57.3% of 150 valid cases choose to participate within CoPs by either face-to-face and online or online only (Figure 5.7). Out of 150 valid cases, 68.7% affirmed that the digital platforms & ICTs helped them to participate within communities of practice (Appendix A2, Table 5A). 68.7% of 150 said ‘yes’ the laptops and computers helped them to 144

participate in CoPs. About 64.7% affirmed that mobile phones helped to participate in CoPs (Appendix A2, T5F) and 55.3% confirmed that iPad and tablets help participation in CoPs (Appendix A2, T5G). Further, 27.9% of 147 valid cases belong to miscellaneous groups. About 6.1% of 147 are members of the Small Business Federation. Circa 69.3% of 150 Women Entrepreneurs were located on the High Streets in SE Wales, and only 5.7% belonged to High Street Traders (Appendix B, Table 2). About 6.8% of 147 belonged to various online groups, and 3.4% of 147 were part of the Market Association. Only 0.7% of 147 valid cases were members of the Chambers of Commerce and 6.8% of 147 belonged to various professional associations. Figure 5.7: Participation in Communities of Practice

Source: F. Tomos, 2016 (SPSS)

5.2.1.5 WOMEN ENTREPRENEURS’ SUCCESS (WES) The last section E, presents financial and non-financial measures of success, determinants of business growth and success, expresses agreements regarding the main factors for business success, defines the entrepreneurial success, indicates the recent entrepreneurial learning for women entrepreneurs and expresses recommendations regarding Learning and its role in achieving entrepreneurial success. The data analysis and the results from the frequency tables showed that 77.2% of 149 valid cases had an increase in sales in the last five years. About 36.2% of 149 valid cases described the increase in sales as a financial measure for business success and 34.2% described the increase in profit as the main financial measure for business WES. About 90.6% of 149 valid cases selected ‘multiple answers’ as non-financial measures for WES. Further, 69.3% of 149 replied 145

that entrepreneurial learning enhances WES (Figure 5.8; Appendix A2, Table 6A), due to the increase in confidence and the enhancement of knowledge and information (37.7%). Figure 5.8: EED/Learning enhances business success

Source: F. Tomos, 2016 (SPSS)

Moreover, 90% of 150 cases replied that Digital Platforms & ICTs increases WES (Appendix A2, Table 5H). About 12.6% of 142 valid cases defined WES as ‘being independent and financially stabled’; 12.7% of 142 described the success as equal to ‘customer satisfaction’ and 4.2% of 142 depicted success as ‘work satisfaction and life balance’. About 52% of 148 valid cases selected ‘multiple types of learning’ (traditional, online and blended learning). Finally, the frequency table showed that 55% of 149 valid cases chose multiple answers as ‘recommendations for others’, in order to achieve success: continue to learn, learn from experience, network, undertake more learning. The last two variables were added to the research because of participants’ feedback on the pilot study.

The analysis showed that 98% of 150 respondents enjoyed being

entrepreneurs and the reason for this was mainly, having freedom and financial independence (40.4%).

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5.2.2 Displaying and Summarizing Scale Variables Graphical display and numerical summaries, produced by SPSS, measure the variation (the spread out of data/the differences within the data) and the location of the data in a particular dataset (Voelkl and Gerber, 1999; Connolly, 2007). Thus, the variability in the sample can be demonstrated either numerically by calculating the range, mean deviation, standard deviation and standard scores (z-scores), or graphically, by using the box-andwhisker plots (Voelkl and Gerber, 1999). In view to display and summarise the variables, this research used means, standard deviations, percentages, bar and pie graphs and boxplots.

Following the summary guide, provided by Connolly (2007, p. 67), the

researcher used SPSS (Connolly, 2007; Yockey, 2008; Pallant, 2013), for the graphical representations of the following scale variables: (1) Learning preferences four item scale, (2) Styles of learning and doing business six item scale, (3) Communities of Practice seven item scale, and (4) Impacts of various factors on business success nine items scale. Although, there are various opinions (Voelkl and Gerber, 1999; Foster, 2001; Howitt and Cramer, 1999; Bryman and Cramer, 2009) regarding graphical representation and data analysis, this study considered Connolly’s (2007) approach to displaying and summarizing data. The rationale for selecting this perspective is the consequence of an accurate critical view and logical interpretation of various methods of displaying and summarizing data. Additionally, Connolly (2007) offered a very well structured guidance and clear explanations for creating such alternatives of exploring and presenting data in various ways. Nevertheless, in order to have a comprehensive and unbiased interpretation and select the right methods, the author of the thesis, combined Connolly’s perspective (2007) with other views, and used mechanics supplied by Pallant (2013), and Argyrous (2011). Section B (Question 14), Scale Variable ‘Learning Preferences’ Statistical techniques with SPSS (Pallant, 2013), allowed the researcher to have a graphical representation for the first scale, entitled ‘Learning preferences’ with its four items: flexible informal learning, flexible formal learning, experienced-based learning and role model-based learning. A thorough analysis, of these four histograms together with the provided means values and standard deviations for each sample size, led the researcher to the conclusion that data on the histograms is normally distributed. Consequently, the best statistics to summarize the data were the mean and standard 147

deviation (Connolly, 2007). Below, are the descriptive statistics table (Table 5.1) and histograms (Figure 5.9 – 5.12) related to the first scale: ‘learning preferences’. The averages showed that experience-based learning and flexible informal learning were the most selected styles of learning preferred by women entrepreneurs from the sample. The standard deviation showed that the answers of participants spread from ‘Neither’ to ‘Strongly Agree’. Although, the distribution is not perfect, as a result of the shape of this scale variable, it is clear that the best statistics to summarize the data will be the mean and standard deviation (Connolly, 2007).

Standard deviation values helped in

establishing the shape by knowing how far the data is distributed from the mean value (Connolly, 2007). According to Bryman and Cramer (2009) the graph shows a normal distribution or bell-shaped curve (Figure 4.9 – Figure 4.12), where all the cases are gathered beneath the curve with 50% on either side of the arithmetic mean. Table 5.1: Scale Variable ‘Learning Preferences’ Experience-based learning Flexible informal learning Role model-based learning Flexible formal learning

N 149 149 149 149

Source: F. Tomos, 2016 (SPSS)

Figure 5.9: Flexible formal learning

Source: F. Tomos, 2016 (SPSS)

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Mean 3.17 2.80 2.53 2.21

Std. Deviation .651 .830 1.118 1.204

Figure 5.10: Flexible informal learning

Source: F. Tomos, 2016 (SPSS)

Figure 5.11: Experience-based learning

Source: F. Tomos, 2016 (SPSS)

Figure 5.12: Role model-based learning

Source: F. Tomos, 2016 (SPSS)

149

Section C (Question 1), Scale Variable ‘Styles of learning and doing business’ The analysis of the histograms for the second scale variable (Figure 4.13 – 4.18): ‘Styles of learning and doing businesses indicated that the data is normally distributed. Therefore, the study used again statistics such as means and standard deviations. The study explores the shapes the histograms and how far from the mean, the data is distributed. The means vary from 3.03 the highest to 1.11 the lowest (Table 5.2). The highest mean value corresponds to ‘Doing business with ICTs’ and ‘Often’ on the scale. The lowest mean value corresponds to ‘Attending courses’ and to ‘Disagree’ on the scale. The standard deviation ranges from 1.080 to 1.472 and corresponds to the interval 1.95 to 4.11, equivalent to ‘Neither to Strongly Agree’ on the scale. Consequently, ‘learning with ICTs’ and ‘doing business with ICTs’ were the most selected by women entrepreneurs. Table 5.2: Scale Variable ‘Styles of learning and doing businesses – Descriptive Statistics N

Mean

Std. Deviation

Doing business with ICTs

150

3.03

1.080

Learning with ICTs

150

2.63

1.271

Learning yourself at home

150

2.58

1.244

Learning online

150

1.85

1.472

Learning in groups

150

1.32

1.372

Attending courses

150

1.11

1.245

Source: F. Tomos, 2016 (SPSS)

Figure 5.13: Attending courses

Source: F. Tomos, 2016 (SPSS)

150

Figure 5.14: Learning yourself at home

Source: F. Tomos, 2016 (SPSS)

Figure 5.15: Learning in groups

Source: F. Tomos, 2016 (SPSS)

Figure 5.16: Learning online

Source: F. Tomos, 2016 (SPSS)

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Figure 5.17: Learning with ICTs

Source: F. Tomos, 2016 (SPSS)

Figure 5.18: Doing Business with ICTs

Source: F. Tomos, 2016 (SPSS)

Section D (Question 4), Scale variable ‘Communities of Practice’ The next scale variable presented in this section is ‘Communities of Practice’, a seven item scale. From the analysis of the bell-shape curve designed around the Histograms, it can be assumed that the data is normally distributed, which leads us to the conclusion that this scale variable can be described by two summary statistics: the mean and the standard deviation. Additional graphic representation (Figure 5.19 – 5.26) and the table for Kolmogorov-Smirnov and Shapiro-Wilk tests (Table 5.4), confirm that data is normally distributed and the results are significant. Further, the study presents below the main descriptive statistics (Table 5.3) and the histograms. The mean values for this variable varied between 1.65 to 1.80, which is almost the same across the scale and 152

corresponds to ‘Agree’. The participants scored almost similarly on this variable, which confirms the women entrepreneurs’ agreement that CoPs are a means of information, learning, knowledge, encouragement, and success. Table 5.3: Scale variable ‘Communities of Practice’ Participation in CoPs increases knowledge In CoPs I find information to grow the business CoPs facilitates learning from experts In CoPs I share knowledge Through CoPs I am encouraged to succeed CoPs are important for business success CoPs give me a sense of identity

Mean

Std. Deviation

150 149 150 150 150 149 150

1.80 1.74 1.73 1.72 1.71 1.69 1.65

.724 .711 .682 .687 .727 .697 .734

Source: F. Tomos, 2016 (SPSS)

Figure 5.19: Boxplot ‘Participation in Communities of Practice

Source: F. Tomos, 2016 (SPSS)

Figure 5.20: Participation in CoPs increases knowledge & Normal Q-Q Plot

153

Source: F. Tomos, 2016 (SPSS)

Figure 5.21: Participation in CoPs facilitates learning from experts & Normal Q-Q Plot

Source: F. Tomos, 2016 (SPSS)

154

Figure 5.22: In CoPs I find information to grow my business & Normal Q-Q Plot

Source: F. Tomos, 2016 (SPSS)

Figure 5.23: In CoPs I share knowledge & Normal Q-Q Plot

155

Source: F. Tomos, 2016 (SPSS)

Figure 5.24: Through CoPs I am encouraged to succeed & Normal Q-Q Plot

Source: F. Tomos, 2016 (SPSS)

156

Figure 5.25: CoPs give me a sense of identity & Normal Q-Q Plot

Source: F. Tomos, 2016 (SPSS)

Figure 5.26: CoPs are important for business success & Normal Q-Q Plot

157

Source: F. Tomos, 2016 (SPSS)

Table 5.4: Test of Normality Kolmogorov-Smirnova Statistic df Sig. Participation in CoP increases knowledge CoPs facilitates learning from experts In CoPs I find information to grow the business In CoPs I share knowledge Through CoPs I am encouraged to succeed CoPs give me a sense of identity CoPs are important for business success

Statistic

Shapiro-Wilk df

Sig.

.269

149

.000

.826

149

.000

.279

149

.000

.802

149

.000

.254

149

.000

.821

149

.000

.273

149

.000

.814

149

.000

.261

149

.000

.828

149

.000

.260

149

.000

.841

149

.000

.269

149

.000

.821

149

.000

a. Lilliefors Significance Correction Source: F. Tomos, 2016 (SPSS)

Section E (Question 5), Scale variable ‘Impact of various factors on business success’ The last scale variable presented in this section is ‘Impact of various factors on business success’ a nine item scale. The statistics showed average values ranging between 4.30 the highest to 2.97 the lowest. A mean value of 4.30 indicated a high level of agreement with a particular statement (Table 5.5). Thus, there is a high agreement regarding the impact of the internet, laptops/computers, mobile phones and Digital Platforms on business success. The table also showed an average agreement of the impact of Learning on WES. Below, the thesis presents the histograms and the table with the statistics. Additionally, in order to enhance, and to confirm, the results of this analysis, the author 158

presented a second graphical representation, a boxplot (Figure 5.27 – 5.30) presentation for two items only, which are significant for the analysis: Learning (EED) and Digital Platforms. Table 5.5: Scale variable ‘Impact of various factors on business success’- Descriptive Statistics Internet Laptops/Computers Mobile Phones Digital Platforms Tablets Facebook Networking and CoPs EED (Learning) Twitter Source: F. Tomos, 2016 (SPSS)

Figure 5.27: Box Plot – Learning (EED)

Source: F. Tomos, 2016 (SPSS)

Figure 5.28: Box Plot – Digital Platforms

Source: F. Tomos, 2016 (SPSS)

159

Mean

Std. Deviation

149 149 149 149 149 149 149 149 149

4.30 4.25 4.15 4.08 3.63 3.59 3.49 3.36 2.97

1.089 1.174 1.234 1.142 1.526 1.461 1.308 1.296 1.526

Figure 5.29: Learning (EED)

Source: F. Tomos, 2016 (SPSS)

Figure 5.30: Digital Platforms & ICTs (NET & ICTs)

Source: F. Tomos, 2016 (SPSS)

The box-and whiskers plot displays the median, interquartile range and the extremes values of the dataset. The median of the distribution, is given by the horizontal line in the middle of the box, whilst the minimum and maximum values are indicated by the ends of the whiskers (Voelkl and Gerber, 1999). Both of them confirm the values from the table (Table 5.5). The next part of this chapter introduces the inferential statistics. 5.3 Inferential Statistics: Reliability and Validity in Measurement Validity and reliability in measurements are important issues, in the sense that every research is confronted with such problems. Moreover, they determine the quality of the research. There are various opinions on reliability and validity of the measurements. Some authors (Punch, 2009; Ghauri and GrĂ¸nhaug, 2005) define reliability as consistency and stability of the measure, whilst the validity deals more with the conformity to the 160

theoretical requirements. Furthermore, Punch (2009) explains that, the internal reliability shows whether the variables work in the same directions, whilst the internal validity is calculated with Coefficient Alpha and can indicate the quality of the research. This thesis used four Likert scales, which are mainly summative scales with multiple statements measuring (1) learning preferences, (2) agreements with styles of learning, (3) participation in CoPs and (4) the impact of a range of factors on business success. In order to create a score for every woman entrepreneur participant in the survey, the scores for each respondent, corresponding to each statement within the particular scale, are added together to give an overall rating score within a certain range of scores (Connolly, 2007). In this research, reliability refers to the consistency of the scores within the same scale. Nevertheless, reliability could be defined as the consistency or repeatability of scores on a particular scale (Yockey, 2008). This thesis employs the reliability based on a single administration of the scale, which is assessed by means of Coefficient alpha or Cronbachâ&#x20AC;&#x2122;s alpha (Yockey, 2008). Connolly (2007) suggests that validity is about the assurance that a certain variable measures something that it is supposed to measure. Despite this definition, it seems that both reliability and validity of a measurement could be perfectly assessed by calculating Coefficient Alpha. This research uses Coefficient Alpha to estimate the reliability of four scales and as a result, the validity, or the quality of this research. In other words, there is an assessment of the internal consistency of the participantsâ&#x20AC;&#x2122; responses for the following measures: (1) learning preferences scale consisting of four-items or variables; (2) styles of learning six-item scale; (3) participation in CoPs seven-item scale; and (4) the impact of various factors on business success, nine-items/variables scale (Table 5.6). Consequently, the values of Cronbach's Alpha can indicate also the internal validity of the scales (Punch, 2009). For the procedure of checking the reliability of the scales, this research applies mechanics by Pallant (2013). The output generated from the analysis is presented in the table (Table 5.7) and is discussed in the sections below.

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Table 5.6 Scales Scale Learning Preferences 4-item scale

Items -Flexible formal learning -Flexible informal learning -Experience-based learning -Role model-based learning

Abbreviation LP

Number of Items 4

Styles of learning and doing business with ICTs 6-item scale

-Attending courses -Learning yourself at home -Learning in groups -Learning online -Learning with ICTs -Doing business with ICTs

Participation in CoPs 7-item scale

-Participation in CoPs increases knowledge -CoPs facilitates learning from experts -In CoPs I find information to grow the business -In CoPs I share knowledge -Through CoPs I am encouraged to succeed -CoPs give me a sense of identity -CoPs are important for business success

PCoP

The impact of various factors on business success 9-item scale

-Learning -Digital Platforms -CoPs & networking -Twitter -Facebook -Internet -Laptops/Computers -Mobile Phones -Tablets

IVF

Source: F. Tomos, 2017, SPSS

Table 5.7 Reliability Table Statistics N valid cases Cronbach’s Alpha Number of Items Item Mean/ Highest Value Item name/ Highest Value Scale Mean Range Scale Standard Deviation Reliability

Section B/ Scale LP 149 0.617

Section C/ Scale SL 150 0.704

Section D/ Scale PCoP 149 0.946

Section E/ Scale IFV 149 0.857

4 3.17

6 3.03

7 1.80

9 4.30

Experience-based learning

Doing business with ICTs

Internet

10.70 ‘0 to 16’ 2.67

12.53 ‘0 to 24’ 4.92

Participation in CoPs increases knowledge 12.09 ‘0 to 21’ 4.28

33.83 ’9 to 45’ 8.01

Marginal

Fair value

Excellent

Good

Source: F. Tomos, 2017 (SPSS)

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a. Section B (Question 14) ‘Learning preferences scale’ four-item measure For the first scale, there was a sample with 150 participants and 149 valid cases included for the analysis. The table (Table 5.7) displays a coefficient alpha of 0.617 which is acceptable. According to Yockey (2008) this is a marginal value, indicating a marginal degree of internal consistency between the items of this scale. The table (Table 5.7) is providing us with the information that the third item had the highest mean rating on the items of the scale, equal to 3.17. This value corresponds to a response of ‘Agree’ on the scale, for the variable ‘experience-based learning preference’. This variable is followed by two more items: ‘flexible informal learning’ with 2.80 and ‘role model-based learning’ with 2.53. The Scale Mean of 10.70 which is within the range of ‘0 to 16’ and the standard deviation of 2.67 demonstrated that on this first scale, the participants rated ‘marginal’ which is interpreted as a marginal internal consistency for the responses of the participants in the survey on this particular scale of measurement (Yockey, 2008). b. Section C (Question 1) ‘Styles of learning and doing business with ICTs’ sixitem scale The second scale indicates a sample of 150 participants with 150 valid cases included in the analysis. Further, the table (Table 5.7) shows a Cronbach’s alpha of 0.707 is a fair value. The coefficient alpha indicates a fair degree of internal consistency between the items of the scale. Items sixth, fifth and second had the highest mean rating with an average of response of 2.74, which correspond to a response of ‘often’. In other words, doing business with ICTs, learning with ICT and learning yourself at home happened ‘often’. This is followed by the fifth item ‘learning with ICT’, with a high value of mean of 2.63 and a low standard deviation of 1.271. The Reliability table (Table 5.7) showed a mean of the six-item scale of 12.53 (overall score ranging from 0 to 24). In conclusion, on the scale, the participants rated ‘fairly good’ for learning and doing business with ICT. c. Section D (Question 4) ‘Participation in CoPs’ seven item scale The Reliability table (Table 5.7) presents a sample of 150 participants with only 149 valid cases. The participants had completed data on seven variables. The Reliability Table (Table 5.7) displays values of Cronbach’s alpha for seven-item scale. The value of Coefficient alpha for the scale is 0.946, which indicates a very high degree of internal consistency among the items of this scale. The highest mean rating with an average of 163

response of 1.80, which corresponds to a response of ‘Agree’ on the scale, is the first item: ‘Participation in CoPs increases knowledge’. Thus, the second item ‘participation in CoPs facilitates learning from experts’ demonstrated less variability from the mean of 1.80 which corresponds to a response of ‘Agree’. The mean of the seven-item scale was 12.09, where the total score ranged from 0 to 21, with a standard deviation of 4.2. As a result, on this scale the participants rated ‘excellent’ for the ‘Participation in CoPs’. d. Section E (Question 5) ‘The impact of various factors on business success’ nine item scale The overall score ranges from 9 to 45. The Reliability Table (Table 5.7) indicates 150 participants and 149 valid cases. The Cronbach’s alpha for this scale has a value of 0.852, which according to Yockey (2008) depicts a ‘good’ degree of internal consistency between the items of this scale. The participants had the highest mean rating on the sixth item of the scale (Internet), the seventh item (Laptops/computers), the eighth item (Mobile Phones) and the second item (digital platforms/ NET). An average mean rating was placed on the ninth item (tablets), fifth item (Facebook) and the third item (Networks and CoPs). The most variable items with the standard deviation of 1.526 were two items: the ninth (Tablets) and the fourth (Twitter) items. The less variable with standard deviation of 1.089 was the sixth item (Internet). The mean of the nine-item scale was 33.83 with a standard deviation of 8.013. Therefore, on this scale the participants in the research rated ‘good’ on the ‘impact of various factors on business success’.

conclusion and based on the above results, it can be said that these measurements are able to provide and assure accurate results (Punch, 2009). 5.4 The Analysis of Relationships between Categorical Variables and the Role of Significance Test In view to start quantitative data analysis, according to the purpose of this research, and in order to have accurate results, it is crucial to know how to examine the relationships between different types of variables used within this study (Connolly, 2007). Although, there are various opinions which are also considered (Howitt and Cramer, 1999; Foster, 2001; Yockey, 2008) in this regard, this research emphasises perspectives such as those offered by Connolly (2007), Voelkl and Gerber (1999), Argyrous (2011) and Pallant (2013). Thus, Connolly (2007, pp.111, 177) in a summary guide, provided a wellstructured alternative to the analysis of the relationships between the variables of a 164

research.

The final aim of this research is to expand the findings from the designed

sample to the wider population of women entrepreneurs in Wales, the UK. As mentioned in the previous section, the author analysed the reliability and validity of the main types of measurements employed by the study. Further, the study endeavours to address concerns such as systematic and non-systematic bias of data.

Nonetheless, various biases could be the result of group under-

representation, incorrect sampling procedures or just sampling errors (Connolly, 2007). Moreover, the final findings might be unrepresentative of the entire women entrepreneur population in South-East Wales, or could just have occurred by chance. Therefore, this research reports the ‘margin of error’ and explores whether the findings occurred by chance (Connolly, 2007). Thus, the research introduces the concept of ‘statistical significance’. However, besides the ‘statistical significance’ concept, there is another concept, also important, ‘the confidence interval’ that could be expressed as a percentage. The focus of this research is mainly on the role of statistical significance. According to Connolly (2007) the statistical test calculates, by means of SPSS, the significance level of the relationship between two variables and confirms firstly, if there is sufficient evidence, to decline /reject the ‘null hypothesis’ which suggests that ‘there is not a relationship’, and to confirm that the findings are not the result of chance (if p<0.05). Secondly, the significance test calculates the significance level of the relationship between two variables, and accept accordingly, the null hypothesis if p>0.05 and confirms that the findings are the results of chance. Additionally, this research employs a directional test. In other words, the research tests directional or one-tailed hypotheses (Connolly, 2007). This research dealt with three types of variables: numerical, ordinal and scale variables. In order to answer the research questions, the author considered the purpose of the study and selected the most suitable variables to be examined. Further, in view to choose the best method of analysis, the author founded the selections, on writings by many authors (Voelkl and Gerber, 1999; Yockey, 2008; Connolly, 2007; Pallant, 2013). To find out whether, there is a relationship between two variables, the study needed to compare two or more categories of the two variables under analysis. In this regard, the study used cross tabulation or contingency tables and percentages. Because of using such tables, the researcher provided a basic definition of the terminologies used in this section. Thus,

165

a standard definition of a two-way contingency table or cross tabulation depicts this as ‘the joint-frequency distribution for two variables’ (Sharma, 1996, p. 37). Although, there is not a particular recommendation regarding the most suitable method to analyse the relationship between two variables, neither such advice, with regard to the most appropriate statistical test to use in such situations, this thesis endeavours to use Connolly’s (2007, p.111) summary guide.

Consequently, the author of this thesis

conducted two analyses of the relationship between two variables, as follows: (1) the first analysis was conducted on the relationship between two nominal variables (Analyses 1 – 4), and (2) the second analysis was conducted on the relationship between two scale variables (Analyses 5 – 8) (Connolly, 2007, p. 111). The first analysis comprised four examples, and the second analysis had four examples. According to Connolly (2007, p. 177), when dealing with the relationship between two nominal variables, it is recommended that the most suitable statistical test is Chi-square test. In view to answer the first research question of the thesis, the author considered the analysis suggested above. Further, the research is exploratory, by investigating also, variables’ relationships with CoPs & networks, as a common theme. ANALYSIS OF RELATIONSHIP BETWEEN TWO NOMINAL VARIABLES Research Question 1: ‘What is the impact of learning on women entrepreneurs’ success? Research Question 6: ‘What is the role of CoPs & networking?’ Hypothesis 2: ‘Learning has a positive impact on women entrepreneurs’ success’ (1)The first relationship under analysis refers to two categorical variables: the first variable is from section B – ‘Learning/Entrepreneurship education’ (Question 12): ‘Learn from information, communication, participation and sharing’ (LICPS), and has three categories: ‘0=Yes; 1=No and 2=n/a’. The second variable belongs to section E – ‘Women entrepreneurs’ success’ (Question 6), and is a categorical variable: ‘Entrepreneurship education is enhancing business success’ (EEDBS), with two categories: ‘1=Yes; 2=No’. The objective of this analysis is to determine if there is a relationship between these two categorical variables. The study formulated the null hypothesis and the alternative hypothesis (Yockey, 2008) as follows: 166

H0: ‘There is no relationship between LICPS and EEDBS’. H1: ‘There is a relationship between LICPS and EEDBS’. According to Yockey (2008) the Chi-Square test of independence provides a test of the ‘null-hypothesis’, in other words, to test that there is no relationship between the two categorical variables. Conform to the first table ‘Crosstabulation’, there are 148 valid cases, showing 98.7% of women entrepreneurs with complete answers out of 150 participants. About 86.9% of the valid cases answered ‘Yes’, they believed that they learn from information, communication, and participation and sharing’ and ‘Yes’; they agreed that ‘Learning (EED) is enhancing business success’ (Table 5.8).

For a given

probability p<0.05, the result of the test is 0.004 (Table 5.9), which is less than 0.05 and indicates that the test rejects the null hypothesis and confirms the existence of a relationship between these two categorical variables.

Moreover, X² (df – degrees of

freedom (3-1)*(2-1) = 2, N =148) = 10.89, p<0.05, Cramér V = 0.27 (Table 5.10), demonstrates that there is a significant positive relationship between the two categorical variables. Also, ‘V’ value indicated from the symmetric measure of 0.27 and showed a ‘medium’ effect size, in other words a ‘moderate relationship’ between the two variables (Cohen, 1998, in: Yockey, 2008, p. 209). Pearson Chi-Square is 10.89, with df = 2, and a p-value of 0.004 which is less than 0.05 (Table 5.9). In conclusion, the null hypothesis is rejected and according to the statistics, there is a relationship between the two variables (Yockey, 2008). Table 5.8 Crosstabulation Cases LICPS * EEDBS

Total 150

Valid 148

Yes

86.9%

13.1%

Source: F. Tomos, 2016 (SPSS)

Table 5.9 Chi-Square Test LICPS * EEDBS

Pearson Chi-Square Sig 0.004

Value 10.897

df 2

Source: F. Tomos, 2016 (SPSS), p<0.05, p-value=sig.

Table 5.10 Symmetric Measures LICPS* EEDBS

Cramer’s V

Value 0.271

Source: F. Tomos, 2016 (SPSS), p<0.05

167

Sig. 0.004

Valid Cases 148

(2)The second relationship under analysis refers to two nominal variables: the first variable is from section D, ‘Communities of practice’, (Question3) which is a categorical variable: ‘Type of participation to communicate’ (TPC), and has five categories: ‘1=Face to face; 2=Online, 3=other, 4=face to face and online, 5=n/a’. The second variable belongs to section E, ‘Women Entrepreneurs’ Success’ (Question 11), which is also a categorical variable: ‘Types of learning to enhance success’ (TLES), with eight subcategories (traditional, blended, online, distance, e-learning, networking through facebook/twitter/linkedin; none; and more than two types of learning). As usual, the objective of the analysis is to find out if there is a relationship between the two categorical variables (CoPs & networking * WES). Further, the null hypothesis and the alternative hypothesis (Yockey, 2008) are defined as follows: H0: ‘There is no relationship between TPC and TLES’. H1: ‘There is a relationship between TPC and TLES’. Conform to the first table (Table 5.11), there are 148 valid cases, showing 98.7% of women entrepreneurs with complete answers out of 150 participants.

There is an

increasing percent of 71.9% of women entrepreneurs who prefer to use blended learning, in other words, both types of learning: face to face, and online. Of 148 valid cases, 55.6% showed that women entrepreneurs preferred online type of participation to communicate, and multiple types of learning to enhance success. In SPSS, the p-value is reported as ‘sig.’. The results of this test showed a sig. of 0.001 which is less than 0.05 (p<0.05) and indicates that the null hypothesis is rejected and a relationship between the two categorical variables is assumed (Yockey, 2008). Further, the chi-square (df=24, N=148) = 56.69, p<0.05, Cramér V = 0.31, demonstrates the existence of a significant relationship between the two categorical variables (Table 5.12; 5.13). The hypothesis in this test allowed for demonstrating the relationship, but failed to indicate how strong the relationship is. The degree of this relationship is given by calculating the effect size, which indicates the magnitude. The ‘V’ value indicates from the symmetric measure of 0.31 showed a ‘medium’ effect size, indicating a ‘moderate relationship’ between the two variables (TPC * TLES) (Cohen, 1998, in: Yockey, 2008, p. 209). Below, are provided the results of this analysis (Table 5.11 – 5.13):

168

Table 5.11 Crosstabulation Cases TPC * TLES

Total

Valid

Face-to-Face & Online

150

148

71.9%

Online/Face-toFace 55.6%/41.2%

Source: F. Tomos, 2016 (SPSS)

Table 5.12 Chi-Square Test TPC * TLES

Pearson Chi-Square Sig 0.001

Value 56.686

df 24

Source: F. Tomos, 2016 (SPSS), p<0.05, p-value=sig.

Table 5.13 Symmetric Measures TPC* TLES

Value 0.309

Cramer’s V

Sig. 0.000

Valid Cases 148

Source: F. Tomos, 2016 (SPSS), p<0.05

(3) The next relationship analysed refers to another two categorical variables from section C (Q3) – Digital Platforms (NET) & ICTs * section D (Q1) – CoPs & networking. These are the following: ‘Twitter usage for business’ (TUB), with two categories ‘Yes/No’ and ‘belonging to Networking Groups to share information and knowledge’ (NGSIK), also with two categories ‘Yes/No’. About 77.9% within the Networking Groups (women entrepreneurs who belong to Networking Groups) answered ‘Yes’, they use Twitter for business. The results of this test indicated a sig. of 0.001 which is less than 0.05 (p<0.05) and indicates that the null hypothesis is rejected. Further, the null hypothesis and the alternative hypothesis (Yockey, 2008) are defined as follows: H0: ‘There is no relationship between TUB and NGSIK’. H1: ‘There is a relationship between TUB and NGSIK’. There is a relationship between the two categorical variables: TUB * NGSIK (Yockey, 2008). Furthermore, according to Cramer’s V there is a significant moderate relationship between these two categorical variables; where sig. = 0.000, with p < 0.05. Therefore, there is a significant relationship between TUB * NGSIK (CoPs & networking * Digital Platforms & ICTs) (Tables 5.14 – 5.16). Table 5.14 Crosstabulation Cases TUB * NGSIK

Total 150

Yes Valid 149

Source: F.Tomos, 2016 (SPSS)

169

77.9%

Table 5.15 Chi-Square Test TUB * NGISK

Pearson Chi-Square Sig 0.001

Value 18.870

df 2

Source: F. Tomos, 2016 (SPSS), p<0.05, p-value=sig.

Table 5.16 Symmetric Measures TUB * NGISK

Cramer’s V

Value 0.356

Sig. 0.000

Valid Cases 149

Source: F. Tomos, 2016 (SPSS), p<0.05

(4)Further analysis was conducted to find out whether there is a relationship between Learning (EED) and CoPs & networking. For this time, the author applied the mechanics proposed by Pallant (2013). The author followed the same steps as above and analysed the relationship between ‘Type of participation to communicate’ (TPC), section D, CoPs & networking (Question 3), and ‘Learning from information, communication, participation and sharing’ (LICPS), section B, Learning (EED) (Question 12). The analysis showed that out of 86 respondents who selected either ‘online’ or ‘’blended’ (online & face-to-face), 82% (71 respondents) selected ‘Yes’ as the main type of participation to communicate (LICPS) (Table 5.17). In conclusion, there is a significant positive relationship between the two variables (rho = 0.215, Aprox. Sig. = 0.008, p<0.01). Table 5.17 Symmetric Measures TPC * LICPS

Spearman Correlation

Value 0.215

Sig. 0.008

Valid Cases 149

Source: F. Tomos, 2016 (SPSS), p<0.05

5.5 The Analyses of Relationships between Scale Variables and the Role of Significance Test Research Question 1: What is the impact of Digital Platforms & ICTs on WES? What is the impact of Learning on WES? Research Question 6: What is the role of CoPs & networking? Hypothesis 3: ‘Digital Platforms & ICTs have a positive impact on WES’. Hypothesis 2: ‘Learning has a positive impact on WES’ (5) In order to answer the research questions (Q1/Q6) and test the hypothesis, the author conducted additional analyses with regard to the relationship between Digital Platforms & ICTs and CoPs & networking. The first relationship under analysis was between the following variables: ‘Communities of Practices’, section D, CoPs & networking 170

(Question 4) and ‘Learning with ICT’, section C, Digital Platforms (NET) & ICTs (Question 1). For the first relationship, the author provided the following tables (Tables 5.18; 5.19): Table 5.18: The Analysis of two scale variables (Digital Platforms & ICTs /Section C/Q1 * CoPs & networking /Section D/Q4): Variables Learning online * CoPs are important for business success (LO * CoPsBS) Learning online * In CoPs I find information to grow my business (LO * CoPsGB) Learning in groups * Through CoPs I am encouraged to succeed (LG * CoPsES) Learning in groups * In CoPs I find information to grow my business (LG * CoPsGB)

Number (1) (2) (3) (4)

Source: F. Tomos, 2016 (SPSS)

Table 5.19: Digital Platforms (NET) & ICTs * CoPs & networking Chi-Squared Tests Variables

Pearson’s R

Approx. Sig.

Approx. Tᵇ

VeryOften/ Strongly Agree (%)

0.394

0.000ᶜ

5.202

52.9

Value

(1)

63.988ª

Asymp. Sig. (2sided) 0.000

(2)

59.314ª

0.000

0.406

0.000ᶜ

5.389

52.9

(3)

45.108ª

0.000

0.362

0.000ᶜ

4.721

50.0

(4)

36.831ª

0.000

0.310

0.000ᶜ

3.959

Source: F. Tomos, 2016 (SPSS) a. Not assuming the null hypothesis. b. Using the asymptotic standard error assuming the null hypothesis. c. Based on 10000 sampled tables with starting seed 2000000.

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The results from the above table (Table 5.19) indicate moderate significant relationships between Digital Platforms & ICTs * CoPs & networking. More specifically, the results clearly indicate that, between the variable ‘learning online’ and the following variables: ‘CoPs are important for business success’ and ‘In CoPs I find information to grow my business’, there are significant moderate relationships. Consequently, “There are relationships between Digital Platforms & ICTs * CoPs & networking”. (6) Further analyses were conducted on the relationship between Digital Platforms & ICTs * WES (Section C/Q1 * Section E/Q5).

The rated opinions of women

entrepreneurs, regarding the impact of a range of factors on WES, and their relationships with women entrepreneurs’ opinions about the frequency of learning in group, and learning online, were scrutinised by the author. The results from the table (Table 5.20) demonstrate the presence of moderate relationships between the following scale variables: learning in groups, learning online and opinions regarding the impact of Digital Platforms, Twitter and Facebook upon WES. In other words, there is a significant relationship between Digital Platforms & ICTs * WES (Table 5.21). Consequently, “There are significant relationships between Digital Platforms & ICTs * WES”. Table 5.20: The Analysis of the relationship between two scale variables: Digital Platforms (NET) & ICTs (Section C/Q1) * WES (Section E/Q5) Variables Learning in groups * Twitter (LG * TW) Learning online * New Emerging Technologies (LO * NET) Learning online * Twitter (LO * TW) Learning online * Facebook (LO * FB)

Number (1) (2) (3) (4)

Source: F. Tomos, 2016 (SPSS)

Table 5.21: Digital Platforms (NET) & ICTs * WES Variables

Chi-Squared Tests Value df Asymp. Sig. (2sided)

Pearson’s R

Approx. Sig.

Approx. Tᵇ

Very Often/Strongly Agree (%)

(1)

33.402ª

0.007

0.196

0.007ᶜ

2.418

12.5

(2)

32.947ª

0.008

0.268

0.001ᶜ

3.378

70.6

(3)

34.102ª

0.005

0.319

0.000ᶜ

4.082

29.4

(4)

43.647ª

0.000

0.381

0.000ᶜ

5.003

52.9

Source: F. Tomos, 2016 (SPSS) a. Not assuming the null hypothesis. b. Using the asymptotic standard error assuming the null hypothesis. c. Based on 10000 sampled tables with starting seed 2000000. d. Based on normal approximation.

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(7)The second part of the analysis on the relationship between two scale variables comprises two additional examples. According to Connolly (2007, pp. 111; 177) the most suitable test for the analysis of the relationship between two scale variables is the Pearson Correlation Test. The author conducted an analysis of the relationship between ‘Learning preferences’ four-item scale variable (Learning/EED), Section B/Q14) and ‘Impact of various factors that affect business success’ nine-item scale variable (WES, Section E/Q5), which is a ranked variable. Although, one of the variables under analysis is a ranked variable, it is still disputable whether to employ the Spearman Correlation statistical test, or to base the selection of the test only on the graphical representation and the guidance from the summary guide by Connolly (2007). In order to avoid bias and to have an increased percent of accuracy within the results of the thesis, the author analysed firstly, this relationship by means of Pearson correlation. The results of such analysis with SPSS are displayed below, together with interpretations. In addition, due to lack of space, the research only presents the most important and significant values for the analysis. The results of the analysis showed a ‘moderate’ relationship between the categories within the same variable (Connolly, 2007). This is the situation for both variables involved in this analysis. However, ‘moderate’ to ‘strong’ correlations are between the internal elements of the second variable ‘Impact of various factors affecting business success’, which can reach, sometimes values such as 0.579 (Twitter versus NET) and 0.641 (Facebook versus NET) or 0.728 (Laptops versus Internet) for a significant level of 0.005 or 0.001. Table 5.22: Learning Preferences * Impact of various factors on business success

Flexible formal learning Flexible informal learning Experience-based learning Role model-based learning

Pearson Correlation Sig. (1-tailed) Pearson Correlation Sig. (1-tailed) Pearson Correlation Sig. (1-tailed) Pearson Correlation Sig. (1-tailed)

Source: F.Tomos, 2016 (SPSS) **. Correlation is significant at the 0.01 level (1-tailed). *. Correlation is significant at the 0.05 level (1-tailed). c. Listwise N=148

173

Flexible formal learning 1 .383** .000 .290** .000 .343** .000

Flexible informal learning .383** .000 1 .163* .024 .239** .002

Experiencebased learning .290** .000 .163* .024 1 .370** .000

From the Correlation table, Pearson Correlation values indicate moderate to strong inter items relationships, varying between r = 0.343 to r = 0.626 and weak relationship between ‘Twitter’ and ‘Role model-based learning’.

A further analysis is conducted with

Spearman coefficient (Spearman’s rho). The values from the table indicate the same positive weak (r=0.209, sig. = 0.005, p<0.05, 1-tailed sig.) correlation between ‘Learning Preferences’ scale variable (Role model-based learning/section B: Learning/EED) and ‘Impact of various factors on business success’ (Twitter/section E: WES) (Connolly, 2007). A second positive (r = 0.204, sig. = 0.006, p-value, p<0.05, 1-tailed sig.) relationship is indicated between ‘Flexible formal learning’ (Section B: Learning/EED) and ‘Tablets’ (Section E: WES). The outcomes of these analyses confirm and support the following hypothesis: H2: “Learning has a positive impact on WES” H2.1: “The impact of learning on WES is controlled by CoPs & networking” In the Correlations tables (Tables 5.23; 5.24) below, the author provides the detailed outcomes of the analyses: Table 5.23: Correlationsᶜ Tablets .204** .006

Pearson Correlation Sig. (1-tailed)

Flexible formal learning Source: F. Tomos, 2016 (SPSS)

Table 5.24: Correlationsc Role model-based learning

Digital Platforms (NET)

Pearson Correlation Sig. (1-tailed) Pearson Correlation Sig. (1-tailed)

.343** .000 .370** .000

.117 .079 .010 .450

Pearson Correlation Sig. (1-tailed) Twitter Pearson Correlation Sig. (1-tailed) Source: F. Tomos, 2016 (SPSS)

.164* .023 .209** .005

.470** 000 579** .000

Flexible formal learning Experience-based learning Networking and CoPs

(8)The last analysis on the relationship between scale variables was conducted by this study and the results are displayed below (Table 5.25). For instance, the author explored the relationship between the following two scale variables: ‘Learning Preferences’ (Section B: Learning (EED)/Q14) and ‘Rating the agreements of participation in CoPs’ (Section D: CoPs & networking/Q4). Below, are statistics provided for the relationships between the categories of the above mentioned variables: (1) Flexible formal learning * 174

Participation in CoPs increases knowledge; (2) Flexible formal learning * CoPs facilitates learning from experts; (3) Flexible formal learning * In CoPs I find information to grow my business; (4) Flexible informal learning * Participation in CoPs increases knowledge; (5) Flexible informal learning * CoPs facilitates learning from experts; (6) Flexible informal learning * In CoPs I find information to grow my business; (7) Experience-based learning * In CoPs I share knowledge; (8) Experienced-based learning * CoPs are important for business success; (9) Role model-based learning * Participation in CoPs increases knowledge; (10) Role model-based learning * CoPs facilitates learning from experts; (11) Role model-based learning * In CoPs I find information to grow my business. The next table (Table 5.25) contains the results of crosstabulation procedure using correlation statistics. The data from the table below indicates the existence of a relationship between the following two variables: Learning * CoPs & networking. Consequently, “There are relationships between Learning and CoPs & networking” Table 5.25: Entrepreneurship Education * Networking & CoPs Variables Relationships (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

No of valid cases 149 149 148 149 149 148 149 148 149 149 148

Pearson’s R value 0.249 0.363 0.304 0.295 0.324 0.291 0.255 0.293 0.220 0.298 0.265

Asymp. Std. Errorª 0.089 0.072 0.084 0.088 0.070 0.0753 0.070 0.085 0.076 0.075 0.077

Approx. Tᵇ

Approx. Sig.

Monte Carlo Sig.

3.113 4.725 3.854 3.737 4.154 3.673 3.199 3.702 2.740 3.701 3.318

0.002ᶜ 0.000ᶜ 0.000ᶜ 0.000ᶜ 0.000ᶜ 0.000ᶜ 0.002ᶜ 0.000ᶜ 0.007ᶜ 0.000ᶜ 0.001ᶜ

0.002ᵈ 0.000ᵈ 0.000ᵈ 0.000ᵈ 0.000ᵈ 0.000ᵈ 0.002ᵈ 0.000ᵈ 0.007ᵈ 0.001ᵈ 0.002ᵈ

Source: F. Tomos, 2016 (SPSS), p<0.05. a. Not assuming the null hypothesis. b. Using the asymptotic standard error assuming the null hypothesis. c. Based on normal approximation. d. Based on 10000 sampled tables with starting seed 2000000.

5.6 Partial Correlation Analysis Further, the author conducted a partial correlation analysis and the outcome from this analysis demonstrates a positive moderate relationship between the categories of the variable (Digital Platforms) (0.303/0.404, sig. 0.001, p<0.01, 1-tailed) (Table 5.26). It seems that the controlling variable (CoPs & networking) has an impact upon this variable. Additionally, the results of the analysis indicate a relationship between CoPs and the 175

categories of the variable Digital Platforms. This is a positive moderate relationship with a correlation coefficient of 0.368 (p-value of 0.001, p<0.01, one-tailed) (Connolly, 2007; Pallant, 2013). Consequently, the analysis demonstrates the impact of CoPs/Networking variable as a controlling variable with influence on both variables: Digital Platforms & ICTs (strong positive influence) and WES (weak positive influence, information provided by the following statistics: correlation coefficient of 0.202, sig. 0.007, p<0.01, one-tailed). Examples are provided by the author of this thesis in the table below (Table 5.26). Table 5.26: Correlations Control Variables Networking Groups

Learning on Facebook

Learning with Google

Home internet connection for learning

Correlation Significance (1-tailed) df

Learning with Google .303 .000 146 1.000 . 0 .440 .000 146 Twitter for learning .368 .000 147

Correlation Significance (1-tailed) df

Facebook usage for business .202 .007 143

Correlation Significance (1-tailed) df Correlation Significance (1-tailed) df

Learning with Google .303 .000 146 .440 .000 146

Correlation Significance (1-tailed) df Correlation Significance (1-tailed) df Correlation Significance (1-tailed) df

Control Variables NET help my participation in CoPs

Learning on Facebook

Control Variables Groups and Associations

Recent entrepreneurial training

Table 5.26: Correlations Control Variables Communities of Practice

Learning on Facebook

Home internet connection for learning Source: F. Tomos, 2016 (SPSS)

Consequently, H3: “Digital Platforms & ICTs impact upon WES” H3.1:“The Impact of Digital Platforms & ICTs upon WES, is controlled by CoPs & networking” The author is presenting below in Table 4.27 a summary of the inferential statistics. 176

Table 5.27 Summary of the Analysis (Inferential Statistics/Categorical Variables) Hypotheses tested by Chi-Square Test Main Hypothesis H2: EED has a positive impact on WES Sub-Hypothesis H2.1:There is a relationship between LICPS * EEDBS Main Hypothesis H5:There is a relationship between CoPs & networking * WES Sub-Hypothesis H5.1: There is a relationship between TPC * TLES Main Hypothesis H6: There is a relationship between NET & ICTs * CoPs & networking Sub-Hypothesis H6.1: There is a relationship between NGSIK * TUB

Alternative Hypothesis

Null Hypothesis

Hypothesis Effect

Accepted

Rejected

Positive

Accepted Sig.=0.004 Moderate relationship

Rejected

Significant Positive Cramér V=0.27 Medium effect size

Accepted

Rejected

Positive

Accepted Sig.=0.001 Moderate relationship

Rejected

Positive Cramér V=0.31 Medium effect size

Accepted

Rejected

Positive

Accepted Sig.=0.001 Moderate relationship

Rejected

Positive Cramér V=0.36 Moderate effect

Source: F. Tomos, 2017 (adopted from Ebie, 2011)

Table 5.28 Summary of the Exploratory Analyses (Scale Variables) Emergent Hypothesis H7: There is a significant relationship between Digital Platforms (NET) & ICTs * CoPs & networking

Emergent Sub-Hypotheses

H7.1: There is a significant relationship between LICPS * TPC H8: There are relationships between Digital Platforms (NET) & ICTs * CoPs & networking H8.1: There is a relationship between LO * CoPsBS H8.2: There is a relationship between LO * CoPsGB H8.3: There is a relationship between LG * CoPsES H8.4: There is a relationship between LG * CoPsGB H9: There are relationships between Digital Platforms (NET) & ICTs * WES H9.1: There is a relationship between LG * Twitter H9.2: There is a relationship between LO * NET H9.3: There is a relationship between LO * Twitter H9.4: There is a relationship between LO * Facebook

177

H10: There is a significant relationship between Learning (EED)*WES H10.1: There is a relationship between LP * IVFBS H10.2: There is a relationship between FFL*T H11: There is a relationship between Learning (EED) * CoPs & networking H12: Digital Platforms & ICTs have an impact on WES. The impact is controlled by CoPs & networking Source: F. Tomos, 2017

The author presents below the Exploratory Model of the categorical/scale variables relationships resulted from these analyses.

After the introductory section of the

inferential statistics, in the next section of this chapter, the author develops in depth the inferential statistics by employing Factor Analysis as a technique. Figure 5.30B Emergent Exploratory Model of the Relationships (Categorical/Scale Variables) 0.204; 0.209; 0.271; sig=0.006

WES

EE D 0.196 - 0.381

NET & ICTs 0.309 0.215; 0.249 - 0.363 0.310; 0.356; 0.362; 0.394; 0.406

CoPs & networking

Source: F. Tomos, 2017

178

5.7 Introduction to Factor Analysis Factoring or factor analysis is a statistical technique “for representing a large number of measured variables in terms of a smaller number of unobserved, usually hypothetical variables” (Miles and Huberman, 1994, p. 256). Sharma (1996) argued about two types of data analysis methods: a) dependence methods; b) interdependence methods. According to his opinion, the dependence methods examine the relationship between two groups of variables and establish whether the group of independent variables have an impact upon the dependent variables. Statistics employed in this case, investigate only the existence or the absence of the relationships (Sharma, 1996). The interdependence methods go one-step further and explore the motive (cause) and the way these variables are related (Sharma, 1996). Conform to the type and the number of variables involved in the study, as well as correlated with the category of data (metric/non metric), a research uses dependence methods such as multiple regression, ANOVA, discriminant analysis or logistic regression. Similarly, the number of variables and the type of data (metric/non metric) determine the use of interdependence analytical methods such as: two-way contingence table, Principal component, simple correlation or Factor Analysis (Sharma, 1996). Sharma (1996) states that Factor Analysis strives to determine a few factors, which are in control of the correlation between large groups of variables. Consequently, Sharma (1996) defines Factor Analysis as a reduction technique. Factor analysis technique reduces the data and finds patterns or themes. Additionally, the technique allocates corresponding labels/names to the cluster factors discovered by the research (Miles and Huberman, 1994). Similarly, other authors (Howitt and Cramer, 1999) established that Factor Analysis (FA) is a technique used by researchers in order to make sense of the complex data, by decreasing the number of variables to a small number of so called ‘super variables’ which have the capability to explain the correlations between the given variables (Pallant, 2013).

Furthermore, this technique is also

employed, in view to interpret and understand the trend, the structure or the pattern in the answers given by the respondents (Howitt and Cramer, 1999). It follows that, Factor Analysis can be used as a tool for further statistical analysis such as correlations and regressions. According to Pallant (2013), there are two approaches to FA: (1) exploratory factor analysis, which is used at the beginning of the research, to collect the information, to investigate the relationships between the variables, and to pinpoint the ‘constructs’ (Foster, 2001), which interpret the inter-correlation matrix; and (2) confirmatory factor 179

analysis, which is considered a more elaborated stage of the research, and is used to support the hypotheses, and to confirm the theoretical structure of the variables of the research (Pallant, 2013). The most effective and the most popular are the following two: principal component analysis (PCA) and factor analysis (FA) (Pallant, 2013; Foster, 2001). As Pallant (2013) argued, both techniques yield a small number of factors and interpret the variability within the main correlations of the variables.

Moreover, the

factors are “interpreted by the variables that correlate with them” (Tabachnick and Fidell, 2007, p. 610). Although, FA and PCA are used for data reduction, they are two separate techniques. As a consequence, the objectives of FA are distinct from the objectives of PCA. FA searches for the smallest number of factors that justifies the correlation between the variables, and uses factor rotation to find the best factor solution (Sharma, 1996). Conversely, PCA explains the variance – covariance structure by blending the original variables. Its objectives are data reduction and interpretation (Taguchi and Jugulum, 2002). Furthermore, in the case of PCA, ‘the variables’ are converted into mix or blended relationships, whilst, in the case of FA, ‘the factor’ is mathematically calculated (Pallant, 2013). PCA is a technique for creating new variables, which emerged from the original variables (Sharma, 1996). In Sharma’s (1996) view, the new created variables are ‘uncorrelated’ and equalled to the number of original variables. It is important that the researcher has to judge which method is most suitable for the research. Therefore, the researcher needs to know that PCA analyzes variance, whilst FA analyses covariance (commonality) (Tabachnick and Fidell, 2007).

The concept

‘variance’, measures the spread in the data (Sharma, 1996). The objective of the PCA is to extract maximum variance from the data with a small number of ‘orthogonal components’, whilst the goal of FA is to duplicate the correlation matrix with a few ‘orthogonal factors’ (Tabachnick and Fidell, 2007). Consequently, the choice between these two techniques depends on the evaluation of the data set and the objectives of the research (Tabachnick and Fidell, 2007). In addition to the above arguments, there are also divided opinions regarding the steps and conditions that a researcher must take into consideration when conducting FA. For instance, Foster (2001, p. 231) argued that for the FA technique, the number of participants in the research (respondents) should be ‘heterogeneous on their abilities or measures being studied’, more than 100 and bigger than the number of variables, at least twice. Furthermore, he suggested that the researcher 180

should use the scree plot to discover the number of factors needed to be extracted, and that FA should be preceded by the PCA. Similarly, Pallant (2013) recommends three steps in conducting FA: (1) to evaluate if the data is appropriate for FA; (2) to extract the factor; (3) to rotate and interpret the factor. Thus, regarding the first step, Pallant (2013) suggests assessing the sample size and the strength of the relationship between the variables. Besides these, authors (Foster, 2001; Pallant, 2013) argued about different methods of rotation, such as: Varimax for orthogonal simple structure rotation and Direct Oblimin for Oblique rotation. There are also various methods of factor extraction such as: principal component, principal factors, image factoring, maximum likelihood factoring, alpha factoring, unweighted least square and generalised least square (Pallant, 2013). However, both the extraction and the rotation are crucial phases of factor analysis, needed for the interpretation of the results of the analysis (Tabachnick and Fidell, 2007). There are a few concepts, which require explanations: scree plot, component, Eigen value, factor loading, commonality, orthogonality, and correlation matrix. A scree plot is a graph displaying the Eigen values and the number of components. The point where two coordinates meet to produce a gradient, or in other words, the place where the line starts its inclination, indicates the number of factors needed to be extracted (Foster, 2001). A component or a factor defines the variance in the inter-correlation matrix and the amount of variance is the Eigen value for that factor (Foster, 2001). A factor loading is the correlation between a variable and a factor and takes values between 0 and 1, the higher the better. Commonality is the percentage of the variance within a variable, which the factor can justify (Foster, 2001). Further, orthogonality represents the lack of association between the variables, or in other words, the correlation is â&#x20AC;&#x2DC;zeroâ&#x20AC;&#x2122; between variables, which do not share a variance (Tabachnick and Fidell, 2007). Finally, the correlation matrix is represented by columns and rows with different variables. At the intersection of these rows and columns with various variables are the indices of correlation between two different variables (Tabachnick and Fidell, 2007). The following sub-section starts FA. Although, there are many approaches, to FA, this thesis considers Pallantâ&#x20AC;&#x2122;s (2013) view, which is complemented with additional techniques by other authors (Foster, 2001; Howitt and Cramer, 1999; Voelkl and Gerber, 1999; Bryman and Cramer, 2009; Argyrous, 2011) that support the results and enhance the interpretation of the results.

181

5.7.1 Factor Analysis for Learning (EED) This analysis contains three phases: (1) the evaluation of the data and its conformity to FA requirements; (2) factor extraction and (3) factor rotation and interpretation (Pallant, 2013). With regard to the first phase of FA, more sophisticated opinions are provided by Tabachnick and Fidell (2007), who recommends the consideration of a few matters to be discussed within FA and interpretation:

sample size and missing data; normality;

linearity; outliers; multicolinearity and singularity; and factorability. A concise analysis of the data set, indicates that the research has a sample size (N = 150) with no missing data, appropriate to the theoretical requirements for this analysis and the number of participants exceeds the minimum of 100 respondents. According to Pallant (2013) this sample size is adequate if the outcome has a number of high loading variables (above 0.800). Tabachnick and Fidell (2007) argue that it is not the sample size, which is crucial, ensuring an effective outcome for the analysis, but the ratio of respondents to variables. Although, Nunnally (1978) suggests a ratio of 10 respondents to 1 variable, Tabachnick and Fidell (2007) recommend five cases per variable/item. This research considered both alternatives. After employing the first ratio (10:1) (Nunnally, 1978) and assessing the outcome of this, the author found that, although, statistically significant (sig. = 0.000, for p<0.05 and p<0.01) the KMO value of 0.504<0.600 was too small (Tabachnick and Fidell, 2007; Pallant, 2013). The next step in the analysis was the assessment of factorability of data. This is given by Bartlett’s test of sphericity (Bartlett, 1954; Pallant, 2013) and Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy (Kaiser, 1970, 1974; Pallant, 2013). In this regard, Bartlett’s test of sphericity should be statistically significant (p<0.05) for the FA to be considered as appropriate. According to Pallant (2013) KMO index ranges from 0 to 1, with 0.6 as a minimum recommended value for a good FA (Tabachnick and Fidell, 2007; Pallant, 2013). Consequently, the thesis employed the second ratio 1:5 suggested by Tabachnick and Fidell (2007). The following alternative selected relevant, randomly, 10 variables per group of the main variable/construct under research (10 variables/group x 4 = 40, 40:150, approximate ratio 1: 4, the ratio is smaller than the suggested one 1:5). However, this alternative proved to be most suitable for this analysis. Next, in the following lines the research conducted the analysis and the interpretation of FA for the first group of variables/constructs entitled ‘Learning (EED)’, with the ratio 1:4. For the purpose of this research and according with its objectives, the author used PCA, seconded 182

by Principal Axis Factoring (PAF) to enhance the results and their interpretation (Pallant, 2013; Tabachnick and Fidell, 2007).

The table below indicates KMO = 0.637 for a

Bartlett’s Test of Sphericity of 0.000 which is statistically significant, for p<0.05 and p<0.01 (Table 5.29). Table 5.29: Two Factors Extraction Solution, Learning (EED), KMO and Bartlett’s Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity

.637

Approx. Chi-Square

403.762

Sig.

.000

Source: F. Tomos, 2016 (SPSS)

Table 5.30: Correlation Matrix, Learning (EED) Two Factor Extraction (to be continued) Items The type of knowledge acquired LICSP

LICSP

Sig. (1-tailed)

0.571

The type of knowledge acquired 1.000

1.000

0.571

0.000

Source: F. Tomos, 2016 (SPSS)

Table 5.30: Correlation Matrix, Learning (EED) Two Factor Extraction (TBC) Items The usage of networking The type of knowledge acquired

The type of knowledge acquired 0.615 1.000

The usage of networking

Sig. (1-tailed)

1.000 0.615

0.000 0.000

Source: F. Tomos, 2016 (SPSS)

Table 5.30: Correlation Matrix, Learning (EED) Two Factor Extraction (Finished) Items Role model-based learning Experience-based learning

Role model-based learning 1.000

Experience-based learning 0.369

Sig. (1-tailed)

0.369

1.000

0.000

Source: F. Tomos, 2016 (SPSS)

183

0.000

Figure 5.31: Scree Plot for FA Learning (EED)

Source: F. Tomos, 2016 (SPSS)

The second concern under scrutiny is the strength of the relationship between the variables. Thus, the analysis of the Correlation Matrix demonstrates the existence of a ‘moderate’ relationship between the items of the matrix. The strength of the relationship is given by the correlation coefficient (Table 5.30) which takes values between r = 0.369 to r = 0.615 (a correlation coefficient between 0 and 0.2 – ‘weak’; 0.3 to 0.6 is moderate; > 0.6 is strong) (Connolly, 2007; Pallant, 2013). This information enforced the fact that the sample size is adequate for FA. Additionally, the presence of correlations that exceeds 0.300, confirms that the matrix is factorable (Tabachnick and Fidell, 2007; Pallant, 2013). The next phase within this analysis is ‘factor extraction’. This study employs PCA and principal factors. The research aims to find the smallest number of factors that can explain the variance in the original data (Pallant, 2013). Tabachnick and Fidell (2007) suggest an exploratory method, investigating different numbers of factors, in order to find the optimal solution. Consequently, the author of the thesis decided to follow these recommendations. These are the techniques that can be used for ‘factor extraction’: Kaiser’s criterion; Scree test and Parallel analysis (Pallant, 2013). Despite the fact that this method has been under heavy criticism for the retention of a big number of factors, this research used Kaiser’s criterion and the Scree plot (Pallant, 2013). According to Kaiser’s criterion or ‘Eigen value rule’ only the factors with an eigenvalue higher than 1.0 are retained for further analysis. Although, five factors have a value of one, however, the exploratory analysis indicated that, five factors extraction is not appropriate 184

(KMO=0.504<0.600) (Pallant, 2013). A second method used in parallel with Eigen values test is the Scree plot (Catell, 1996; Pallant, 2013). Conform to this second method of extraction the number of factors should be two/three. The above figure (Figure 5.31) indicates the first gradient between two and three. Consequently, the author extracts two factors. It is presumed that the ‘two factor extraction solution’ is more appropriate for the analysis of Learning (EED) (Pallant, 2013). The author presents below the results of this analysis, followed by the comments. Table 5.31: Two Factors Extraction Solution, Learning, Communalities Initial

Extraction

The Usage of networking 1.000 Learn from information, communication, 1.000 participation and sharing The type of knowledge acquired 1.000 Flexible formal learning 1.000 Flexible informal learning 1.000 Experience-based learning 1.000 Role model-based learning 1.000 Interactive Learner 1.000 Type of learner 1.000 studies 1.000 Source: F. Tomos, 2016 (SPSS), Extraction Method: Principal Component Analysis

.889 .861 .656 .566 .380 .453 .514 .012 .009 .032

Table 5.32: Two Factors Extraction Solution, Learning, Component Matrixª Component 1 .913

The Usage of networking Learn from information, communication, participation and sharing The type of knowledge acquired Flexible formal learning Flexible informal learning

.900 .710 -.314

Experience-based learning

.389 .683 .541 .657

Role model-based learning Interactive Learner

-.403

Type of learner studies Source: F. Tomos, 2016 (SPSS) Extraction Method: Principal Component Analysis.a a. 2 components extracted.

185

.593

Table 5.33: Two Factors Extraction Solution, Learning, Pattern Matrixª Component 1 .933

The Usage of networking Learn from information, communication, participation and sharing The type of knowledge acquired

.917 .810

Flexible formal learning

.753

Flexible informal learning

.619

Experience-based learning

.646

Role model-based learning

.717

Interactive Learner Type of learner studies Source: F. Tomos, 2016 (SPSS) Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization.a a. Rotation converged in 5 iterations.

Table 5.34: Two Factors Extraction Solution, Learning, Structure Matrix Component 1 .912

The Usage of networking Learn from information, communication, participation and sharing The type of knowledge acquired

.895 .810

Flexible formal learning

.752

Flexible informal learning

.615

Experience-based learning

.659

Role model-based learning

.706

Interactive Learner Type of learner studies Source: F. Tomos, 2016 (SPSS) Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization.

The presence of correlations that exceed 0.300 (0.339 – 0.893) indicates that the matrix is factorable (Tabachnick and Fidell, 2007; Pallant, 2013). The Component Matrix (Table 5.32) shows that the first three items load very strong on the first component (0.710 – 0.913) (Pallant, 2013). The factor extraction demonstrates that the smallest number of factors is two and they justify 43.7% of the variance (Pallant, 2013). The Pattern Matrix (Table 5.33), shows that the first three items (the usage of networking; learn from information, communication, participation and sharing; the type of knowledge acquired) load very strong on the first component and other three items (learning preferences) load strong on the second component (Pallant, 2013). The results from the Pattern Matrix, Structure Matrix and the Component Matrix, demonstrate that the two factor extraction 186

is a viable solution for this analysis. Additionally, Component Correlation Matrix shows a positive weak correlation between the items. The above table (Table 5.30) also indicates KMO = 0.637 for a Bartlett’s Test of Sphericity of 0.000 which is statistically significant, for p<0.05 and p<0.01 (Connolly, 2007; Pallant, 2013). It follows that, there is a relationship between the first factor, followed by the second factor, and the variable EED. The author labelled the first component with impact upon the variance in the data set, as ‘networking’ and the second component as ‘learning preferences’. In other words, EED (styles of learning) and the ‘usage of Networking’ are the main components leading to major variance in the original data set. In conclusion, these are the labels assigned by the author to the explored factors, which, impact upon the original data set and explain 43.7% of the variance in the variable – Learning (EED) and the relationships between the variable and the factors (Tabachnick and Fidell, 2007). 5.7.2 Factor Analysis for Digital Platforms & ICTs Ten items belonging to variable ‘Digital Platforms & ICTs’ (NET & ICTs), were analysed by Principal Component Analysis (PCA) using SPSS version 22. Before applying this method, the author investigated the suitability of data for factor analysis. In view to assess the appropriateness of such method, the data from the Correlation Matrix was inspected. In the table provided below, the Matrix (Table 4.35) shows a moderate to strong inter items relationship (e. g. 0.357 – 0.536/0.720) (Pallant, 2013; Connolly, 2007), which supports FA method. Also, the Kaiser-Meyer-Olkin value is 0.757, which exceeds the recommended value by Kaiser (1970; 1974) and Bartlett’s Test of Sphericity (Bartlett, 1954; Pallant, 2013) shows a significant value of 0.000, where p<0.05 and p<0.01, and supports the idea of factorability of the correlation matrix.

187

Table 5.35: Correlation Matrix, Digital Platforms & ICTs, (to be continued) Twitter for learning Correlation

Twitter for learning Other social network usage for business Facebook usage for business Twitter usage for business Mobile applications usage for business You Tube usage for business Learning with YouTube Wireless connection for learning Internet at home usage for business Google usage for business Source: F. Tomos, 2016 (SPSS)

1.000 .461

Other social network usage for business .461 1.000

Facebook usage for business .416 .357

.416 .720 .352

.357 .536 .355

1.000 .406 .374

.347 .249 .318

.405 .288 .066

.170 .194 .322

.132

.087

.085

.186

.184

.146

Table 5.36: Correlation Matrix, Digital Platforms & ICTs (Finished) Twitter usage for business Twitter for learning Other social network usage for business Facebook usage for business Twitter usage for business Mobile applications usage for business You Tube usage for business Learning with YouTube Wireless connection for learning Internet at home usage for business Google usage for business Source: F. Tomos, 2016 (SPSS) Correlation

You Tube usage for business

.720 .536

Mobile applications usage for business .352 .355

.406 1.000 .238

.374 .238 1.000

.170 .369 .322

.369 .280 .103

.322 .244 .287

1.000 .522 .123

.087

.219

.040

.076

.275

.166

.347 .405

Table 5.37: KMO and Bartlettâ&#x20AC;&#x2122;s Test, Digital Platforms & ICTs (NET & ICTs) Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity

Approx. Chi-Square df Sig.

Source: F. Tomos, 2016 (SPSS)

188

.757 400.474 45 .000

Figure 5.32: Scree Plot, Digital Platforms & ICTs

Source: F. Tomos, 2016 (SPSS)

Principal Component Analysis discovered three factors with Eigenvalues higher than 1. These three factors explain 59.8% of the variance of the original data set. Also, the Scree Plot (Catell, 1966) presented above indicates (Figure 5.32) a clear change in line direction at two and three. It is arguable whether the analysis should consider two or three factors to be finally extracted. Nevertheless, a further analysis of the Component Correlation Matrix indicated ‘weak’ inter-items correlation and a moderate relationship between items one and three (r = 0.340). Therefore, as a result of the strength of the relationship between two factors (factor one and three), and the indirect influence that the third factor might have through its relationship with the first factor and the variable, the author suggests considering the extraction of three factors. In support of this presumption, the study conducted further investigation into Pattern Matrix and Structure Matrix (Tables 5.38; 5.39). Pattern Matrix explains factor loadings on each variable. Consequently, the first components can be named ‘Digital Platforms for Businesses’ or ‘Social Media for Businesses’. The label for the second component could be ‘internet connection and search engine for business and learning’. The label for the third component is ‘Learning and doing business with You Tube ‘. The last table ‘Structure Matrix’ (Table 5.39) indicates ‘moderate’ to ‘very strong’ correlations between factors and variables. The situation is similar for the three factors, a fact that enforced the decision to accept the extraction of three factors as a valuable solution for the analysis and interpretation.

189

Table 5.38: Three Factor Extraction Solution, Pattern MatrixÂŞ, Digital Platforms & ICTs Component 1 Twitter usage for business

.866

Twitter for learning

.829

Facebook usage for business

.712

Other social network usage for business

.612

Wireless connection for learning

.701

Google usage for business

.693

Internet at home usage for business

.678

Mobile applications usage for business

.453

Learning with YouTube

.835

You Tube usage for business

.831

Source: F. Tomos, 2016 (SPSS) Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization.a a. Rotation converged in 6 iterations.

Table 5.39: Three Factor Extraction Solution, Structure Matrix, Digital Platforms & ICTs Component 1

Twitter usage for business

.852

.368

Twitter for learning

.850

.305

Facebook usage for business

.701

Other social network usage for business

.695

.350 .496

Wireless connection for learning

.725

Google usage for business

.691

Internet at home usage for business

.655

Mobile applications usage for business

.465

You Tube usage for business

.379

Learning with YouTube

.554

.374 .864 .831

Source: F. Tomos, 2016 (SPSS) Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization.

190

5.7.3 Factor Analysis for CoPs and Networking The following table (Table 5.40) presents FA for ten items belonging to variable ‘CoPs & Networking’. The author assessed the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO) (Table 5.41). In this case KMO = 0.954, which is a superior value above the recommended value of 0.600 (Pallant, 2013). Also, the table (Table 5.41) below shows the Bartlett’s Test of Sphericity value which is significant sig. / p = 0.000, for p<0.05 or p<0.01. Additionally, the Correlation Matrix shows a significant number of values above 0.300. The correlation coefficient varies between r = 0.576 and r = 0.868/0.894, indicating a strong inter-items correlation and the factorability of the Matrix (Tabachnick and Fidell, 2007). Consequently, FA is appropriate as a method of analysis (Pallant, 2013). Table 5.40: Correlation Matrix, CoPs & Networking

Correlation

iPad. tablet help my participation in CoPs

Communities of Practice

Business Associations

Laptop, computers help participation in CoPs

.901

.855

.656

Mobile phones help my participation in CoPs

.894

.840

.636

Facebook helps me to participate in CoPs

.868

.790

.601

iPad. tablet help my participation in CoPs

1.000

.817

.663

Communities of Practice

.817

1.000

.738

Business Associations

.663

.738

1.000

Networking Groups

.694

.805

.576

Twitter helps me to participate in CoPs

.859

.764

.592

Yahoo Messenger help my participation in CoPs

.817

.723

.576

Groups and Associations

.768

.778

.599

Source: F. Tomos, 2016 (SPSS)

Table 5.41: KMO and Bartlett’s Test, CoPs & Networking Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity

Approx. Chi-Square df Sig.

Source: F. Tomos, 2016 (SPSS)

191

.954 1907.291 45 .000

From the Total Variance Explained Table (SPSS) the column labelled â&#x20AC;&#x2DC;Initial Eigenvaluesâ&#x20AC;&#x2122; indicates that one factor only has an Eigenvalue above 1.00 and accounts for 79.5% of the original data set variance. In order to confirm whether the study has to extract one factor, the author also looked at the Scree Plot (Figure 5.33). Conform to Pallant (2013) only components above the elbow of the line are considered for the extraction/analysis. Figure 5.33: Scree Plot, CoPs & Networking

Source: F. Tomos, 2016 (SPSS)

Table 5.42: One Factor Extraction Solution, Communalities, CoPs & Networking Initial

Extraction

Laptop, computers help participation in CoPs

1.000

.925

Mobile phones help my participation in CoPs

1.000

.897

Facebook helps me to participate in CoPs

1.000

.868

iPad. tablet help my participation in CoPs

1.000

.870

Communities of Practice

1.000

.827

Business Associations

1.000

.542

Networking Groups

1.000

.696

Twitter helps me to participate in CoPs

1.000

.838

Yahoo Messenger help my participation in CoPs

1.000

.751

Groups and Associations

1.000

.742

Source: F. Tomos, 2016 (SPSS) Extraction Method: Principal Component Analysis.

192

Table 5.43: One Factor Extraction Solution, Component Matrix, CoPs & Networking Component 1 Laptop, computers help participation in CoPs

.962

Mobile phones help my participation in CoPs

.947

iPad. tablet help my participation in CoPs

.933

Facebook helps me to participate in CoPs

.932

Twitter helps me to participate in CoPs

.915

Communities of Practice

.910

Yahoo Messenger help my participation in CoPs

.866

Groups and Associations

.861

Networking Groups

.834

Business Associations

.736

Source: F. Tomos, 2016 (SPSS) Extraction Method: Principal Component Analysis.a a. One component extracted.

The above table (Table 5.42) entitled ‘Commonalities’ shows the variance in the variable justified by a factor (Tabachnick and Fidell, 2007). The following five factors are accountable for the main variance in the variable under analysis: (1) Laptops, computers help participation in CoPs; (2) Mobile phones help my participation in CoPs; (3) iPad, tablets help my participation in CoPs; (4) Facebook help my participation in CoPs; (5) Twitter helps me to participate in CoPs. The second table named ‘Component Matrix’ (Table 5.43) indicates the ‘unrotated’ loadings of each item in the component. The first six items ‘load’ very strong (above 0.900) and the next four items load strong (above 0.700) on the first component (Tabachnick and Fidell, 2007). This demonstrates the suitability of one factor extraction solution (Pallant, 2013). In order to interpret the meaning of the factor, the author needed to consider the content of the variable that loaded highly on the factor (Pallant, 2013). Thus, the factor under discussion could have one label such as: ‘CoPs and Digital Platforms’ or the following two labels: CoPs and ICTs & CoPs with Social Media. In this case the study discovered one factor only with Eigenvalue above 1.00. Nevertheless, based on the Scree test and for the enhancement of the interpretation of the analysis, as well as for a better understanding, the author endeavoured to analyse a two factors fixed extraction (the second factor Eigenvalue = 0.800<1.00). The main outcome of two factors extraction is presented below (Tables 5.44 – 5.47). KMO = 0.947, Bartlett’s test of significance is significant for p<0.005 (sig. 193

= 0.000) and the correlation coefficient shows strong inter items correlations. Moreover, the Component Correlation Matrix indicates a strong correlation between the two components (0.685). Table 5.44: Two Factors Extraction Solutions, KMO and Bartlettâ&#x20AC;&#x2122;s Test, CoPs Kaiser-Meyer-Olkin Measure of Sampling Adequacy.

.947 Approx. Chi-Square

Bartlett's Test of Sphericity

1913.049

Sig.

.000

Source: F. Tomos, 2016 (SPSS)

Table 5.45: Two Factors Extraction Solution, Component Correlation Matrix, CoPs Component

1.000

.685

1.000

Source: F. Tomos, 2016 (SPSS)

Table 5.46: Two Factor Extraction Solution, Component MatrixÂŞ, CoPs Component 1

Communities of Practice

.917

Business Associations

.763

.525

Professional Associations

.742

.574

Networking Groups

.833

Yahoo Messenger help my participation in CoPs

.859

Twitter helps me to participate in CoPs

.907

Facebook helps me to participate in CoPs

.924

Laptop, computers help participation in CoPs

.958

Mobile phones help my participation in CoPs

.944

iPad. tablet help my participation in CoPs

.929

Source: F. Tomos, 2016 (SPSS) Extraction Method: Principal Component Analysis.a a. 2 components extracted.

194

Table 5.47: Two Factors Extraction Solution, Pattern MatrixÂŞ, CoPs and Networking Component

Communities of Practice

.586

.424

Business Associations

.890

Professional Associations

.951

Networking Groups

.723

Yahoo Messenger help my participation in CoPs

.923

Twitter helps me to participate in CoPs

.980

Facebook helps me to participate in CoPs

.995

Laptop, computers help participation in CoPs

.934

Mobile phones help my participation in CoPs

.938

iPad. tablet help my participation in CoPs

.902

Source: F. Tomos, 2016 (SPSS) Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization.a a. Rotation converged in 4 iterations.

The two factors together explained 85.6% of the total cumulative variance of the variables/original data set, whilst the second factor only explains 8.1% of the variance. According to Howitt and Cramer (1999), unless we have a rotation, the interpretation of the results is less valuable and is not valid. The study used PCA and Direct Oblimin as a rotational approach. The Component Matrix, shows unrotated loadings on each item, which for both components are higher than 0.400 (Pallant, 2007). This fact suggests that the two factors extraction solution is acceptable for the analysis. Also, the rotated two factors solution, as displayed within the Pattern Matrix, indicates very high loadings of eight items on the first component, and two very high loadings on the second component (Pallant, 2007). This outcome confirms the suitability of the two factors extraction solution for factor analysis of CoPs & Networking (ten items solution). Additionally, this second alternative to factor analysis for CoPs & Networking enhances the interpretation of the results and enriches the methods of labelling within the interpretation process: (1) ICTs help participation in CoPs and (2) Digital Platforms helps participation in CoPs.

195

5.7.4 Factor Analysis for Women Entrepreneurs’ Success (WES) The nine items were analysed with Principal Component Analysis (PCA). Further, the suitability of data was assessed by investigating the correlation matrix. There is a good number of high values above 0.300, which demonstrates strong inter items relationship and the factorability of the matrix. The Kaiser-Meyer-Olkin (KMO) has a value of 0.833, and the Bartlett’s Test of Sphericity for sig. = 0.000, is statistically significant for p<0.01 and 0.05, thus, confirming the factorability of the correlation matrix. The Total Variance Explained Table (SPSS) indicates that the three factors solution explained 71.6% of the variance in the data set (Pallant, 2013). Additionally, the Scree Plot shows that the line has an ‘elbow’ at 3.00 (2.00 = 3.00), which indicates the suitability of three factor extractions. To revise, the extraction method was PCA and the rotation method ‘Oblique’ with Oblimin technique (Tabachnick and Fidell, 2007; Pallant, 2013). Table 5.48: Three Factors Extraction Solution, KMO AND Bartlett’s Test, WES Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity

.833

Approx. Chi-Square

576.054

Sig.

.000

Source: F. Tomos, 2016 (SPSS)

Table 5.49: Three Factors Extraction Solution, Component Correlation Matrix, WES Component

1.000

.521

.222

.521

1.000

.218

.222

.218

1.000

Source: F. Tomos, 2016 (SPSS) Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization.

Table 5.50: Three Factors Extraction Solution, Correlation Matrix, WES

Correlation

Twitter

Facebook

Internet

Entrepreneurship Education

.143

.097

.286

Laptops/ Computer s .203

Digital Platforms & ICTs

.567

.631

.437

.464

Networking and CoPs

.404

.410

.375

.374

Twitter

1.000

.630

.388

.299

Facebook

.630

1.000

.584

.466

Internet

.388

.584

1.000

.729

Laptops/Computers

.299

.466

.729

1.000

Mobile Phones

.279

.384

.423

.529

196

Sig. (1-tailed)

Tablets

.389

.429

.613

.606

Entrepreneurship Education

.041

.120

.000

.007

Digital Platforms & ICTs

.000

CoPs & networking

.000

Twitter Facebook

.000

Internet

.000

Laptops/Computers

.000

Mobile Phones

.000

Tablets

.000

Source: F. Tomos, 2016 (SPSS)

Figure 5.34: Scree Plot, WES Women Entrepreneursâ&#x20AC;&#x2122; Success

Source: F. Tomos, 2016 (SPSS)

Table 5.51: Three Factors Extraction Solution, Communalities, WES Initial

Extraction

Learning (EED)

1.000

.875

Digital Platforms & ICTs

1.000

.700

CoPs & networking

1.000

.621

Twitter

1.000

.740

Facebook

1.000

.760

Internet

1.000

.724

Laptops/Computers

1.000

.775

Mobile Phones

1.000

.559

Tablets

1.000

.690

Source: F. Tomos, 2016 (SPSS) Extraction Method: Principal Component Analysis.

197

Table 5.52: Three Factors Extraction Solution, Component Matrixª, WES Component 1

Learning (EED)

.341

Digital Platforms & ICTs

.753

CoPs & networking

.620

Twitter

.669

.526

Facebook

.775

.325

Internet

.801

Laptops/Computers

.777

Mobile Phones

.658

Tablets

.728

3 .869

.357 .395

-.410

-.389

Source: F. Tomos, 2016 (SPSS) Extraction Method: Principal Component Analysis.a a. 3 components extracted.

Table 5.53: Three Factors Extraction Solution, Pattern Matrixª, WES Component 1

Learning (EED)

3 .938

Digital Platforms & ICTs

.761

CoPs & networking

.513

Twitter

.908

Facebook

.773

Internet

.762

Laptops/Computers

.886

Mobile Phones

.736

Tablets

.845

Source: F. Tomos, 2016(SPSS) Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization.a a. Rotation converged in 6 iterations.

198

.496

Table 5.54: Three Factors Extraction Solution, Structure Matrix, WES Component 1

Learning (EED)

3 .932

Digital Platforms & ICTs

.522

.830

CoPs & networking

.378

.622

Twitter

.378

.856

Facebook

.574

.850

Internet

.836

.511

Laptops/Computers

.878

.435

Mobile Phones

.740

.413

Tablets

.830

.410

.608

.323

Source: F. Tomos, 2016 (SPSS) Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization.

The preceded tables (Tables 5.51 – 5.54) give information about the Communalities, Component Matrix, Pattern Matrix and Structure Matrix. Thus, the first table (Table 5.51) under discussion is entitled ‘Communalities’. This table gives details regarding the variance in a variable, explained by the factor. In this situation, the table presents high values of variance, for the items. There are no low values within this table, which indicates that the items ‘fit well with other items’ (Pallant, 2013). The second table, Component Matrix (Table 5.52) indicates the unrotated loadings of each item on the three components, as follows: internet (0.801), laptops/computers (0.777), facebook (0.775), new emerging technologies (0.753) and tablets (0.728). All items load very strong (above 0.600) on the first component (except the first item). Only two items load strong (above 0.400) on the second component. One item loads very strong on the third component (0.895). This indicates that ‘the three factors’ is a good solution. There are two more analyses that should be considered before deciding the appropriateness of three factor solution. The next table presented the rotated two factor solution ‘Pattern Matrix’ (Table 5.53). This table shows items loading on three factor solution, with four items loading above 0.700 on the first factor and three items loading above 0.700 on the second factor and one item loading very strong (0.938) on the third component. However, Pattern Matrix indicates that the loading is not a correlation, but instead measures the relationship between the factor and the variable (Tabachnick and Fidell, 2007). Consequently, the Pattern Matrix demonstrated a very strong relationship between the factors and the 199

variable. The last table ‘Structure Matrix’ (Table 5.54) provides indeed details about the correlation between variables and factors. The table shows four high loadings (over 0.700) on the first component, followed by four high loadings on the second component (over 0.600) and two high loadings on the third component (above 0.600). The higher the loading, the more viable is that the variable measures a factor. Moreover, the measures demonstrate a correlation between the variables and the components (Tabachnick and Fidell, 2007). Furthermore, the Component Correlation Matrix (Tables 5.73) shows a strong inter-item correlation. Consequently, three factor extraction for this variable is an appropriate solution. The factors can be labelled as follows: ‘Digital Platforms’, ‘Social Media’ and ‘Learning’ which determine women entrepreneurs’ success. 5.8 Factor Analysis Discussions and Interpretations Following the analysis conducted above, the author must provide a rationale or the purpose for using FA, its benefit and conclusions, with regard to the outcome of such analysis. FA allowed the author to obtain both a small number of factors, called ‘super variables’ to be considered for further analyses and valuable insights into the correlation matrix, with regard to the correlations between various variables (Howitt and Cramer, 1999). Another benefit of using such method is that the author has the opportunity of a general perspective upon the pattern and the composition of responses (Howitt and Cramer, 1999). Thus, a PCA was conducted on the correlation of ten variables for the following four sections of the questionnaire: Learning (EED), Digital Platforms & ICTs (NET & ICTs), Communities of Practice & networking (CoPs & networking) and Women Entrepreneurs’ Success (WES).

These were the main variables of the conceptual

framework, research questions, and from the hypotheses of the thesis. A number of factors were extracted for each of these four sections, with Eigenvalue equal or greater than 1.00 (Howitt and Cramer, 1999). However, the extraction of factors has no value without the rotation of factors (Tabachnick and Fidell, 2007). As a result, the study conducted an Oblique rotation method with Oblimin technique, which yielded the Factor Structure (Table 5.54). A summary table (Table 5.55), showing the proposed labels allocated to the analysed factors and information regarding the factors and the variances explained by them within the original data set is presented below:

200

Table 5.55: FA labels and variances explained by factors within the variables and dataset Factor/variable

KMO Measure of sampling adequacy 0.637

Bartlett’s Test of Sphericity (Sig.)

Number of factors extracted

0.000

PCA/FA /Explained variance in the dataset (%) 43.7

FA NET & ICTs

0.757

0.000

59.8

FA CoPs & networking

0.947

0.000

85.6

FA WES

0.833

0.000

71.6

FA EED

Labels allocated to factors

(1) Learn from information, participation and Networking; (2) Learning preferences/styles of learning. (1) Digital Platforms for business. (2) Internet & search engines for business & learning. (3) YouTube for business & learning. (1) ICTs help participation in CoPs. (2) Digital Platforms helps CoPs & Networking. (1) Digital Platforms determine business success. (2) Social Media affects business success. (3)Learning determines business success.

Source: F. Tomos, 2016 (SPSS), FA – Factor Analysis; NET & ICTs – Digital Platforms & ICTs; CoPs & networking – Communities of Practices; ICTs – Information Communication Technologies

The table (Table 5.55) is based on Tabachnick and Fidell (2007) who suggested an exploratory method, investigating different numbers of factors, in order to find the optimal solution. The next section introduces the section entitled ‘correlation and regression’.

201

5.9 Correlation and Regression According to Tabachnick and Fidell (2007) there are various statistical techniques and the choice of a particular statistical technique depends on the purpose of the analysis, the number of variables assessed, the type and the nature of the variables, either they are dependent or independent or they are discrete or continuous. Thus, bivariate correlation evaluates the relationship between two continuous variables.

Whilst the bivariate

correlation determines the association between two variables, the bivariate regression predicts the dependent variable from the independent variable (Tabachnick and Fidell, 2007).

Further, multiple correlations assess the association between a continuous

dependent variable and two or more continuous independent variables. Contrary to this, multiple regressions predict the dependent variable from the scores of a few independent variables (Tabachnick and Fidell, 2007). A correlation conveys the degree to which two variables can change (Foster, 2001). A positive relationship depicts two variables that alter in the same direction: when one increases, the second variable increases also.

Contrary to this, a negative correlation

indicates that two variables act differently: when one variable increases, the second variable decreases (Foster, 2001). Correlations vary between -1.00 and +1.00 and a correlation of 0.00 indicates no relationship. According to Tabachnick and Fidell (2007), the Pearson product – moment correlation coefficient ‘r’ is the most used ‘measure of association’, no matter the scale of measurement. The correlation coefficient squared r² indicates the percentage of variance in y, which is determined by x. In others’ opinion (Tabachnick and Fidell, 2007), the correlation measures both the size and the direction of a ‘linear relationship’ between two variables. In order to check whether the relationship between variables is linear or curvilinear, one can plot a scattergram. On the scattergram, SPSS can draw the best fitting straight line that represents the relationship between x and y. This line is named the regression line and it takes the form of an equation: y=a + bx, ‘a’ is the intercept and ‘b’ is the slope, where ‘y’ is predicted from ‘x’. This is another type of correlation when one uses one or a few independent variables in order to predict a dependent variable and this type of analysis is called ‘bivariate’ or ‘multiple regression’ (Foster, 2001). According to Howitt and Cramer (1999), particularly in the case of a regression analysis, the relationship between two variables is expressed mathematically by the slope ‘b’ of the best fitting line and the coordinates where the line intersects the axis y, named intercept ‘a’. Therefore, 202

‘b’ is the slope of the regression line and is named the ‘unstandardised regression coefficient’ in SPSS. The intercept ‘a’ is referred to as the ‘constant’ in SPSS (Howitt and Cramer, 1999). Another type of analysis also discussed in this research is the partial correlation, which refers to a type of relationship between two variables, determined by a third variable, which is named controlled variable. Conform to some authors (Foster, 2001), the process of correlation and regression analysis is a complex process, which requires a few steps and procedures: (1) to assess the graphical representation (plot/scattergram) and find the evidence of linear/curvilinear relationship; (2) to calculate the mean and the standard deviations of the variables under correlation analysis; (3) to conduct a partial correlation and analyse the relationship between two variables when the third controlled variable has been ‘partialled out’; (4) to use a few independent variables and predict the dependent variable. 5.9.1 Introduction to Correlation Correlation analysis is defined as the linear relationship between two variables (Pallant, 2013). Moreover, this analysis has the capability to provide the details regarding ‘the strength’ and ‘the direction’ of the relationship. There are two main statistics that can be used to express the relationship between two variables: Pearson correlation ‘r’ which is used either with two continuous variables or one continuous and one dichotomous; the second used is Spearman rho, which is used for ordinal or ranked data (Pallant, 2013). According to Pallant (2013), Pearson correlation coefficient takes values from - 1 to + 1 where the strength of the relationship is given by the magnitude of the ‘absolute value’ (no matter the sign). The scatterplot for a perfect relationship displays a straight line. According to Pallant (2013), there are two types of interpretations: (a) the interpretation of output from scatterplot; (b) the interpretation of output from correlation. Both interpretations are valuable for the outcome of the analysis. Thus, (a) the interpretation of the output from scatterplot includes three phases: (1) the assessment of outliers, such as the accuracy of data and the presence of errors; (2) the assessment of data points, which implies check on data spread. A wide spread means ‘low correlation’ whilst a narrow spread means ‘strong correlation’. Pearson correlation is only used for linear relationship, thus the scatterplot should exhibit a straight line, not a curve; (3) the assessment of the direction of the 203

relationship between the variables (Pallant, 2013). With regard to (b) the interpretation of the output from the correlation, Pallant (2013) suggests that five steps are required within the process of output interpretation. These are the following: (1) assessment of the information regarding the sample; (2) evaluation of the direction of the relationship; (3) assessment of the strength of the relationship; (4) the calculation of the coefficient of determination; (5) assessment of the significance level. The author provides below details regarding the concepts used within this analysis. Thus, the strength of the relationship refers to the size of the value of the correlation coefficient and can vary between -1 to +1. The value of zero indicates no relationship, whilst +1 shows a perfect relationship (Pallant, 2013). Nevertheless, the authors have various interpretations. Cohen (1988, pp. 79-81; Pallant 2013, p. 139) suggested the following categories: small (r = 0.10 to 0.29); medium (r = 0.30 to 0.49) and large (r = 0.50 to 1.00). The next term refers to the ‘calculation of the coefficient of determination’. The formula used for this Coefficient is the following (r x r) = r² x 100. For example for two variables that correlate, r = 0.2, r² = 0.04 x 100 = 4%, the percentage of shared variance (explains only 4% of the variance). The last term explained is ‘the assessment of the significance level’ (sig. 2 tailed). The statistical significance indicates the level of confidence we have, in the results obtained (Pallant, 2013). In small samples (n = 30), moderate correlations, do not have statistical significance at p<0.05, whilst in large samples (N = 100+) small correlations (r = 0.20) have statistical significance. The focus, however, is on the strength of the relationship and the amount of shared variance (Pallant, 2013).

204

5.9.2 Correlation Analysis Research Question 4 (RQ4): Are there correlations between Learning, Digital Platforms & ICTs and WES? RQ4a: Are there correlations between Learning and WES? RQ4b: Are there correlations between Digital Platforms & ICTs and WES? Table 5.56A: Correlation (a) NET & ICTs * WES; (b) NET & ICTs* CoPs & Networking Variables (1) Increase in Sales/Turnover

r² = r x r

r²x100 (%) -

(2) Learning on Facebook

0.27**

0.073

7.3

(3) Twitter for business

0.28**

0.079

7.9

(4)The usage of Digital Platforms & ICT

0.36**

0.129

12.9

(5) Learning with youtube

0.25**

0.063

6.3

(6) Twitter for learning

0.25**

0.063

6.3

(7) Facebook usage for business

0.34**

0.116

11.6

(8) Other social networks for business

0.22**

0.049

4.9

0.177

17.7

0.144

14.4

0.348

34.8

(9) Facebook helps me to participate in CoPs

0.42**

(9) Facebook helps me to participate in CoPs

0.38**

(10)Twitter helps me to participate in CoPs

0.59**

**. Correlation is significant at the 0.01 level (1-tailed). Appendix Source: F. Tomos, 2016 (SPSS), Note: NET & ICTs – Digital Plaforms & ICTs; WES – Women Entrepreneurs’ Success, CoPs & networking – Communities of Practice and Networking

The interpretation of the output is based on the above table (Table 5.56A) and the information from SPSS. Thus, the analysis indicates N=149 valid cases. The correlations from the table are significant at sig. = 0.01 level, (1-tailed). (a)There is a significant small relationship between ‘increase in sales/turnover’ and the following variables: ‘learning with Facebook’, ‘Twitter for business’, Twitter for learning’, ‘learning with YouTube’ and ‘other social networks for business’. The coefficient of determination varies within a range between 4.9 (other social networks for business) to 7.9 (Twitter for business). The percentage of shared variance indicates that the correlations between the mentioned variables explain only 4.9% to 7.9% of the variance of the data set (Pallant, 2013). 205

(b)There is a significant moderate relationship (Pallant, 2013) between ‘increase in sales/turnover’ and the following variables: ‘the usage of Digital Platforms & ICTs’ (EED), and ‘Facebook usage for business’ (r = 0.36; r = 0.34). The coefficient of determination has increased values (r²=12.9; 11.6) which pinpoints toward a higher percentage of shared variance, and indicates that the correlation between these variables explains 12.9% and 11.6% of the variance in the data set.

Consequently, there is a

significant positive ‘small to moderate’ correlation between ‘Digital Platforms & ICTs * WES’ (r = 0.34), and between ‘EED * WES’ (r = 0.36). (c)A second type of relationship under analysis is between ‘Facebook helps me to participate in CoPs’ and the following variables: ‘Twitter for business’ and ‘Twitter for learning’. There is a significant positive moderate relationship, between ‘CoPs & networking * Digital Platforms & ICTs’, (r=0.38/0.42), explaining 14.4% to 17.7% of the variance.

Finally, (d) the last

relationship analysed is between ‘Twitter helps me to participate in CoPs’ and ‘Twitter for business’. This is a positive strong correlation, between ‘CoPs & networking * Digital Platforms & ICTs’, (r=0.59), with a significant coefficient of determination equal to 34.8 which explains approximately 35% of the variance in ‘increase in sales/turnover’ (Pallant, 2013). In conclusion, (1) there is a significant positive ‘strong’ correlation between Digital Platforms & ICTs * CoPs & networking; (2) there is a significant moderate correlation between Learning * WES; (3) there is a significant moderate correlation between Digital Platforms & ICTs * WES; (4) there is a significant strong relationship between CoPs & networking * WES. The results are displayed in the table below (Table 5.56 B). Table 5.56B Correlation Analysis Correlation WES * Learning (Increase in Sales * Usage of NET & ICTs) Digital Platforms & ICTs * WES (Facebook usage for business * Increase in Sales) CoPs & networking * WES (Twitter helps participation in CoPs * Increase in Sales) Digital Platforms & ICTs * CoPs & networking (Twitter for business * Facebook helps participation in CoPs)

Coefficient of Determination % ( r²) 12.9%

Interpretation Significant moderate correlation

11.6%

Significant moderate correlation

34.8%

Significant strong correlation

17.7%

Significant moderate correlation

Source: F. Tomos, 2017 (SPSS)

206

5.9.3 Simple Regression Analysis Research Question 2 (RQ2): Is there a significant relationship between Learning, Digital Platforms & ICTs and WES? (RQ2a): Is there a significant relationship between Digital Platforms & ICTs and WES? Regression analysis is defined as a collection of techniques that assesses the relationship between one dependent variable and a few correlated independent variables (Tabachnick and Fidell, 2007). The author of the thesis, started with a simple regression analysis for the relationship between two variables: ‘Increase in sales/turnover’ (section E/WES) and ‘Facebook usage for business’ (Section C/Digital Platforms & ICTs). The interpretation of the results from the regression analysis requires five steps: (1) estimating the regression analysis; (2) test of significance for ß; (3) strength of association of x and y; (4) test of significance for the correlation and (5) drawing the regression line. Table 5.57: Descriptive Statistics Mean

Std. Deviation

Increase in Sales/Turnover

1.23

.421

149

Facebook usage for business

.21

.411

150

Source: F. Tomos, 2016 (SPSS)

This is a simple regression involving two variables, which reports the regression equation as a ‘slope’ (b) and ‘intercept’ (a). According to the terminology used by SPSS version 22, the ‘slope’ of the regression line is called the ‘unstandardised regression coefficient’ (Howitt and Cramer, 1999). (1) In other words, estimates of the intercept and slope of the regression line are presented in the Coefficients table (Table 5.58) under the title ‘Unstandardised Coefficients’.

The unstandardised regression coefficient between

‘increase in sale/turnover’ and ‘facebook usage for business’, presented in column ‘B’ is 0.35. The interpretation of such result is as follows: for every increase of 1.00 on the horizontal axis, the graph changed in the scores on the vertical axis by 0.35. According to the Coefficients table, the 95% confidence interval for this coefficient ranges from 0.19 to 0.50. The ‘intercept’ ‘a’ is referred to as the constant in SPSS version 22. In this study, the constant is equal to 1.154 which is rounded to two decimal places as 1.15 and represents the point where the regression line cuts the vertical Y axis. Further, the 95% confidence interval for the intercept is between 1.08 (1.082) and 1.23 (1.227). Consequently, there is 95% probability that the intercept for the population lies between 1.08 and 1.23. Additionally, the column ß has a value of 0.339, which is the Pearson 207

correlation coefficient between the two variables under analysis. This is called the ‘standardised coefficient’and labelled Beta, in the output of SPSS version 22 (Howitt and Cramer, 1999; Voelkl and Gerber, 1999). Thus, the equation of the least-squares line is as follows: y = 1.15 + 0.35x. Table 5.58: Coefficientsª (to be continued) Model

Unstandardized Coefficients B

Std. Error

(Constant)

1.154

.037

Facebook usage for business

.347

.079

Standardized Coefficients

Beta 31.433 .339

4.365

Source: F. Tomos, 2016 (SPSS)

Table 5.58: Coefficientsª (to be continued) Model 1

Sig.

95.0% Confidence Interval for B Lower Bound

Upper Bound

(Constant)

.000

1.082

1.227

Facebook usage for business

.000

.190

.504

Correlations Zero-order

.339

Source: F. Tomos, 2016 (SPSS)

Table 5.58: Coefficientsª (Finished) Model 1

Correlations Partial

Part

Tolerance

VIF

.339

1.000

(Constant) Facebook usage for business

Source: F. Tomos, 2016 (SPSS) a. Dependent Variable: Increase in Sales/Turnover

(2) Test of significance for ß. Within this phase the study tested the two hypotheses: H0: ß = 0 and H1: ß = 0. The t-statistic is t = 0.35/0.079 = 4.365. The p-value listed under sig. in the table is 0.000 indicating statistical significance for p<0.01 and p<0.05. Consequently, the first hypothesis H0: ß = 0 is rejected and there is a relationship/association between the two variables: ‘increase in sales/turnover’ and ‘facebook usage for business’. (3) The strength of relationship/association of x and y. Referring to the correlation output, the table presented below (Table 5.59), indicate a ‘moderate positive’ relationship

208

between these two variables (r = 0.339) which is statistically significant for sig. = 0.000 (p<0.01). Table 5.59: Correlations

Pearson Correlation

Sig. (1-tailed)

Increase in Sales/Turnover

Facebook usage for business

Increase in Sales/Turnover

1.000

.339

Facebook usage for business

.339

1.000

Increase in Sales/Turnover

.000

Facebook usage for business

.000

Increase in Sales/Turnover

149

Facebook usage for business

149

150

Source: F. Tomos, 2016 (SPSS)

The square of the correlation r² = 0.339² = 0.115 is the proportion of variation in y attributable to x. In other words 11.5% of the variation in increase in sales/turnover is attributable to ‘facebook usage for business’ which is a moderate relationship. This figure is listed under the column entitled R Square in the Model Summary table (Table 5.60). Below, the study presents the following tables: Model Summary and ANOVA (Analysis of Variance) (Tables 5.60 – 5.61A). Table 5.60: Model Summaryb (to be continued) Model

R Square

.339a

Adjusted R Square

Std. Error of the Estimate

.109

.398

.115

Change Statistics R Square Change

F Change

.115

19.052

Source: F. Tomos, 2016 (SPSS)

Table 5.60: Summaryb (finished) Model

Change Statistics

df1

df2

Sig. F Change

147

.000

Source: F. Tomos, 2016 (SPSS) a. Predictors: (Constant), Facebook usage for business b. Dependent Variable: Increase in Sales/Turnover

Table 5.61A: ANOVAª Model 1

Sum of Squares

Mean Square

Sig.

Regression

3.011

19.052

.000b

Residual

23.231

147

.158

Total

26.242

148

Source: F. Tomos, 2016 (SPSS) a. Dependent Variable: Increase in Sales/Turnover b. Predictors: (Constant), Facebook usage for business

209

(4)Test of significance for the correlation. The correlation output introduces a test of the correlation coefficient with two hypotheses: H0: ρ = 0; H1: ρ = 0. From the correlation table the sig. = 0.000, which is below the p-value, p<0.01 (1-tailed). Consequently, there is a statistically significant relationship between these variables.

(5) Drawing the

regression line. The SPSS provided the regression line, which is presented in the figure below (Figure 5.35). In conclusion, ‘there is a positive moderate relationship between Digital Platforms & ICTs * WES’. The results are displayed in the table below (Table 5.61 B).

In the section below the author introduces essential information for the

advancement of this research. Thus, the following section of this chapter discusses the standard multiple regressions. Figure 5.35: The Regression Line

Source: F.Tomos, 2016 (SPSS)

Table 5.61B Regression Analysis NET & ICTs * WES (Facebook usage for business * Increase in Sales)

t 4.365

Sig. 0.000

r 0.339

Source: F. Tomos, 2017 (SPSS)

210

r² 11.5%

Interpretation Significant Moderate Relationship

5.9.4 Standard Multiple Regressions In this section, the author introduced basic information as well as the interpretation of the output for the standard multiple regression. Yockey (2008) argued that the main objective of multiple regressions is to predict the scores on a dependent variable, using scores on two or more independent variables. Also, there are particular requirements regarding the type of data involved in multiple linear regressions. Consequently, it is assumed that the independent variables can be continuous or categorical (nominal/ordinal), whilst the dependent variable must be continuous. Besides these requirements, there is a demand for the formulation of both null and alternative hypotheses for each predictor, or independent variable (Yockey, 2008). According to this author, the analysis is centred on the new created regression equation, as well as on the regression weight (beta weight) for each predictor, to assess whether it is significantly different from zero. If significantly different from zero, the beta weight demonstrates that the independent variable is a significant predictor for the dependent variable. The null hypothesis for each of the predictors is that ‘beta weight is equal to zero’, in other words: H0: ß = 0, the alternative hypothesis is H1: ß = 0. In other words, if the beta weight of Learning (EED) is equal to zero, then Learning does not predict WES. If beta weight of Learning is not equal to zero, then, “Learning predicts WES”.

A second type of

hypothesis required by the multiple regressions is whether the regression equation with all predictors embedded (Learning, Digital Platforms & ICTs), significantly predicts the dependent variable (WES) (Yockey, 2008). Consequently, if the regression is significant, it assumes that, all predictors together, account for a significant amount of variance in the dependent variable. The measure of the variance accounted for is given by R², which ranges from 0 to 1 (R² = 0 indicates that no variance is accounted for by the predictors; R² = 1 indicates that all the variance is accounted for by the predictors). The study also formulates the following regressions equation hypotheses: H0: R² = 0 all the predictors as a whole do not predict women entrepreneurs’ success. H1: R² = 0 all the predictors (Learning and Digital Platforms & ICTs) account for variance in women entrepreneurs’ success. The analysis was carried out with SPSS 22 and the output of the linear multiple regressions displayed a number of tables whose content is explained by the author in the following lines. Thus, the first table included in the output is the ‘Descriptive Statistics’, 211

which presents the mean, standard deviation and the sample size for each variable. The next table is the ‘Correlations table’, displaying the bivariate correlations between all variables in the study. The next table is ‘ANOVA’ used for testing the overall regression for significance. This table assesses whether the regression model with all the predictors significantly predicts the dependent variable. The test is conducted using an analysis of variances. Thus, the p-value less than or equal to 0.05 indicates that the regression model with all the predictors significantly predicts the dependent variable (Yockey, 2008). There is one Model only in ANOVA, because the variables were entered into the equation at once, not separately. Accordingly, the two predictors/or one explain significant variance in the dependent variable (p<0.05) (Voelkl and Gerber, 1999). The last table ‘Coefficients’ tests the individual predictors for significance and provides the necessary values to construct a regression equation and to test each of the predictors for significance (Yockey, 2008).

According to Voelkl and Gerber (1999), the

Coefficients table lists the partial regression coefficients in raw and standardised form. Moreover, each regression coefficient reflects the effect of one variable (the constant) above the other independent variable. Nevertheless, there are various opinions regarding the interpretation of output from the standard multiple regressions. Besides the above interpretations, Pallant (2013) suggests that in order to make sense of the data, there is a requirement to consider the following additional steps: (1) Assessing the assumptions, such as: (a) multicollinearity; (b) outliers, normality, homoscedasticity and independence of residuals; (2) Evaluating the Model; (3) Evaluating each of the independent variables. According to this view, the study approaches and discusses each of these recommended steps. This section discusses only Step (1) Assessing the assumptions, as the other two steps were already discussed above.

The author assesses the correlations between the

independent and dependent variables that should be above 0.300. The next part of the procedure is the assessment of ‘collinearity’. This is introduced in the ‘Coefficient’ table in the columns entitled Tolerance and VIF. Thus, Tolerance is calculated with the formula (1 – R squared) for each variable, and indicates the amount of variability of one independent variable that is not explained by the other independent variable (Pallant, 2013).

If the Tolerance value is less than 0.10, this suggests the presence of

‘multicollinearity’ (Pallant, 2013). The second index provided in the table is VIF, which, stands for ‘variance inflation factor’, is calculated as 1/Tolerance. In other words, this 212

value is the inverse of Tolerance. If the values of VIF are above 10, this would indicate also ‘multicolinearity’ (Pallant, 2013). According to Pallant (2013) if the values for these indices exceed the recommended level, it is suggested that, the highly intercorrelated independent variables should be removed from the model. Besides the assumption of ‘multicollinearity’, the analysis introduces the following assumptions regarding ‘outliers, normality, linearity, homoscedasticity and the independence of residuals. In order to assess these assumptions, the study assesses the Normal Probability Plot (P-P) of the Regression Standardised Residual and the Scatter Plot. According to Pallant (2013), in the Normal P-P Plot, whose points are spread in a straight diagonal line from bottom left to top right, indicates the absence of major deviations from normality. Pallant (2013) argues that deviations from the middle of a rectangle shape indicate the breach of the assumption. Interpretation of the residuals is given by Tabachnick and Fidell (2007). These authors defined outliers as having standardised residual out of the range – 3.3 and + 3.3. However, in order to alter these deviations, the outliers should be removed. Nevertheless, if the plot has only a few residuals, the authors suggest ignoring them (Tabachnick and Fidell, 2007; Pallant, 2013). Step (2) Assessing the Model refers to Model Summary and to R values. Step (3) regards the assessment of the independent variables, which contributed to the prediction of the dependent variable. This information is presented in the ’Standardised Coefficients’ through the value of ‘beta’ (Pallant, 2013). The largest value of beta coefficient (no matter the sign) represents the variable with the largest contribution to the variability in the dependent variable. Additionally, it is recommended to assess also the sig. in order to test whether the variable makes a ‘significant unique contribution’ to the equation (Pallant, 2013). In the lines below, the author presents (1) the total factor extraction, (2) the regression analysis and (3) the correlation analysis based on total factor extraction.

213

5.10 Total Factor Extraction and Analysis & Regression Analysis In this section, the study conducted additional Factor extraction which is used for further investigation, in procedures such as correlations and regressions as well as to test holistically the hypotheses of this thesis (Tabachnick and Fidell, 2007; Pallant, 2013). Although, the factors extracted in the previous sections were interpreted in a meaningful manner, for the benefit of this research and for the enhancement of the analysis, the study needs to produce a second range of factors extracted by SPSS version 22, which are used in correlations and regressions analyses. The extraction technique used is Principal Component Analysis (PCA) and the rotation procedure is Oblimin technique. However, as a result of one fixed factor extraction, the outcome of the analysis does not yield rotated loadings (Pattern and Structure Matrix). The rationale for doing such procedure is in fact a consequence of SPSS limitation in its Factor Analysis mechanics, which does not allow the system to use more than one dependent variable and a few independent variables for the regression and correlation analysis procedures. Consequently, based on the outcomes from the previous Factor Analysis, a single fixed factor is extracted out of ten relevant items for each of the four variables (dependent and independent). These four compressed super variables, or in other words four â&#x20AC;&#x2DC;Total/General Factorsâ&#x20AC;&#x2122; form the components or elements of correlation and regression analyses. There is a substantial difference between the two groups of factors used within this study. Thus, the first group of factors introduced by the previous sections of the chapter, indicates an in depth analysis, helping the interpretation of the meaning of the components, and the labelling of the factors which are determinants for the variance in the dependent variable (DV). The second group provides the means for developing statistics that are able to answer the research questions and to test the hypotheses. This second group of factors allow meaningful interpretation, together with a general compressed perspective of the relationship between the variables of the research. The main details regarding the correlation matrix for each variable/factor, the assessment of the KMO values and the statistical significance for the adequacy of factorability of the correlation matrix, are provided in the tables below (Tables 5.62 â&#x20AC;&#x201C; 5.65).

The total factor analysis is based on ten relevant items selection and the ratio

employed for the factor analysis is 4:1 (150:40). In addition to the main variables, the research introduces and tests another element component of the Conceptual Model: CoPs & networking.

214

Total Factor Analysis for Learning (EED) Table 5.62: KMO and Bartlett’s Test, TFA EED Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity

Approx. Chi-Square df

.637 403.762 45

Sig.

.000

Source: F. Tomos, 2016 (SPSS)

Total Factor Analysis for Digital Platforms & ICTs (NET & ICTs) Table 5.63: KMO and Bartlett’s Test, TFA NET Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity

Approx. Chi-Square df

.746 331.623 45

Sig.

.000

Source: F. Tomos, 2016 (SPSS)

Total Factor Analysis for Communities of Practice (CoPs & Networking) Table 5.64: KMO and Bartlett’s Test, TFA CoPs & Networking Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity

Approx. Chi-Square df

.954 1907.291 45

Sig.

.000

Source: F. Tomos, 2016 (SPSS)

Total Factor Analysis for Women Entrepreneurs’ Success (WES) Table 5.65: KMO and Bartlett’s Test, TFA WES Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity

Approx. Chi-Square df

.833 576.054 36

Sig.

.000

Source: F. Tomos, 2016 (SPSS)

215

Table 5.66: Assessment of suitability of data for Total Factor Analysis R values KMO High loadings % of for Sig. = Bartlett test values/Component Variance 0.000 sig. = 0.000 Matrix Explained Total Factor (1) The usage of 0.339 – 0.637 25.3 Analysis networking 0.839 Learning (0.913); (TFAEED) (2) Learn from information, participation, sharing (0.900) Total Factor (1) Mobile 0.344 – 0.746 32.3 Analysis Digital applications usage 0.536 Platforms & ICTs for business (TFANET) (0.667); (2) Twitter usage for business (0.636) Total Factor (1) Laptops and 0.576 – 0.954 79.5 Analysis CoPs & computers help 0.942 Networking CoPs (0.962); (TFACPN) (2) Mobile phones help CoPs (0.947) Total Factor (1) Digital 0.308 – 0.833 48.1 Analysis Women Platforms & ICTs 0.729 Entrepreneurs’ affect business Success success (0.801); (TFAMSC) (2) Facebook affects business success (0.775) Source: F. Tomos, 2016 (SPSS); Note: ICTs – Information Communication Technologies; NET – Digital Platforms; CoPs – Communities of Practices; WES – Women Entrepreneurs’ Success

The sample size is N = 150 which according to Pallant (2007) is sufficient and meets the requirements of sample size mentioned by the author.

The strength of the inter-

correlations between the items of the variables, indicated by the correlation matrix, shows coefficients greater than 0.300 (Table 5.66) (Tabachnick and Fidell, 2007). Further statistical measures such as Kaiser-Meyer-Olkin (KMO) and Bartlett’s test of sphericity (Sig. = 0.000) which is significant for p<0.05 (Kaiser, 1970, 1974; Bartlett, 1954; Pallant, 2007; Pallant, 2013) (Table 6.8) demonstrate that one factor extraction is appropriate solution for the analysis. Factor extraction in this case, is based only on Kaiser’s criterion, which requires Eigenvalues above 1.00 and does not consider the Scree test (Pallant, 2007). Furthermore, as a result to one factor extraction, which is used for statistical reason and for the purpose of the research, there is no assessment of factor rotation and

216

interpretation, as the system SPSS did not produce the Pattern and Structure Matrix, but only the Component Matrix. 5.10.1 Multiple Standard Regression Analysis This section of the chapter tests the following hypotheses: H2: ‘TFAEED has a positive impact on TFAMSC’; H3: ‘TFANET have a positive impact on TFAMSC’; H1: ‘There is a significant relationship between TFAEED, TFANET and TFAMSC’. As a result of compressing the factors, by factor extraction technique, and for the purpose of the research, the hypotheses are expressed in terms of Total Factor Analysis and in relation to each corresponding variable. These are followed by the adequate interpretations of the outcomes of the analysis. In other words, the multiple standard regression analysis and the correlation analysis sections that follow are based on the Total Factor Extraction and Analysis from the previous section. For this analysis, the author used SPSS version 22 Regression and Explore. In order to conduct multiple regression analysis, the author needs to execute a few assessments. (1) The first assessment is with regard to sample size, followed by the assessment of the assumptions.

According to

Tabachnick and Fidell (2007) the size of the sample should be N > 50 + 8 x m (m = number of independent variables). The minimum sample size for two independent variables should be more than 60 cases. In this study, N = 150 cases, with N = 148; 149 valid cases, which exceeds the minimum required in order for the results to be recommended for generalisation. Because the research includes within the analysis, CoPs & networking, as the controlled variable (CoPs with ten sub-variables) then, the study has a ratio of 4:1 (150:40). This is acceptable according to Tabachnick and Fidell (2007). Further, it is advisable that the correlation between the dependent and the independent variable should be r > 0.300. Thus, according to the table below (Table 5.67), if we consider the absolute values of the correlation, there is a significant strong correlation between TFANET and TFAMSc. Nevertheless, there is a significant negative strong correlation, with r = -0.505 (sig. = 0.000, for p<0.01), between TFANET (Total Factor Analysis Digital Platforms & ICTs) and TFAMSc (Total Factor Analysis Women Entrepreneurs’ Success), and a significant negative correlation, with r = -0.2 (-0.197, sig. = 0.008 for p< 0.05), between TFAMSc (Women Entrepreneurs’ Success) and TFAEED (Total Factor Analysis Learning), for N = 148 valid cases. There is also a strong inter217

items correlation (between the IVs) indicated by r = 0.403, between TFAEED and TFANET (Digital Platforms & ICTs and Learning). Table 5.67: Correlations

Pearson Correlation

Sig. (1-tailed)

Total FAMSc 1FX nine items

Total FA EED 1FX ten items

Total FA NET 1FX ten items

Total FAMSc 1FX nine items

1.000

-.197

-.505

Total FA EED 1FX ten items

-.197

1.000

.403

Total FA NET 1FX ten items

-.505

.403

1.000

Total FAMSc 1FX nine items

.008

.000

Total FA EED 1FX ten items

.008

.000

Total FA NET 1FX ten items

.000

Total FAMSc 1FX nine items

149

148

149

Total FA EED 1FX ten items

148

149

Total FA NET 1FX ten items

149

150

Source: F. Tomos, 2016 (SPSS)

(2) The second assessment regards the multicollinearity and singularity. Pallant (2007) defines multicollinearity as the high level of correlations between the independent variables (r = 0.9 and above). Singularity happens when an independent variable is a synthesis of two or more independent variables (Pallant, 2007). Information about collinearity is provided in the ‘Coefficient’ table under two columns: Tolerance and variance inflation factor (VIF). Thus, in this study, Tolerance = 0.837 and VIF = 1.2. According to Pallant (2013) if the Tolerance is < 0.10 and VIF > 10 indicates multiple correlations with other variable of greater values and the presence of multicollinearity, which is not our case. Consequently, the study does not have multicollinearity and singularity. It follows that the study can proceed with further analysis. These details could be observed in the table provided below (Table 5.68): Table 5.68: Coefficientsª Model

Correlations Partial

Part

Tolerance

VIF

Total FA EED 1FX ten items

.009

.008

.837

1.194

Total FA NET 1FX ten items

-.475

-.466

.837

1.194

(Constant)

Source: F. Tomos, 2016 (SPSS) a. Dependent Variable: Total FAMSc 1FX nine items

The second assessment is with regard to outliers, normality, homoscedasticity and the independence of residuals. Pallant (2007) defines ‘normality’ in relationship to the 218

dependent variable and refers to a normal distribution of the residuals, whilst linearity is referring to a linear relationship.

Homoscedasticity is also, in relationship to the

dependent variable and is referring to a consistent variance of the residuals (Pallant, 2007). Moreover, when referring to homoscedasticity, there should be a similarity in the spread of scores for both variables, or, even more, their general shape should either be a rectangular shape or a cigar shape (Pallant, 2007, 2013; Tabachnick and Fidell, 2007). Residuals outside of the defined range -3 to +3 are defined as outliers (Pallant, 2013). From the Normal P-P Plot of Regression Standardised Residual and from the Scatterplot of Residual and Predicted Value of dependent variable (TFAMSC), it is deducted that, there are no deviations, and the scores are spread in almost a straight diagonal line from bottom left to top right, showing normality with 1% outliers which is acceptable (Pallant, 2013). Evidence is provided by the study within the following Graph with Normal P-P Plot Regression and Scatterplot of DV (Figures 5.36; 5.37): Figure 5.36: Normal P-P Plot of Regression, TFA MSc

Source: F. Tomos, 2016 (SPSS)

219

Table 5.37: Scatterplot, TFA MSc

Source: F. Tomos, 2016 (SPSS)

Finally, the study also meets the requirement of homoscedasticity, which is given by a normal rectangular shape distribution of the residuals between -3 to +3 on both axes (Pallant, 2013; Tabachnick and Fidell, 2007). (3) Further assessment was conducted on the Model and on each of the independent variables (TFANET and TFAEED) (Pallant, 2013). The following are the phases of this assessment. The first phase of the second assessment: (1) the formulation of the null and alternative hypothesis for each predictor /independent variable (IV): H0:‘Beta weight for TFAEED = 0’, (the first independent variable) – ‘TFAEED does not predict TFAMSc’ H1:‘Beta weight for TFA EED = 0’, (the first independent variable) – ‘TFAEED predicts TFAMSc’ H0:‘Beta weight for TFANET = 0’, (the second independent variable) – ‘TFANET does not predict TFAMSc’ H1:‘Beta weight for TFANET = 0’, (the second independent variable) – ‘TFANET predicts TFAMSc’ The author needed to find out which of the independent variables contributed to the prediction of the dependent variable. This information is provided by the Coefficients table, under the column ‘Standardised coefficients’ by the value of beta. The largest beta value is given by TFANET, ß = -0.509. For sig. = 0.000, with p-value < 0.05. This variable (Digital Platforms & ICTs – TFANET) makes the strongest unique contribution 220

to justifying the dependent variable (Women Entrepreneurs’ Success – TFAMSc). The beta value for the second independent variable (TFAEED) is a very low value, ß = 0.009 with sig. > 0.05 and with no unique contribution to the prediction of the dependent variable (Women Entrepreneurs’ Success – TFAMSc). In conclusion, both alternative hypotheses were confirmed, ß = 0. However, whilst TFANET variable has the largest unique significant contribution in explaining the variance in the dependent variable (DV) (TFA MSc), the second independent variable TFAEED has a weak no significant contribution to justifying the variance in the DV. The information is provided below (Table 5.69): Table 5.69: Coefficientsª (to be continued) Model

Unstandardized Coefficients

Standardized Coefficients

Std. Error

Beta

(Constant)

.000

.071

Total FA EED 1FX ten items

.009

.078

.009

.110

Total FA NET 1FX ten items

-.509

.078

-.509

-6.496

.000

Source: F. Tomos, 2016 (SPSS) Dependent Variable: Total FAMSc 1FX nine items;Total FAMSc – Total Factor Analysis Women Entrepreneurs’ Success; Total FA EED – Total Factor Analysis Learning; Total FA NET – Total Factor Analysis Digital Platforms & ICTs

Table 5.69: Coefficientsª (finished) Model

Sig.

95.0% Confidence Interval for B Lower Bound

Upper Bound

Correlatio ns Zeroorder

(Constant)

1.000

-.141

.141

Total FA EED 1FX ten items

.912

-.146

.163

-.197

Total FA NET 1FX ten items

.000

-.664

-.354

-.505

Source: F. Tomos, 2016 (SPSS) Dependent Variable: Total FAMSc 1FX nine items

(4) The last phase of the regression analysis consists of assessing the Model. This is a second type of Hypothesis required by the multiple regression method. According to Yockey (2008) this hypothesis should test whether the regression equation for this time, together with the independent variables (as predictors), significantly predict the dependent variable. The measure for variance here is provided in the table ‘Model Summary’ by R values. First, the author needed to formulate the null and alternative hypothesis regarding R value: 221

H0: R² = 0, ‘There is no variance accounted for by the regression equation’ – the entire model – regression equation and both independent variables/predictors (TFANET and TFAEED) do not predict the dependent variable (TFAMSc), do not account for variance in the dependent variable; H1: R² = 0 ‘There is variance accounted for by the regression equation’ - the entire model – regression equation and predictors account for the variance in the dependent variable (TFA MSc). R² = 0.255 = 0.26, R² x 100 = 26% of the total variance in the dependent variable (TFAMSc) accounted for by all the predictors embedded in the regression equation. H1 is confirmed and as a result, there is a variance accounted for by the regression equation and the independent variables. This is a large percentage of variance (26%) determined by the independent variables and the regression equation within the dependent variable (positive/negative) (Yockey, 2008). These figures are provided in the table below (Table 5.70): Table 5.70: Model Summaryb Model

.505a

R Square

Adjusted R Square

Std. Error of the Estimate

.255

.245

.86885518

Change Statistics R Square Change

F Change

.255

24.863

Source: F. Tomos, 2016 (SPSS) a. Predictors: (Constant), Total FA NET 1FX ten items, Total FA EED 1FX ten items b. Dependent Variable: Total FAMSc 1FX nine items

Finally, the ANOVA table (Table 5.71) provided below, assesses the overall regression for significance. In other words it tests whether the entire model predicts the dependent variable (Yockey, 2008). This test consists of the analysis of variance. Thus, Sig. = 0.000 which is less than p-value, where p < 0.05. In other words, the p-value is less than or equal to 0.05, indicates that the regression model with all the predictors significantly predicts the dependent variable (Yockey, 2008). This confirms that the model predicts the dependent variable and accounts for the variance in TFAMSc (WES). Tables 5.71: ANOVAª Model 1

Sum of Squares

Mean Square

Sig.

Regression

37.538

18.769

24.863

.000b

Residual

109.462

145

.755

Total

147.000

147

Source: F. Tomos, 2016 (SPSS) a. Dependent Variable: Total FAMSc 1FX nine items

222

b. Predictors: (Constant), Total FA NET 1FX ten items, Total FA EED 1FX ten items

In addition to the above, the study provides information regarding the matrix of scatterplots (Figures 5.38 â&#x20AC;&#x201C; 5.39): Figure 5.38: Scatterplot, Matrix: TFAEED, TFAMSc, TFANET (a11/positive)

Source: F. Tomos, 2016 (SPSS)

Figure 5.39: Scatterplot, Matrix: TFA EED, TFA MSc (negative)

Source: F. Tomos, 2016 (SPSS)

223

Table 5.40: Scatterplot, Matrix: TFA NET, TFA MSc (negative)

Source: Author, 2016 (SPSS)

According to results of the analysis, ‘Digital Platforms & ICTs have an impact on WES’. However, their impact upon women entrepreneurs is negative.

Consequently, H3

becomes: H3: ‘Digital Platforms & ICTs have a significant impact on WES’ Consequently, H3 is half confirmed, and half supported, by the results of the analysis. Following previous FA, the following are Digital Platforms & ICTs with impact upon WES: mobile applications for business; twitter usage for business, facebook; internet connection and search engine for business and learning; learning and doing business with You Tube. H1: ‘There is a significant relationship between Digital Platforms & ICTs, Learning and WES’ Consequently, H1 is confirmed, and supported, by the results of the analysis. The correlation analysis considers the size of the effect and this is provided by the absolute value of r = 0.505. From the scatterplot and the negative value of Pearson coefficient (r = -0.500), it is certainly a negative direction and trend. The results are contradictory, opposing the results from earlier sections. However, the regression equation and the

224

predictors of the model – TFANET & TFAEED, account for 26% (large percentage of variance) of the total variance in the dependent variable – TFAMSc/WES. H2: ‘Learning has a positive impact on WES’ As a consequence of the last analysis, H2 is half supported and needs further investigation.

In order to have an in-depth interpretation as well as, a correct

understanding of the results, the author of this thesis undertakes also, a qualitative analysis. 12.11 Correlation Analysis H4: ‘There is a correlation between TFAEED, TFANET and TFAMSC’ The author conducted a preliminary analysis upon the scores within the scatterplot and assessed the linearity and the homoscedasticity for the variables under analysis. Thus, according to Pallant (2007; 2013), the scatterplot displayed roughly linearity and a rectangular shape in the distribution of the scores. The scores that are outside of the main group or cluster are called outliers. In this case, the scatterplot shows one single case outside of the range -3 to +3, which according to Pallant (2013) is acceptable. This provides evidence of the existence of a relationship between the variables: TFANET (Total Factor Digital Platforms & ICTs), TFAEED (Total Factor Analysis Learning) and TFAMSc (Total Factor Analysis Women Entrepreneurs’ Success). Following the preliminary analyses, the author first assesses and discusses whether there is a correlation between the independent variable TFAEED and the dependent variable TFAMSc, and the direction and the strength of this relationship. The evidence in this case is provided by the correlation coefficient, which needs to exceed 0.300 (Pallant, 2007). The descriptive statistics shows the number of valid cases N = 149. Because the sample can be considered in Pallant’s opinion (2007) as a large sample, then the value of 0.197 (almost 0.200) is displayed by the outcome of SPSS in the ‘Correlation Matrix’ as a significant value. Consequently, r = - 0.197, with Sig. = 0.01 for p-value, p<0.05 level (1-tailed), indicates a significant negative correlation between the two variables. Further details are provided below (Tables 5.72; 5.73): Table 5.72: Correlations (Pearson Correlation), TFAEED Total FAMSc 1FX nine items

Pearson Correlation Sig. (1-tailed)

Total FAMSc 1FX nine items

Total FAEED 1FX ten items

-.197** .008

225

N Total FA EED 1FX ten items

Pearson Correlation

149

148

-.197**

Sig. (1-tailed)

.008

148

149

Source: F. Tomos, 2016 (SPSS) **. Correlation is significant at the 0.01 level (1-tailed).

Table 5.73: Correlations (Spearman’s rho), TFA EED

Spearman's rho

Total FAMSc 1FX nine items

Total FA EED 1FX ten items

1.000

-.226**

.003

149

148

-.226**

1.000

Sig. (1-tailed)

.003

148

149

Correlation Coefficient Sig. (1-tailed) N

Total FA EED 1FX ten items

Correlation Coefficient

Source: F. Tomos, 2016 (SPSS). **Correlation is significant at the 0.01 level (1-tailed).

The second correlation under analysis is between the independent variable TFANET (Total Factor Analysis – Digital Platforms & ICTs) and the dependent variable TFAMSc (Total Factor Analysis - Women Entrepreneurs’ Success). Preliminary analyses were conducted, and the results indicate linearity and homoscedasticity for the variables under research. Moreover, there are no major deviations, in other words the scatterplot does not show major outliers. Therefore, the author proceeded to the next phase of correlation analysis.

Further, the outcome from the first phase demonstrates the existence of a

relationship between the two variables. The ‘Descriptive Statistics’ table shows a different number of valid cases for each variable. Thus for the dependent variable (TFAMSc) N = 149, whilst for the independent variable (TFANET) N = 150 cases. The ‘Correlations’ table shows r = - 0.505, with Sig. = 0.000, for p-value, p<0.01 (1-tailed), indicating a strong negative significant correlation between these two variables. Further details are provided in the table below (Tables 5.74; 5.75): Table 5.74: Correlations (Pearson Correlation), TFA NET Total FAMSc 1FX nine items

Pearson Correlation

Total FANET 1FX ten items

-.505**

Sig. (1-tailed)

.000

N Total FA NET 1FX ten items

Total FAMSc 1FX nine items

Pearson Correlation Sig. (1-tailed)

149

-.505**

.000

226

149

150

Source: F. Tomos, 2016 (SPSS) **. Correlation is significant at the 0.01 level (1-tailed).

Table 5.75: Correlations (Spearman’s rho), TFA NET

Spearman's rho

Total FAMSc 1FX nine items

Total FA NET 1FX ten items

1.000

-.471**

.000

149

-.471**

1.000

Sig. (1-tailed)

.000

149

150

Correlation Coefficient Sig. (1-tailed) N

Total FA NET 1FX ten items

Correlation Coefficient

Source: F. Tomos, 2016 (SPSS). **Correlation is significant at the 0.01 level (1-tailed).

A third analysis was conducted on the relationship between the dependent variable (TFAMSc) and both independent variables (TFANET, TFAEED). The tables below provided two types of correlation coefficients: Pearson’s coefficient and Spearman’s rho coefficient. For an enhanced interpretation, the author of this thesis considered both values and offered two types of interpretation. The rationale of this choice is the fact that, within the ten selected items for factor extraction, there are two types of data: scale data and nominal/categorical data. It is indeed a matter of interpretation, whether, one can also consider Spearman’s rho coefficient. There is a low percent of nominal data, which implies the use of Spearman’ rho coefficient for the analysis. There are significant correlations between the three variables, results which enforce and confirm the outcomes obtained within the two analyses from above tables r = -0.197 and r = -0.505, Sig. = 0.008 (p-value, p<0.01) and Sig. = 0.000 (p<0.01) (1-tailed). In addition to these correlations, the ‘Correlation’ table offers another type of relationship, that between the two independent variables (TFAEED and TFANET), indicated by r = 0.403, Sig. = 0.000, p<0.01, (1-tailed), which is a strong positive significant correlation. These outcomes are confirmed by Spearman’s rho coefficient. Further details are provided below (Tables 5.76; 5.77): Table 5.76: Correlations (Pearson Correlation), TFAMSc, TFAEED, TFANET

Total FAMSc 1FX nine items

Total FANET 1FX ten items

Total FAEED 1FX ten items

-.505**

-.197**

.000

.008

Pearson Correlation Sig. (1-tailed)

227

N Total FA NET 1FX ten items

Total FA EED 1FX ten items

Pearson Correlation

149

148

-.505**

.403**

Sig. (1-tailed)

.000

149

150

149

-.197**

.403**

Sig. (1-tailed)

.008

.000

148

149

Pearson Correlation

.000

149

Source: F. Tomos, 2016 (SPSS) **. Correlation is significant at the 0.01 level (1-tailed).

Table 5.77: Correlations (Spearman’s rho)

Spearman's rho

Total FAMSc 1FX nine items

Total FA NET 1FX ten items

Total FA EED 1FX ten items

1.000

-.471**

-.226

.000

.003

149

148

-.471**

1.000

.383**

Sig. (1-tailed)

.000

149

150

149

-.226**

.383**

1.000

Sig. (1-tailed)

.003

.000

148

149

Correlation Coefficient Sig. (1-tailed) N

Total FA NET 1FX ten items Total FA EED 1FX ten items

Correlation Coefficient

149

Source: F. Tomos, 2016 (SPSS); **Correlation is significant at the 0.01 level (1-tailed)

In conclusion, H4 is confirmed by the analysis: H4: ‘There is a correlation between TFAEED, TFANET and TFAMSc’ In addition, the analysis discovered another relationship: ‘There is a moderate positive significant correlation between TFAEED and TFANET’ (r = 0.403; sig = 0.000, p-value < 0.01 (1-tailed)). 5.12 Partial Correlation Analysis In order to enhance the interpretation and to test the Conceptual Research Framework from the first part of the thesis, the author conducted a partial correlation analysis. Thus, two types of relationships with the impact of CoPs & networking (TFACPN) as a controlled variable were analysed. Firstly, there was an analysis on the relationship between each of the independent variables: TFAEED (Learning) and TFANET (Digital 228

Platforms & ICTs) and the dependent variable TFAMSc (Women Entrepreneurs’ Success), when controlled by the variable TFACPN (Communities of Practices & networking). More details are provided in the tables below (Tables 5.78 – 5.81): Table 5.78: Descriptive Satistics (TFAEED, TFAMSc, TFACPN) Mean

Std. Deviation

Total FA EED 1FX ten items

-.0006625

.99993960

149

Total FAMSc 1FX nine items

.0000000

1.00000000

149

Total FA CPN 1FX ten items

.0005064

1.00088411

147

Source: F. Tomos, 2016 (SPSS)

Table 5.79: Correlations (TFAEED, TFAMSc, TFACPN) Control Variables

Total FA CPN 1FX ten items

Total FA EED 1FX ten items

Total FAMSc 1FX nine items

1.000

-.091

Significance (1-tailed)

.138

143

Correlation

-.091

1.000

Significance (1-tailed)

.138

143

Correlation

Total FAMSc 1FX nine items

Source: F. Tomos, 2016 (SPSS)

Table 5.80: Descriptive Statistics (TFANET, TFAMSc, TFACPN) Mean

Std. Deviation

Total FAMSc 1FX nine items

.0000000

1.00000000

149

Total FA NET 1FX ten items

.0000000

1.00000000

150

Total FA CPN 1FX ten items

.0005064

1.00088411

147

Source: F. Tomos, 2016 (SPSS)

Table 5.81: Correlations (TFANET, TFAMSc, TFACPN) Control Variables

Total FACPN 1FX ten items

Total FAMSc 1FX nine items

Total FA NET 1FX ten items

Total FAMSc 1FX nine items

Total FA NET 1FX ten items

1.000

-.448

Significance (1-tailed)

.000

144

Correlation

-.448

1.000

Significance (1-tailed)

.000

144

Correlation

Source: F. Tomos, 2016 (SPSS)

229

Secondly, there was an analysis upon the relationship between the two independent variables (TFAEED and TFANET) together the dependent variable (TFAMSc) when controlled by the variable TFACoPs. The results demonstrated that TFACPN has a significant impact upon both independent variables and the dependent variable. This was demonstrated by the drop down in the value of the correlation coefficient. For instance, the correlation value was r = - 0.197 compared to r = -0.091, when TFACPN is a controlled variable for the relationship between TFAEED and TFAMSc. TFACPN is also a controlled variable for the relationship between TFANET and TFAMSc. For instance, previously r = - 0.505, whilst when the relationship was controlled by TFACNP, the value of r was lower, r = - 0.448. Consequently, TFACPN is a control variable, affecting the relationship between TFANET * TFAMSc, as well as for the relationship between the following variables: TFAEED * TFAMSc. Following the analyses of this chapter the author provides a Summary chapter and a table with the summary of the research hypotheses, statistical analysis and the results (Satiropoulos, 2014). 5.13 Summary Chapter This chapter comprised an introduction, descriptive statistics, a section on displaying and summarizing categorical and scale variables, and a section on inferential statistics, together with essential information on the concepts of reliability and validity in measurements. The chapter highlighted the information regarding the role and importance of knowing and differentiating between the types of variables, such as categorical (nominal and ordinal) and scale. A fair knowledge about these is essential in selecting the appropriate statistical tests and analysis. The chapter allocated space for various perspectives upon the concepts of reliability and validity for the scale variables and their role in providing accurate and valid results to the audience of this research. Following this introduction, the chapter approached a range of relationships between the types of variables and provided appropriate statistical analyses.

For the analyses of the

relationship, the authors used cross tabulations, Chi Square test and Spearman correlation coefficient. The analyses of various relationships between variables and the knowledge of the significance test, correlations and partial correlations supported the author in designing the final model emerging from the analysis of quantitative data. Next, the author proceeded to inferential statistics. In this regard, the author introduced Factor Analysis, followed by factorisation of the main four variables of the research: Learning, 230

Digital Platforms & ICTs, CoPs & networking and WES.

The chapter also contains

factor extraction procedure and analyses for each variable, the emergence of the super variables and their analyses with the following statistics: simple regression, multiple standard regression analysis, correlation analysis and partial correlation analysis. The chapter excels by using an exploratory method, which enhanced the opportunities of an in-depth and meaningful interpretation of the results of the analysis.

The chapter

answered the main research questions and tested the hypotheses. The table below (Table 5.82) is inspired from Satiropoulos (2014) and presents a valuable summary of the research hypotheses, research questions, statistical analyses and the results. This is followed by hypotheses redefined, according with the outcomes from the quantitative data analyses (Table 5.83A) and a theoretical model (Figure 5.41), entitled â&#x20AC;&#x2DC;A Theoretical Business Model for Women Entrepreneursâ&#x20AC;&#x2122; Successâ&#x20AC;&#x2122;, which is based mainly on the findings from quantitative data analysis. The author improves the model, by adding the findings from qualitative data analysis and building a final robust theoretical model. Finally, the chapter closes with the new emergent hypotheses from this analysis, and recommended for further research (Table 5.83B).

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Table 5.82: Summary of the Research Hypotheses & Research Questions. Statistical Analysis and Results, TFA Hypotheses/RQ Outcomes Statistics Results RQ1: What is the impact of Learning and Digital Platforms & ICTs on Women Entrepreneurs’ Success, in the context of CoPs & networking? RQ6: What is the Role of CoPs & networking? Hypothesis 2: Exploratory Descriptive Statistics 79.7% of 149 Learning has a Supported. valid cases positive impact on TFA, Half answered WES. Supported ‘Learning (Redefine Simple regression analysis enhances Redefined: hypothesis) Factor Analysis & business ‘Learning impacts Extraction success’; on WES’ Multiple Standard r=-0.197, Regression Analysis sig.=0.008, H2.1: ‘The Impact Exploratory (MSRA) p<0.05 of Learning on WES Supported Requirement: is controlled by ß=0 CoPs & networking’ Consequently:ß1 =-0.009;p>0.05 TFA EED predicts DV (TFA MSc) Hypothesis 3: Exploratory Descriptive Statistics 90% of 150 valid Digital Platforms & Supported. cases answered: ICTs have a positive TFA, Half ‘Digital impact on WES. Supported Platforms & (Redefine Simple regression analysis ICTs enhance Redefined: hypothesis) business ‘Digital Platforms & Factor Extraction success’; ICTs have a Multiple Standard r=-0.505, significant impact Regression Analysis sig.=-0.009, on WES’. (MSRA) p>0.05 ß2=-0.509, H3.1: ‘The Impact Supported sig.=0.000, of Digital Platforms p<0.05 & ICTs on WES is TFA NET controlled by CoPs predicts DV & networking’ (TFA MSc) RQ2: Is there a significant relationship between Learning, Digital Platforms & ICTs and Women Entrepreneurs’ Success? Hypothesis 1: Supported Total Factor Extraction & Significant There is a Analysis strong significant Multiple Standard relationship relationship between Regression Analysis Equation & Learning, Digital (MSRA): predictors Platforms & ICTs ‘TFA EED * TFA NET * account for 26% and WES. TFA MSc’ of total variance in DV 232

Sub-Hypothesis 1a: Supported ‘There is a significant relationship between Learning and WES’.

Chi-Square test Pearson Chi-Square Cramer V (Nominal variables)

Cross tabulation/ contingency table Spearman Correlation Multiple Standard Regression: ‘TFA EED * TFA MSc’ Total Factor Extraction & Analysis

Sub-Hypothesis 1b: Supported There is a significant relationship between Digital Platforms & ICTs and WES.

Pearson’ R (Scale variables)

Simple regression analysis

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ß1=0.509, ß2=0.009, sig.=0.000, p<0.05 TFA NET -‘strong unique contrib.’ to DV R²=0.26, EQ & PRCTS - 26% to DV. -Value = 10.89; sig. 0.004, p<0.05 -V = 0.271 -Effect size = small -Significant moderate relationship -86.9% of 148 valid cases: ‘yes’ ‘learn from information & sharing’, agreed ‘yes’ ‘EED enhances business success’ -rho=0.209, sig.=0.05, p<0.05, 1-tailed -r=-0.197, sig.=0.008 P<0.05 (r absolute value= 0.197) significant moderate correlation -R=0.197-0.386 -Sig. = 0.0070.000; p<0.05 -Significant moderate relationship ß=0.339,sig.=0.0 00, p<0.01&0.05 r=0.339, r²=11.5%

Multiple Standard Regression Analysis: ‘TFA NET * TFA MSc’ Total Factor Extraction & Analysis

variation in sales attributable to NET -r=-0.505 (r absolute value=0.505), sig.=0.000, p<0.05 ‘significant strong correlation’ RQ4: Are there correlations between Learning, Digital Platforms &ICTs and Women Entrepreneurs’ Success? Hypothesis 4: Supported Total Factor Extraction & r=-0.505, ‘There is a Analysis sig.=0.000, correlation between p<0.01 (1-tailed), Correlation Analysis after Learning, Digital r=-0.197, Factor Extraction Platforms & ICTs sig.=0.008,p<0.0 Pearson Correlation and WES’. 1 (1-tailed) Spearman Correlation r=0.403, Scatterplot sig.=0.000 Homoscedasticity p<0.01, (1-tailed) Linearity Sub-Hypothesis 4a: ‘There is a correlation between Learning and WES’.

Supported

Sub-Hypothesis 4b: ‘There is a correlation between Digital Platforms & ICTs and WES’.

Supported

Total Factor Extraction & Analysis Correlation Analysis after Factor Extraction Pearson Correlation Spearman Correlation Scatterplot Homoscedasticity Linearity Correlation Analysis

Total Factor Extraction & Analysis Correlation Analysis after Factor Extraction Pearson Correlation Spearman Correlation Scatterplot Homoscedasticity Linearity

Source: F. Tomos, 2019 (Inspired from Satiropoulos, 2014)

234

r=-0.197, sig.=0.008, p<0.01, (1-tailed) rho=0.226, sig.=0.003, p<0.01, (1-tailed) ‘significant moderate relationship’ r=0.28-0.36, sig.=0.000, r²= 7.9% - 12.9%, p<0.01, (1-tailed) Acc for variance in DV r=-0.505, sig.=0.000, pvalue<0.01 (1tailed); rho=-0.471, sig.=0.000, p<0.01, (1tailed) ‘significant strong relationship’

HYPOTHESES RESULTED FROM THE QUANTITATIVE ANALYSIS TFA AND EXPLORATORY APPROACH Table 5.83A: Emergent Hypotheses Thesis Hypotheses/ Emergent Sub-Hypotheses Emergent Hypotheses Hypothesis1: There is a significant Hypothesis1a: There is a significant relationship between Learning, Digital relationship between Learning and WES. Platforms & ICTs and WES. Hypothesis1b: There is a significant relationship between Digital Platforms & ICTs and WES. Hypothesis 2: Learning has a positive Hypothesis2a: The impact of Learning on impact on WES. WES is controlled by CoPs & networking. Redefined H2: Learning impacts on WES. Hypothesis3: Digital Platforms & ICTs Hypothesis3a: The impact of Digital have a positive impact on WES. Platforms & ICTs on WES is controlled Redefined H3: Digital Platforms & ICTs by CoPs & networking. have a significant impact on WES. Hypothesis4: There is a correlation Hypothesis4a: There is a correlation between Learning, Digital Platforms & between Learning and WES. ICTs and WES. Hypothesis4b: There is a correlation between Digital Platforms & ICTs and WES. Hypothesis5: There are relationships Table 4.56B, Table 4.55 between Digital Platforms & ICTs and WES. Hypothesis6: There are relationships Table 4.56B, Table 4.55 between Digital Platforms & ICTs and CoPs & networking. Hypothesis 7: There is a strong Hypothesis 7a: There is a strong correlation between CoPs & networking * correlation between ‘Twitter helps WES. participation in CoPs * Increase in Sales’. Hypothesis 8: There is a significant Hypothesis 8a: There is a significant moderate correlation between Learning * moderate correlation between ‘Increase WES. in Sales * Usage of NET & ICTs’. Source: F. Tomos, 2016, 2017, 2019 (based on SPSS analysis), Tables 4.55; 4.56B; 4.27; 4.28; Figure 4.30B.

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THEORETICAL MODEL Figure 5.41: Theoretical Business Model for Women Entrepreneurs’ Success (Emergent from Quantitative Data Analysis)

Learning

-Learning through Networking & CoPs by participation, communication and sharing information -Preferences for styles of learning -Type of knowledge acquired -Methods of learning -Type of learner

Women Entrepreneurs’ Success

-Digital Platforms & ICTs (Laptops, PC, Mobile Phones, Tablets) -Social Media (Twitter&Facebook) -Learning determine business success

3 8 2

7 6

Digital Platforms & ICTs

5 -Digital Platforms & ICTs for business -Social Media for business (Facebook & Twitter) -Mobile applications usage for business -Internet & search engines for business and learning -YouTube for business & learning

CoPs & networking -Digital Platforms help participation in CoPs & Networks (Laptops, PC, Mobile Phones) -Social Media helps CoPs & Networks (Twitter & Facebook)

236

Table 5.83B: New Relationships/Hypotheses emergent from the quantitative analysis New Statistics & Outcome Allocated number Hypothesis/Relationship from the Emerged Theoretical Model CoPs & networking * Chi Square = 56.69; (6) Women Entrepreneurs’ sig.=0.001; p<0.05; Cramer’s Success V=0.31, sig.=0.000, p<0.05; (D/Q3; E/Q11) ‘medium size effect’, ‘moderate relationship. Categorical variables. CoPs & networking * Spearman Correlation, (4) Learning rho=0.215, sig.=0.008, p<0.01 (B/Q12; D/Q3) Significant positive relationship Categorical variables CoPs & networking* Digital Pearson’s R; R=0.310-0.406, (5) Platforms & ICTs sig. =0.000, significant (D/Q4; C/Q1) moderate relationship. Scale variables Digital Platforms & ICTs * Chi Square Test=18.8; (5) CoPs & networking sig.=0.000, p<0.05; Cramer’s (C/Q3; D/Q1) V=0.356, sig.=0.000. Significant moderate relationship. Categorical variables CoPs & networking * Pearson’s R value; R=0.220(4) Learning 0.324, (B/Q14; D/Q4) Sig.=0.000, p<0.05, significant moderate relationship. Scale variables TFA NET * TFA MSc Factor Extraction; Pearson’s R (7) value, R=-0.404, sig.=0.000, p<0.01, Partial correlation; Controlling variable: TFA CPN TFA EED * TFA MSc Factor Extraction; Pearson’s R (8) value, R=-0.197, sig.=0.000, p<0.01, Partial correlation; Controlling variable: TFA CPN Source: F. Tomos, 2016, 2019 (based on SPSS) Note: TFA EED – Total Factor Analysis Entrepreneurship Education; TFA NET – Total Factor Analysis New Emerging Technologies; TFA MSc – Total Factor Analysis Women Entrepreneurs’ Success; TFA CPN – Total Factor CoPs & networking; B, C, D, E – Sections of the Questionnaire; Q - Question

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CHAPTER 6: QUALITATIVE DATA ANALYSIS Figure 6.1: The Structure of chapter 6 CHAPTER 6: QUALITATIVE DATA ANALYSIS

INTRODUCTION TO QUALITATIVE DATA ANALYSIS

PHENOMENOLOGY & QUALITATIVE DATA ANALYSIS

TEMPLATE ANALYSIS FINAL CODING TEMPLATE THEMATIC ANALYSIS Learning Digital Platforms & ICTs Women Entrepreneurs’ Success & Business Growth CoPs & networking Entrepreneurial Activity and Entrepreneurial Profile ILLUSTRATIONS

QUALITATIVE DATA ANALYSIS: INTERVIEWS (theory)

QUALITATIVE DATA ANALYSIS: FOCUS GROUP

INITIAL CODING TEMPLATE FINAL TEMPLATE MASTER TEMPLATE DESIGN VALIDATION THEMATIC ANALYSIS Learning Digital Platforms & ICTs Women Entrepreneurs’ Success & Business Growth CoPs & networking Entrepreneurial Activity and Entrepreneurial Profile ILLUSTRATIONS

INTERVIEWS ANALYSIS Using IPA & TA

INITIAL EMERGENT MODEL Qualitative Data Analysis

EMERGENT THEMES Focus Group & Interviews

FINAL EMERGENT MODEL Qualitative Data Analysis

ANDRAGOGICAL MODEL OF LEARNING SOLUTIONS TO Research Questions (Q3/Q5/Q6)

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6.1 Introduction to Qualitative Data Analysis According to Corbin and Strauss (2015), qualitative research is an alternative to quantitative research and implies data collection and analysis with specific methods. Moreover, the qualitative research aims to exceed the technical characteristics of the statistics used within the quantitative research and to direct its purpose more toward a hermeneutical interpretation of the results (Silverman, 2010; Creswell, 2007). However, what distinguishes the qualitative research from the quantitative research is the fact that, the researcher is involved with the research process together with the participants and the collected data. The grounded theory is a qualitative methodology (Glaser and Strauss, 1967) aiming to build a theory rooted within the collected data (Corbin and Strauss, 2015). The thesis aims to build a theoretical model, and employs some of the principal elements of the ground theory process (Glaser and Strauss, 1967; Charmaz, 2006) as follows: codes and categories, both from the data and from the hypothesis of the research; themes; a comparative approach and analysis. Furthermore, the elements of the ground theory process supplement the main approach to qualitative data analysis, used by this thesis, such as, phenomenology (Charmaz, 2006; Creswell, 2007). Phenomenological research depicts a phenomenon based on the individual views of the participants in the research, emphasising their experiences with that phenomenon and aims to extract the quintessence and formulate a general meaning out of this (Creswell, 2007; Moustakas, 1994). The grounded theory distinguishes by exceeding the purpose of phenomenology and aiming to generate a new theory and to design a process (Creswell, 2007). This study builds a theoretical model and uses elements of grounded theoryâ&#x20AC;&#x2122;s methodology characteristics and techniques in a creative manner. This approach is adopted, in view to find meanings and enhance the interpretation of the data obtained from the interviews and Focus Group. Additionally, the results enrich the interpretation of the outcome and finds explanations to the statistics obtained from the quantitative data analysis. The thesis is rooted within the Mixed Methods Research (MMR) methodology and is a hybrid form of using qualitative research to enhance and support the quantitative research. By using triangulation for data collection and analysis, and triangulation of methodologies, methods and theories, as well as the triangulation of research perspectives or philosophies, the study aims to contribute significantly to the development and 239

advancement of MMR as the third research method (Tomos et al., 2015; Flick, 2015). This type of triangulation is called multiple triangulations, and its aim is to avoid errors and validate the outcomes and the conclusions of the research (Arksey and Knight, 1999). Despite the criticism of this technique, Arksey and Knight (1999) highlighted that, as a consequence of using such technique, there was an increase in trust in the results of the research and a better interpretation. Furthermore, this is a mixed methodology design with two approaches across the stages of the research design (Flick, 2015). With regard to the qualitative data analysis, this is a process (Corbin and Strauss, 2015) involving various phases: data collection, coding, data classification into categories, new emergent themes from data collection and super – ordinate themes emergent from the hypotheses or the conceptual framework, and the last phase, data analysis and interpretation. The data was collected through thirty-seven interviews and a focus group. Nevertheless, the data, as Olsen (2012) mentioned, is not knowledge but only information coming from semi-structured interviews and the focus group. The semi-structured interviews were recorded as raw data on external drivers and these were used to create transcripts. According to Arksey and Knight (1999), the semistructure interviews are defined as semi-flexible tools, where the researcher has the freedom to explore the meanings, more in depth. Furthermore, the interviews in general, were defined as a range of techniques, and were characterised as ‘discussions’ or ‘dialogues’ between the participants and the interviewer (Arksey and Knight, 1999). The second instrument used to collect the data was a focus group with five women entrepreneurs. This was a forty minutes group meeting, with women entrepreneurs, gathered to a network business event.

About eight minutes were allocated to each

interviewee. Following the data collection, the next phase of the analysis was data transcription, which was dependent on the length and quality of the records (Olsen, 2012). The transcription process was accompanied by the acknowledgement of various insights into the processes, structures and reasons provided by women entrepreneurs and required by the entrepreneurial process, along thirty seven interviews, and a focus group with five women entrepreneurs (Olsen, 2012). Olsen (2012) defines transcripts as typed documents with complete punctuations to show the entire conversation. According to Langdridge (2007, p. 73), the transcription is ‘a verbatim account of the interview’. With regard to coding, this is about not only applying signs, numbers or letters to data, but is specifically about 240

grouping together data according to the purpose of the study, considering the themes and the meanings, in view to analyse this without falling into coding traps (Richards, 2011; Miles, Huberman and Saldaña, 2014). A pluralistic view, with multiple interpretations was considered, by taking into consideration both women entrepreneurs’ view as ‘insiders’ view’, and the published research on this topic, as ‘outsiders’ perspective’, in order to have a meaningful interpretation of the outcome of the analysis (Olsen, 2012; Dey, 1993; Arksey and Knight, 1999; Olsen, 2012; Miles, Huberman and Saldaña, 2014; Corbin and Strauss, 2015). 6.2 Phenomenology and Qualitative Data Analysis There are four main qualitative research approaches used by human science inquiries and these are the following: (1) the ethnographic research; (2) the grounded research theory; (3) the empirical phenomenological research; and (4) the Heuristic research (Moustakas, 1994). In analysing the qualitative data, this thesis considers a phenomenological perspective. What is phenomenology? Phenomenology involves the examination of human experience, and provides methods of analysis of real experiences (Langdridge, 2007; Smith, Flowers and Larkin, 2009). This study considers a method of data analysis employed by researchers in the field of phenomenological research psychology. There are various phenomenological methods for data analysis, such as: Interpretative Phenomenological Analysis (IPA), Hermeneutic Phenomenology (HP) and Template Analysis (TA). The Interpretative Phenomenological Analysis (IPA) is at the heart of Phenomenological Research Psychology and is recognised by the researchers in this field in the UK as a success for data analysis (Langdridge, 2007; Smith, Flowers and Larkin, 2009). The IPA is a ‘participant – centred’ method of analysis, which pinpoints towards a meaningful interpretation of human experience from the participants’ perspective. The rationale for this choice resides within the literature on IPA (Smith, Flowers and Larkin, 2009), which does not provide a specific method in working with the collected data, but instead suggests to researchers using freely the creativity and imagination for the data analysis with IPA.

Additionally, IPA provides the opportunity for data analysis

triangulation. Nevertheless, there are general recommendations regarding data collection and data analysis with IPA. Thus, Langdridge (2007) argued about the time required for the analysis, and recommends a purposive small sample size of maximum six participants. 241

Also, according to Langdridge (2007), the main method of analysis with IPA is the (1) thematic analysis, which consists of listening to the records, reflecting and discovering the main emergent themes. According with Smith, Flowers and Larkin (2009) the following are the steps in thematic analysis: reading, noting, developing emergent themes, finding connection between them and moving to the next case. The second phenomenological method, which is considered within this thesis is (2) the Template Analysis (TA), which, according to Langdridge (2007), is a substitute to IPA. Nigel King developed this, at the University of Huddersfield and yielded results analogous to IPA. Although, the method is alike IPA, however, while IPA focuses on thematic analysis regarding the human experience, TA pinpoints to producing similar result based on the usage of a previously established coding frame. According to Langdridge (2007), the reading and searching in the case of Template Analysis, focus on finding text that connects with the ‘a priori’ established themes. It is advisable, as we have multiple cases, and due to the complexity of the work and time restrictions, to conduct the analysis only on a sub-set of five transcripts out of 37 transcripts (Langdridge, 2007). The rationale of employing opposite philosophical perspectives and various methods of analysis is also considered common and normal practice between researchers in the UK (Langdridge, 2007). 6.3 Qualitative Data Analysis: Interviews & Focus Group The process of data analysis embeds within an exploratory coding method, which helps testing the hypotheses of the thesis and answers the research questions. Thus, the coding method answered the research questions, and applied so called ‘predetermined list of codes’ and ‘a priori themes’ (Miles, Huberman and Saldaña, 2014; King, 1998) or the list of codes extracted from the Coding Book of quantitative data, the conceptual framework and the key variables of the research. The rationale of using the predetermined list of codes and a starter list of categories (Richards, 2011) extracted from the Coding Book of quantitative data, was to limit the time spent on coding the qualitative data, which was actually very complex, and to obtain meaningful outcomes able to support the results from quantitative data analysis. The method of qualitative data analysis, was Template Analysis (King, 1998), with the following procedural steps: (1) Familiarizing with the textual data by reading; (2) Conducting preliminary coding of textual data, which is similar to IPA (Langdridge, 2007); (3) Defining the Initial Coding Template; (4) Holistic 242

Application of the Initial Coding Template; (5) Adaptation and finalisation of the defined Template, which had the capability of data interpretation. Dye (1993) stated that a specific characteristic of qualitative data analysis consists in a continuous process of thematic change, development and improvement across the stages. Additionally, both Interviews and the Focus Group used a priory themes emerged from the literature review and the conceptual framework of the thesis (Smith, Flower and Larkin, 2009). 6.4 Qualitative Data Analysis: Focus Group In order to have a holistic perspective of the outcome of data analysis from the Focus Group, and also in view to extract the essence from the participants’ answers to the research questions, the author of this thesis employed a combined technique of TA and IPA for the Focus Group analysis. The technique is based on line-by-line analysis of the transcript. Below, is provided the Final Template for the Focus Group (Table 6.1) with the super – ordinates emergent themes, themes relevant to this research and the connections between them. As a result of having a large sample with interviews, the author considered the recurrence of the themes when designing the final template with the emergent themes (Smith, Flowers and Larking, 2009). As opposed to this situation, in the case of the Focus Group, the thesis had a limited number of cases, homogenous and purposive. Consequently, the Final Table with the emergent themes for the Focus Group did not include the recurrent themes but the unique and most relevant themes to the research in a comparative manner. This is followed by the interpretation accompanied by illustrations (King, 1998; Brooks and King, 2014; Brooks et al., 2013). Table 6.1: Template Analysis – Final Coding Template for the Focus Group Box 1.1 Template with Emergent Super-Ordinate Themes and Themes from the analysis of a Focus Group with Five Women Entrepreneurs 1. Learning (EED) (Q4) 1.1 Styles of learning (Q4) 1.1.1 Flexible informal with ICTs and New Emerging Technologies (NET) 1.1.2 Learning with NET through information, communication and sharing 1.1.3 Learning through networking (Q8) 1.2 Methods of Learning (Q1, Q4) 1.2.1 Self-taught traditional learning with books and class-based/formal (Q1, Q4) 1.2.2 Experience – based learning (Q1)

243

1.2.3 Role model – based learning (parents entrepreneurs, mentors, investors) 2. Digital Platforms and Information Communication Technologies (NET & ICTs) (Q4) 2.1 Digital Platforms & ICTs usage for learning 2.2 Digital Platforms & ICTs usage for business 2.3 Preferences of using Digital Platforms & ICTs for learning 2.4 Preferences of using Digital Platforms & ICTs for business 2.5 Digital Platforms & ICTs are means of reaching friends, family, businesses and clients 2.6 Digital Platforms (Facebook, Twitter, Website and Blogs) usage for personal life and for business life 3. Women Entrepreneurs’ Success and Business Growth (WES) (Q2) 3.1 Women Entrepreneurs Defined (Q2) 3.1.1 Entrepreneurial perspective 3.1.2 Customer relationship perspective 3.1.3 Innovation and uniqueness perspective 3.1.4 Flexibility and parental care perspective 3.1.5 Personal characteristics perspective 3.1.6 Group characteristics perspective 3.2 Entrepreneurial Success Defined – gender perspective (Q2) 3.2.1 Entrepreneurial identity and personal perspectives 3.2.2 Ownership perspective 3.3 Business Growth Defined (Q2) 3.3.1 Development and expanding perspectives 3.3.2 Financial perspective 3.3.3 Customer perspective 3.3.4 Increase in sales perspective 3.4 Women Entrepreneurs’ Success Defined (Q2) 3.4.1 Financial Perspective 3.4.2 Self-Esteem & Confidence Perspectives 3.4.3 Customer Perspective 3.4.4 Business Growth Perspective 3.4.5 Survival Perspective 3.4.6 WES related to EED and NET & ICTs 3.5 Forum and Networks impact on achievement and success (Q6) 3.6 Online networks are a means of information and empowerment for success (Q6) 3.7 Digital Platforms & ICTs have impact upon the success of some women entrepreneurs (Q6) 3.8 Digital Platforms & ICTs do not have impact upon arts and creative entrepreneurs (Q6) 3.9 Measuring WES (Q3) 3.9.1 Financial Perspective 3.9.2 Non-Financial Perspective: Personal Happiness, Achievement and Contentment. 3.9.3 Non-Financial Perspective: Reputation

244

3.9.4 3.10 3.11

Non-Financial Perspective: Customer focus and good feedback from customers Enjoyment being a woman entrepreneur (Q7) Reasons of enjoyment: life balance, empowerment, networking (Q7)

4. Communities of Practice (CoPs) and Networking (Q4) 4.1 Dual aspect of networking: Face-to-Face and Online with Digital Platforms & ICTs (Q4) 4.2 Mum’s Network and other Networks are means of information and empowerment (Q6; Q8) 4.3 Acquiring knowledge through traditional networks Face – to – Face (Q5) 4.3.1 Face – to – Face networks inspire women entrepreneurs to take the risk 4.3.2 Face – to – Face networks are supportive and provide encouragement 4.3.3 Face – to – Face networks keep women entrepreneurs informed 4.4 Women Entrepreneurs acquire knowledge and information through online participation in informal and local community groups (Q5) 4.5 Women entrepreneurs belong to more than one and various network groups (Q5) 4.6 Women entrepreneurs belong to informal, unofficial online local communities groups (Q5) 4.7 Women entrepreneurs network with customers 4.8 Women entrepreneurs participate in community-centred networks through digital platforms (Q5) 4.9 Women entrepreneurs prefer women only networks (Q8) 4.10 Women entrepreneurs join networks to help their businesses (Q8) 4.11 Networks support social life, friendship and help through the tribulations (Q8) 4.12 Networking is crucial for business (Q8) 5. Entrepreneurial Activity and Personal Profile (Q1) 5.1 Setting up the enterprise (The engine behind/motivation/reasons/root) 5.1.1 Based on owner’s sector experience 5.1.2 Based on knowledge and studies 5.1.3 Purposeful and community oriented 5.2 Entrepreneurial identity 5.2.1 Professional and Freelancer 5.2.2 Owner of the business 5.3 Parental responsibilities 5.4 Entrepreneurial profile and entrepreneurial abilities 5.4.1 Ability to find opportunities and gaps in the market 5.4.2 Uniqueness and innovation 5.5 Type of entrepreneurial activities 5.5.1 Common to other businesses and routine based: cashing, ordering stock, selling, admin, secretarial, emailing 5.5.2 Activities specific to the business sector 5.5.3 Leadership: planning, forecasting, vision to grow, predicting, research 245

5.5.4

Management: Marketing, Finances, Accounting, Promotion, Networking 5.5.5 Networking 5.5.6 Using Digital Platforms & ICTs 5.5.7 Building customer relationship, customer base, dealing with customers 5.5.8 Teaching, training, mentoring 5.5.9 Having a vision, expanding the business 5.6 Gender is not an issue in the business world 5.7 Entrepreneurial research in the past ignored gender issues 5.8 Gender is an issue for a woman entrepreneur 5.8.1 Gender impacts upon business growth and personal achievement 5.8.2 Gender is an issue in certain business sectors (construction) 5.8.3 Gender issues can be overcome by participating within networks Source: © 2016, 2019 Florica Tomos (Based on the Focus Group) Digital Platforms & ICTs – NET & ICTs Communities of Practices & networking – CoPs & networking Information Communication Technologies – ICTs Question – Q

The Summary with the final coding template for the qualitative data analysis, part one Focus Group was shown in the Table above (Table 6.1). The researcher carried out a substantial amount of work, in order to present this final template for the analysis. The work which, was conducted beyond the coding process comprised the following phases: transcribing the interviews, reading, looking for patterns and uniqueness, selecting the key words, writing notes, extracting significant textual data, exploring, identifying, classifying, incorporating, blending and delivering relevant meaningful emergent super – ordinate themes and themes. In this TA, the researcher employed participant quotes. These quotes (Table 6.2) have the potential to illustrate, assist and empower the researcher’s interpretation of the data and support others in evaluating the validity of both participants’ accounts and data interpretation (Brooks and King, 2014). The final template includes four main themes, which are called super – ordinate themes and which emerged initially from the literature review of the thesis: (1) Learning (EED); (2) Digital Platforms & ICTs (NET & ICTs); (3) Women Entrepreneurs’ Success and Business Growth (WES); (4) Communities of Practice and networking (CoPs & networking).

Additionally, the researcher discovered a blended theme, entitled

‘Entrepreneurial Activity and Profile’ (EA & P) (5), which comprises the following topics: reasons of setting up own enterprise; entrepreneurial identity, profile and abilities; parental responsibilities; types of entrepreneurial activities and gender. Below, the thesis depicts and interprets each theme. These are accompanied by illustrations or examples of quotes from the participants’ accounts. 246

The Learning (EED) theme investigates styles and methods of learning that women entrepreneurs used in the past, along their lives, career and studies. It was very important to find out how they learn. Furthermore, what are the best styles and methods of learning to suit their particular needs as entrepreneurs, wives and parents, in the context of Digital Platforms & ICTs. The research found out three methods of learning. Thus, the first category of women entrepreneurs learned within class – based environments and strengthened their knowledge by their own efforts, with traditional studies based on book reading. The second category of women entrepreneurs learned by experience, whilst the third category of women entrepreneurs learned by role model method, from parents who were themselves entrepreneurs, from their investors or their male mentors.

illustration for each of these cases is provided below. It is worthy to mention that the majority of women entrepreneurs interviewed were educated at a degree or postgraduate level and most of this education was education related to the field of their choice of entrepreneurial activity (Table, 6.2, Illustration 1, FGP2; FGP5). The second focus of the analysis was on the styles of learning, which women entrepreneurs employed, in view to maintain their entrepreneurial activity, to face the challenges within the business world and to be updated with all the information required by their businesses, regarding the trends in the customers’ purchases and preferences, and the developments within their local communities, and with all the general information needed to promote their businesses. Consequently, the study discovered that women entrepreneurs used three styles of learning. The first category of women entrepreneurs learned flexibly and informally, from using digital platforms such as Facebook, Twitter, Blogs and websites, which can be accessed on a variety of ICT tools such as: iPhones, Smart Phones, Tablets, Laptops, iPad, etc. (Table 6.3, Illustration 2, FGP2). The second category of women entrepreneurs learned from accessing the online networks, Forums, online groups from the local communities and website information, by communicating with suppliers, customers, friends, professionals and family. The last category of women entrepreneurs learned by belonging to, and by participation in, Networking Groups and Business Associations, either Face – to – Face or online networking. The most preferred method of networking by women entrepreneurs within the Focus Group was Face – to – Face networking. Furthermore, there is a relationship between women entrepreneurs’ sector experience or educational background and the type of activity they set up (Table

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6.2, Illustration 1, FGP1). The researcher provides below, a few examples related to the mentioned methods and styles of learning. Table 6.2: Methods of learning, Illustrations Illustration 1: Women Entrepreneurs business educational background – methods of learning, example quotes: Experience-based learning: “My business educational background is ten years experience in arts education and administration.” (Participant One – FGP1, the owner of X Admin Services)

“Before I did my degree, I worked in a design factory, in ‘A’ town, where I am from.” (Participant Two – FGP2, Freelancer, Personal Stylist)

“...then [I] landed in Radio by default, never left the media for fifteen years. That’s why now I own a magazine and a media consultancy.” (Participant Four - FGP4, Publisher, Owner of Media Consultancy) “I did teaching training...” (Participant Five – FGP5, Owner of Training & Mentoring Limited)

Self-taught traditional learning with books and classes based/formal learning: “I went to University to become a nutritionist and have a health science degree. I did a health promotion postgraduate course” (Participant Four – FGP4)

“I have got a degree... “ (Participant Five – FGP5)

“When I did the postgraduate certificate recently at the university in mentoring... I got books and I actually bought books. I still prefer books.” (Participant Five – FGP5)

“...I am a book worm...” (Participant Four – FGP4)

Role model – based learning (other women entrepreneurs): “...then I will digest myself into something like the career girl Blog. When it comes to learning, I rather learn from inspirational women entrepreneurs, which I am still on a battle to find out, because I am one for younger women. I think is enough there locally to inspire me.” (Participant Four – FGP4) Source: F. Tomos, 2016, 2019 (Participants in Focus Group, 2015)

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Table 6.3: Styles of learning, Illustrations Illustration 2: Women Entrepreneurs business educational background – styles of learning, example quotes: Flexible Informal with Digital Platforms & ICTs (NET & ICTs): “Yeah, daily life and work life on laptop, iPhone, definitively on social media. It is amazing ... to get free advertising, free messages to your clients and to the world. I use them for learning, research, for looking into things. Yeah, I use the internet every day. I use for both learning and business.” (Participant One – FGP1) Learning with Digital Platforms & ICTs through information, communication and sharing: “The way I learn is by using most of these technologies. ... I use Facebook, Twitter, Google, iPhone, iPad, Mac Book Air.” (Participant Two – FGP2) Learning through CoPs & networking: “[Networking] It is crucial, it is how I learn. It’s my clients, how I learn about how other businesses are doing, how I can be involved in that...” (Participant One – FGP1) Source: F. Tomos, 2016, 2019 (Participants in Focus Group, 2015)

The Digital Platforms & ICTs theme explores women entrepreneurs’ learning preferences in the context of Digital Platforms & ICTs such as Facebook, Twitter, Smart Phones, iPhones, iPad, Androids, tablets and computers. Further, the theme seeks to find out whether women entrepreneurs use them for learning or for business.

The women

entrepreneurs interviewed indicated high dependence on these technologies in terms of learning and business. They confirmed the usage of some technologies such as Smart Phone and iPhone for texting and communicating with friends, family and clients. Further, digital platforms such as Facebook and Twitter are used for both learning and business promotion. Moreover, for some women entrepreneurs, most of their businesses come from Facebook and Twitter. They do prefer, and they confirmed, their daily use of iPad, tablets and laptops. In addition, a majority of women entrepreneurs pointed out their adherence to Instagram, Pinterest and LinkedIn, which helps them with business promotion. The analysis showed that the majority of women entrepreneurs use social media for business and communication.

Digital Platforms & ICTs assist women

entrepreneurs with communication, searching for information, promoting, selling, stocking, cashing, ordering, and learning about businesses and customers, finding trends in the market and local or national information. The researcher provides below (Table 6.4), a few examples, which demonstrate women entrepreneurs’ usage and preferences for Digital Platforms & ICTs: 249

Table 6.4: Preferences for Digital Platforms & ICTs (NET & ICTs) Illustration 3: Learning and business preferences for Digital Platforms & ICTs, example quotes: Women Entrepreneurs learning and doing business with Digital Platforms & ICTs: “I think Apple sponsors me. I do not think I can function more than one night without an Apple product. I do not know whether that is good or bad, but that is my life, my oxygen. It is my only way of promoting myself...” “But, yes, everything what you think about, whether is Pinterest, LinkedIn, Twitter, Facebook...” (Participant Four – FGP4)

“Nowadays, you have to use social media to promote your business...” (Participant Five – FGP5)

Women Entrepreneurs’ preferences for Digital Platforms & ICTs: “I use the laptop for the business and for the learning. The style of learning: reading, researching and exploring. I use information technology.” (Participant Two – FGP2)

“... I use Facebook, Twitter, Google, iPhone, iPad, Mac Book Air. I am equally addicted because they are my main learning facilities.” (Participant Two – FGP2)

“For learning it will always be Google search, I am on Blogger so, I have things regular, every day in the morning. Whose Blog is about some topic I am interested in...” (Participant Four – FGP4) Source: F. Tomos, 2016, 2019 (Participants in Focus Group, 2015)

In the next theme, WES and Business Growth, the author explored the perceptions of women entrepreneurs regarding the role and importance of Learning and Digital Platforms & ICTs for WES. The general opinion was that technologies are crucial and very important for business success. Women entrepreneurs acquire knowledge and information, and learn by means Digital Platforms & ICTs. However, there were also suggestions that technologies can be overwhelmed, and they are not decisive for the success of all types of entrepreneurs. For instance, it was indicated that the usage of technologies are not determinants for the success of artists and entrepreneurs belonging to the creative fields, neither for some types of entrepreneurs who effectively do not wish to embrace technology. Nevertheless, they argued, these categories of entrepreneurs can be successful and have successful businesses. The author provides below (Table 6.5), a few examples, which demonstrate the importance of Learning and Digital Platforms & ICTs for WES:

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Table 6.5: WES, Learning, Digital Platforms & ICTs, Illustrations Illustration 4: Women Entrepreneurs’ Success and Business Growth, example quotes: The impact of learning on women entrepreneurs’ success and business growth “I just did a postgraduate certificate in women entrepreneurship and what was really interesting was the research that came out, because of growth of women entrepreneurs. ... I think women entrepreneurship is growing.” (Participant Five – FGP5)

“However, in an organisation I did work for, we were training musicians, at high education level and to be entrepreneurs in that field, they couldn’t just survive as musicians, they had to be teachers, educators and concert performers. They had to adapt to be entrepreneurs to succeed in that field.” (Participant One – FGP1)

The impact of Digital Platforms & ICTs for women entrepreneurs’ success and business growth “New emerging technologies, again, Mum’s Network is so fantastic because there are entrepreneurs within network and they chose the power of social media for having a voice. ... Through technologies, they seem to be aware of what happens. This never happened in the past. It is very different.” (Participant Five – FGP5)

“The technology is just a matter of time, it’s not tomorrow, it’s happening now, and you can’t even breathe until you see that something new it’s on your radar. I think it is a benefit, the new technology it’s great.” (Participant Four – FGP4)

Technologies do not affect the success of all categories of entrepreneurs “But, the new technology it can overpower you...” “There are people who embraced it and there will be those who won’t embrace it because they haven’t got the make up to embrace it. And it is not by default it is just the fact that some are very academic and some are very creative. You either embrace something like emerging technologies or you can’t.” (Participant Four – FGP4) Source: F. Tomos, 2016, 2019 (Participants in Focus Group, 2015)

From the analysis of this theme, the author of the thesis was able to gather participants’ opinions and their perspectives of the meaning of essential terms, which led finally to the creation of definitions for entrepreneurial success (women’s perspective), women entrepreneurs and business growth. There are also controversial opinions and arguments regarding the impact of Digital Platforms & ICTs upon WES. Consequently, the author supplies further illustrations in the table below (Table 6.6):

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Table 6.6: Entrepreneurial Terms Defined, Illustrations Illustration 5: Women Entrepreneurs’ Success, example quotes: Women Entrepreneurs Defined “For me, I am the definition of that because I am doing what I have chosen to do, which is to balance my work and my family life and also to focus my career on something that I really enjoy doing, meeting amazing female clients who become really good friends.” (Participant One – FGP1)

“It is about a woman coming up with a unique idea and having the courage and being confident to go with it, on top of everything else that they require to do in daily lives, especially if they are mothers.” (Participant Two – FGP2)

“For me women entrepreneurs despite saying: this is what I do, this is what I cannot do, this is what I want to do, how can I turn it into a job, how can I make this sort, you know, who I am. They don’t have to step into a traditional role, or a traditional kind of job, which might be something that you have to do. So, thinking about and outside the box, and saying, this I want to do and do it.” (Participant Three – FGP3)

“A woman entrepreneur to me, is an interesting one, because I am very passionate about, energising women... there is a definitive movement in the UK at the moment about women finding themselves and being able to find inner confidence about ‘yes’ they can do what they love, they can be flexible, they can work around whether they are busy wives, busy girlfriends, busy mums. There are so many elements and dynamics to this. This is what will power through something that will effectively make a better country.” (Participant Four – FGP3)

“Woman entrepreneur is a woman who left a safe paid job to take a risk to set up a business whether as a self-employed or limited company. It is leaving a Job College with a monthly paid package and starting on my own.” (Participant Five – FGP5)

Entrepreneurial Success Defined (gender perspective) “Entrepreneurial success could be about the money, but also I think is about balance and how it makes you feel when you work at your personal success.” (Participant Five – FGP5)

“Entrepreneurial success is about continuing to grow the business.” (Participant Two – FGP2)

“I think entrepreneurial success leads straight from that in the sense of how you turn your idea in something that actually works and finally makes money to live...” (Participant Three – FGP3)

“Entrepreneurial success it’s all about being confident that you don’t have to conform. Before always have been boundaries and ... that ‘You can’t!’ Now it is a ‘can do’ attitude.” (Participant Four – FGP4)

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“Entrepreneurial success is being in a place where you are comfortable with your income and what the company is providing to other people.” (Participant Five – FGP5)

Entrepreneurial Success Defined (ICTs and NET – type of activity /sector perspective) “You either embrace something like emerging technologies or you can’t. It doesn’t mean that you are any less of the success, and I think that the new platform that allows people that are more creative...they need more contact, more human conversation, fact-to-face, whether that will be in literature, performing arts.” (Participant Four – FGP4)

Business Growth Defined “Business growth is just looking for new avenues and keeping abreast of what is out there and always being one step ahead and being...” (Participant Two – FGP2)

“...business growth is how you take that further, going from just surviving to how can I throw out, how can I build my business and somebody figures out how to do that cliché... how to sort that out to happen.” (Participant Three – FGP3)

“Business growth, I don’t think is down to money. I think business growth is personal, mental and physical, is that you have a confidence not only to believe in yourself, but believing in others and taking others along with you.” (Participant Four – FGP5)

“Business growth is hopefully a business which is not where was a year ago and might go in many directions...” (Participant Five – FGP5)

CoPs & networks impact upon Women Entrepreneurs’ Success “But, as an individual, to grow personally and through business I need the one-to-one and group contact.” (Participant Four – FGP4)

“Absolutely!”[Networking is important for business success] (Participant Two – FGP2)

Enjoyment and Reasons of Enjoyment “Yes, I do! It’s empowering and it’s fantastic.” (Participant Three – FGP3)

“It’s my oxygen; I don’t know why I took so long to become a female entrepreneur...” “When you find your passion in life...It is a lifelong balance.” (Participant Four – FGP4) Source: F. Tomos, 2016, 2019 (Participants in Focus Group, 2015)

The fourth theme analysed within the Focus Group, was CoPs & Networking. The focus of the theme was to discover whether women entrepreneurs belong to Networking Groups or Business Associations and to find out the influence of the CoPs & networks upon WES. 253

A particular importance was given to the aspects of the impact of CoPs & networking in the context of Digital Platforms & ICTs, upon women entrepreneurs’ participation, sharing knowledge and information in order to achieve success. The answers of the participants in the Focus Group demonstrated that a majority of women entrepreneurs belong to networking groups and these are valuable, in the sense that women entrepreneurs gain support, encouragement and information. Women entrepreneurs acquire knowledge by participating in networks, by meeting and talking to other women entrepreneurs. There are two types of networking: online and Face-to-Face. Women entrepreneurs gain knowledge and information by online networking, also within official and unofficial groups, with entrepreneurs, friends, customers, suppliers, members of local community, and family members by means of emerging technologies. Consequently, CoPs & networking are an essential part, and a factor that affects positively WES. By networking, women entrepreneurs reach the world and gain confidence, moral support and encouragement. Furthermore, they develop their knowledge and promote their businesses. Particularly successful were Face –to – Face networking, which were perceived as positively impacting upon both personal and business growth. The outcomes indicate that CoPs & Networking are a major theme with impact upon entrepreneurial learning, WES and business growth. The author provides below (Table 6.7) a few examples, which demonstrate the perceived impact of CoPs & networking upon WES: Table 6.7: CoPs & Networking, Illustrations Illustration 6: Networking and Communities of Practices (CoPs) and Women Entrepreneurs’ Success and Business Growth, example quotes: CoPs & Networks are inspirational, supportive and helpful for women entrepreneurs “Forum like this is so fantastic, because women can see other women doing and achieving.” “Women entrepreneurs acquire knowledge and information through Face – to – Face and online networks” (Participant Five – FGP5)

I belong to Business Women in X, which is a networking group and was probably, one of the main catalysts for me, for leaving my own regular salary, income job and jump off the plank to start my own business. It gave me the confidence and inspiration to feel like I can do it, and to balance all things I need into my life. I do belong and I find it very important and valuable and an important part of my business and personal life. (Participant One – FGP1)

Networking promotes the business, is crucial for business success and reaches the world 254

“In terms of other sort of networks, I take part of Nation Wide which is (...). I also go to local trade shows. This is how I connect to my networks to reach the whole world...” (Participant 3 – FGP3)

Face – to – Face networking impact personal and business success “I find face-to-face more human and personal, that’s where I am like as an individual. Online is a bit more solo, it’s not so transparent. I don’t feel like I connect. I will go there for information, if I needed. But, as an individual, to grow personally and through business I need the one-to-one and group contact.” (Participant Four – FGP4) Source: F. Tomos, 2016, 2019 (Participants in Focus Group, 2015)

The last theme explored by this research within the Focus Group is a blended theme, which emerged from the Focus Group discussions. The author entitled this last theme Entrepreneurial Activity and Profile (EA & P). This is a complex theme, in the sense that it explores mixed issues related to both the enterprise and the entrepreneur.

characteristic of this theme is the fact that it investigates aspects with various degrees of importance. Some of the aspects refer to a suggested relationship between setting up enterprise and the business educational background of the entrepreneur. The investigation of this theme within the Focus Group, demonstrates also, the presence of a relationship between the owner’s sector experience and the type of business to set up. Other aspects are with regard to the entrepreneurial identity, role identity, parental responsibility, entrepreneurial profile and abilities, and the types of entrepreneurial activities. The reasons behind setting up enterprises were the following aspects: independence, financial stability, life and work balance to suit parental responsibilities, and the desire of ownership. Most of the women entrepreneurs demonstrated a keen eye in finding gaps in the market, opportunities and uniqueness. Another important aspect that emerged from the analysis of the theme within the Focus Group was the acknowledgement of different types of entrepreneurial activities, which finally provided detailed elements to formulate a comprehensive definition of the entrepreneurial process. The author provides below (Table 6.8) a few examples, which indicate the importance of this theme in assessing the impact of the factors involved in the research for women entrepreneurs’ success:

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Table 6.8: Entrepreneurial Activity and Profile Illustration 7: Entrepreneurial Activity and Profile and Women Entrepreneurs’ Success, example quotes: Entrepreneurial identity & ownership “I am the owner of X Admin.” “I am a Personal Stylist.” “I am the owner of Y Landscape.” “I am the owner of Z Media Consultancy.” “I am the owner of V Training Limited.” (Participants to Focus Group – FGP1, FGP2, FGP3, FGP4)

Parental responsibilities “My daily activities are two days per week working and three days per week looking after my boys.” (Participant Four – FGP4)

“I have to sort out my two boys to go to school, by nine o’clock...” (Participant Four – FGP4)

Entrepreneurial profile and entrepreneurial abilities “I am a personal stylist. My aim is to help women to refine their confidence and personal style, and give them something for themselves back.” (Participant Two – FGP2)

Type of entrepreneurial activities “My day starts with anything from talking to my Personal Assistant (PA) which I am very proud of, running the accounts, selling, advertising, writing features, going to do workshops, going to sell, encouraging businesses to join my Forum, running a women in business network.” (Participant Four – FGP4)

“My daily activities are very varied: meeting clients, hands on, on site, emailing, marketing, all sorts.” (Participant Two – FGP2) Source: F. Tomos, 2016, 2019 (Participants in Focus Group, 2015)

In order to determine the most powerful or dominant themes across the sample, the researcher looked for patterns and the relationships between them, and their relevance for the thesis. The process was accompanied by adding, deleting, renaming themes until the final template was presented for the researcher’s interpretation. As opposed to the interviews, the Focus Group assumes to have a complementary perspective upon the cases (participants’ accounts). This approach required the consideration of all cases of the Focus Group for the analysis in a complementary manner. 6.5 Interviews Analysis Using IPA & TA The thesis conducted also, thirty-seven interviews with women entrepreneurs. In a large sample like this the author of the thesis considered ‘A Priory Themes’ (King, 1998) and searched for patterns, relationships and new themes relevant to the study. Furthermore, it was essential to measure the recurrence of the main themes (Smith, Flowers and Larkin, 2009). Having considered these highlights, the author of this thesis, defines the recurrent 256

theme, as that theme which is presented in, at least twenty percent of all accounts or participant interviews for the superordinate themes; at least ten percent of all accounts for the unique themes relevant for the research and at least thirty percent of all accounts for the controversial themes for both Focus Group and Interviews (Smith, Flowers and Larkin, 2009). The analysis of these is based mainly on IPA. It is not entirely IPA-based, because the author used a blended procedure that is not only innovative, but suits the purpose of this research, and increases the validity of the outcome through a pluralistic approach and perspective upon the meaning and interpretation of the interviews conducted with women entrepreneurs. In the first phase, the author carried an in depth and methodical line-by-line analysis of a data set of five interviewees. Following the first and second phases of the analysis, this section presents below the tables with the Initial Coding Template (Tables 6.9 â&#x20AC;&#x201C; 6.13). This suffered a continuous change and adaptation according with the progress in coding, creating and selecting the recurrent emergent themes from the next thirty-two interviews with women entrepreneurs. The Final Coding Template followed this process, allowing the main interpretation of the interviews to be developed accordingly. Table 6.9: Initial Coding Template, Learning (EED) Box 1 The Initial Coding Template, Data Set of Five Interviewees Theme: 1. Learning 1.1 Methods of Learning 1.1.1 Formal learning class based & non class based 1.1.1.1 Learning from male mentor 1.1.1.2 Traditional learning self-taught with books 1.1.2 Experience based 1.1.2.1Trial and error 1.1.2.2 Learning from other entrepreneurs 1.1.2.3 Learning from customers 1.1.3 Informal learning 1.2 Styles of learning 1.2.1 Learning with Digital Platforms & ICTs 1.2.1.1 Learning through Conference calls 1.2.1.2 Learning with Social Media (Facebook & Twitter) 1.2.1.3 Learning with YouTube 1.3 Learning Preferences 1.3.1 Informal learning by searching for news and reviewing the press 1.3.2 Formal learning from experts 1.4 Entrepreneurship Competences Source: F. Tomos, 2016, 2019 (Interviews, 2015)

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Table 6.10: Initial Coding Template, Digital Platforms & ICTs (NET & ICTs) Box 2 The Initial Coding Template, Data Set of Five Interviewees Theme: 2. Digital Platforms & ICTs 1.1 Digital Platforms & ICTs usage for business 1.2 1 Computers usage for business 2.2.2 Internet and Social Media usage for business (Facebook & Twitter) 2.2.3 Google usage for business 2.2.4 Websites usage for business 2.2 Digital Platforms & ICTs for learning 2.2.1 Google Analytics for learning 2.2.2 Internet usage for learning 2.3 Digital Platforms & ICTs usage for personal life 2.4 Preferences for Digital Platforms & ICTs usage for learning 2.5 Preferences for Digital Platforms & ICTs usage for business 2.6 Preferences in accessing Digital Platforms through various technological tools 2.7 Women entrepreneurs capability to create Digital Platforms 2.8 Digital Platforms & ICTs usage for business communication 2.9 Accessing Digital Platforms for business from mobile devices (Cloud based system) 2.10 Methods of learning to use Digital Platforms & ICTs 2.10.1 Learning from children and family members 2.10.2 Learning from customers 2.10.3 Learning via online 2.10.4 Learning via Media Source: F. Tomos, 2016, 2019 (Interviews, 2015)

Table 6.11: Initial Coding Template, WES Box 3 The Initial Coding Template, Data Set of Five Interviewees Theme: 3. Women Entrepreneurs’ Success and Business Growth 3.1 Defining Entrepreneurial Process 3.2 Digital Platforms & ICTs impact entrepreneurial success 3.2.1 Learning with Digital Platforms & ICTs increases entrepreneurial success (YouTube tutorial) 3.2.2 Doing business with Digital Platforms & ICTs increases entrepreneurial success (Facebook, Twitter, Pinterest, Instagram, websites, Blogs, eBay) 3.3 Learning with Digital Platforms & ICTs increase entrepreneurial success 3.4 Financial Measures for Entrepreneurial Success 3.4.1 Increase in Sales 3.4.2 Increase in Profit 3.5 Non-Financial Measures of Entrepreneurial Success 3.5.1 Increase in the number of customers 3.5.2 Increase in customers’ spending 3.6 Defining Women Entrepreneurs’ Success 3.6.1 Financial perspective 3.6.2 Ownership perspective 258

3.6.3 Processual perspective 3.6.4 Networking perspective 3.6.5 Customer centred perspective 3.6.6 Enjoyment and rationale 3.6 Entrepreneurial Success 3.7.1 Gender perspective 3.7.2 Non gender perspective 3.7 Learning impacts women entrepreneurs’ success 3.8 Networking & CoPs are essential for women entrepreneurs’ success 3.9 Women’s entrepreneurial capabilities Source: F. Tomos, 2016, 2019 (Interviews, 2015)

Table 6.12: Initial Coding Template, CoPs & Networking Box 4 The Initial Coding Template, Data Set of Five Interviewees Theme: 4. Communities of Practice & networking (CoPs) 4.1 Networking Defined 4.1.1 Official Networking Groups 4.1.2 Non Official Networking Groups 4.2 Networking online with customers, suppliers, entrepreneurs and friends 4.3 Networking for a purpose 4.3.1 Networking to suit parental care 4.3.2 Networking for success 4.3.3 Networking for setting up business 4.3.4 Networking for encouragement 4.3.5 Networking for knowledge and information 4.3.6 Networking for gender empowerment 4.4 Types of networks and CoPs 4.4.1 Traditional Face-to-Face 4.4.2 Online networks 4.5 Advantages of Networking & CoPs Source: F. Tomos, 2016, 2019 (Interviews, 2015)

Table 6.13: Initial Coding Template, EA & P Box 5 The Initial Coding Template, Data Set of Five Interviewees Theme: 5. Entrepreneurial Activity and Profile 5.1 The engine of setting up an enterprise 5.1.1 Sector experience 5.1.2 Knowledge and business education 5.1.3 Personal and family motives 5.1.4 Health Issues 5.1.5 Opportunity 5.1.6 Desire for ownership 5.1.7 Self-esteem and self-actualization 5.1.8 Work and life balance 5.1.9 Challenge and a certain stage in life 5.1.10 Determination for freedom and independence 5.1.11 Financial independence 259

5.2 The modality of starting up an enterprise 5.2.1 Setting up a new enterprise 5.2.2 Buying an established business 5.2.3 Sector experience and research 5.2.4 Business education & opportunity Source: F. Tomos, 2016, 2019 (Interviews, 2015); Note: Entrepreneurial Activity â&#x20AC;&#x201C; EA, Entrepreneurial Profile - EP

6.6 Data Analysis: Interviews with 37 Women Entrepreneurs. Final Template In order to provide the validity of the main themes resulting from interviews analysis, the author defines as valid a theme, which is based on at least 20% recurrence. Presented below is the Master Template (Table 6.14) with such validation for the main five themes, followed by the Final Coding Template, which is used within the interpretation of the outcomes from the qualitative data analysis of the interviews (Brooks and King, 2014): Table: 6.14 Master Template Design for theme validation by recurrence, EED Theme Participants Recurring Percent/ Validation Theme One: Learning (EED) 1. Methods of learning 1.1 Formal learning class-based P2, P20, P13, P9, 43%/Yes P29, P24, P26, P4, P30, P22, P37, P35, P33, P21, P12, P19 1.2 Formal learning non class-based: P2, P18, P31, P1, 27%/Yes learning from mentors and role models & P13, P4, P21, P12, family members (children, husbands) P22, P17 1.2 Formal learning non class-based: P25, P17, P23, P2, 22%/Yes traditional learning, self-taught with P1, P30, P21, P19 books 1.3Experience-based learning: trial & P22, P1, P18, P15, 57%/Yes error P13, P14, P11, P10, P9, P29, P31, P28, P26, P24, P4, P36, P35, P33, P32, P19, P30 1.3Experience-based learning: learning P34, P32, P1, P22, 38%/Yes from other entrepreneurs, customers and P17, P20, P30, P35, suppliers P9, P11, P31, P27, P4, P19 1.4Informal learning: acquiring knowledge and information 22%/Yes 1.4 Acquiring knowledge and information P12, P21, P30, P13, by reading books, magazines, studies, P23, P24, P37, P29 watching TV, news and updates on trends 260

1.4 Acquiring online information (Google, P21, P4, P19, P37, Social Media, internet) P36. P31, P32, P29, P22, P24, P13, P7, P18, P1 1.4 Acquiring information from suppliers, P34, P35, P4, P33, trainers, customers, competitors, Welsh P32, P22, P31, P27, Government courses, schemes, reps, fairs, P30, P26, P7, P17, exhibition and research P20, P12, P8 1.4 Acquiring information and knowledge P24, P26, P13, P7, from networking (online and face-to-face) P18, P17, P20, P5, P2, P1, P21, P30, P22 1.4 Acquiring information and knowledge P1, P7, P8, P18, P17, by learning with Digital Platforms & ICTs P11, P13, P29, P25, P24, P20, P27, P37, P32, P33, P36, P35, P13, P21, P19, P31 2. Styles of learning

38%/Yes

2.1 Flexible learning

22%/Yes

P9, P8, P4, P12, P21, P19, P17, P30 P23, P20, P11, P35, P32, P4, P21, P24, P33, P30 P23, P13, P10, P7, P29, P37, P32, P4 P18, P16, P15, P14, P11, P10, P7, P31, P29, P28, P26, P24, P4, P19, P36, P35, P33, P32, P22 P5, P3, P32, P35, P33, P1, P17, P9, P29, P26, P25, P37, P36, P6, P18, P17, P34, P24, P33

2.2 Auditive Style 2.3 Visual style 2.4 Experiential style

2.5 Online & networking style

41%/Yes

35%/Yes

54%/Yes

27%/Yes 22%/Yes 51%/Yes

51%/Yes

Source: F. Tomos, 2016, 2019 (Interviews, 2015); Note: Themes valid at least 20% recurrence P – Participant/Interviewee, Number of participants under analysis – 32; former sub set data – 5 participants; total participants – 37 (100%) ICTs – Information Communication Technologies NET – Digital Platforms

The values from the above table demonstrated the validity of the themes and the sub themes.

The highest percent of validity indicated a high recurrence for the following

methods of learning: ‘experience-based learning by trial & error’, and ‘acquiring information and knowledge by learning with Digital Platforms & ICTs’, as well as for the following women entrepreneurs’ style of learning: ‘experiential’ and ‘online and networking’. Also, a high percent of recurrence for the methods of learning ‘acquiring 261

information from suppliers, trainers, customers, competitors, Welsh Government courses, schemes, reps, fairs, exhibition and research’ and ‘acquiring information and knowledge by networking’, indicated that these are valid methods used by women entrepreneurs in achieving business growth and success. As mentioned previously, the first part of the Final Coding Template was related to the Focus Group with five women entrepreneurs in Wales (Table 6.2). Further, the author discusses the second part of the Final Coding Template, based on the interviews with thirty-seven women entrepreneurs in the South East Wales. The author of the thesis used a combined technique of TA and IPA, in order to increase the validity of the results.

A laborious and comprehensive work was

developed in order to transcribe thirty-seven interviews (about 65,000 words) and analyse these line-by-line. Whilst, in the case of the Focus Group, the author dealt with a small number of cases, and considered both, the recurrent and relevant themes, which were crucial for the analysis, within the case of the interviews, the author encountered a large sample of interviews, which certainly, required the consideration of the recurrence of the themes in selecting the emergent themes for the final template (Smith, Flowers and Larking, 2009) (Tables 6.15; 6.18; 6.21; 6.24; 6.27). Furthermore, as a result of the purpose of the research and large amount of information, the author decided to employ ‘a priory themes’, together with a critical and selective manner when designing the Final Template. As mentioned before, each Final Template is followed by the interpretation accompanied by illustrations (King, 1998; Brooks and King, 2014; Brooks et al., 2013). The Final Template covers five super ordinate themes: (1) Learning (EED); (2) Digital Platforms & ICTs (NET & ICTs); (3) Women Entrepreneurs’ Success (WES); (4) Communities of Practice and networking (CoPs & networking); (5) Entrepreneurial Activity and Profile (EA & P). Considerable work was carried out in order to produce the Final Template. The template was first designed by Brooks and Nigel (2014), who applied this to a large number of interviews. Consequently, they concluded upon the adequacy of its design and application. Therefore, the author applied confidently the TA, and considered the results remarkable unique. Below, is the version of the Final Template for the Learning (EED) (Table 6.15) super ordinate theme with the first, the second and the third level themes included.

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Table 6.15: The Final Template for the Interviews Box 6 The Final Template for the Interviews with thirty seven women entrepreneurs Theme: 1. Learning (EED) 1.1 Methods of Learning 1.1.1 Formal learning class-based 1.1.2 Formal learning non-class based 1.1.2.1Learning from mentor, role models (other women entrepreneurs, father, parents and husbands) and family members (young/adult children & husbands) 1.1.2.2. Traditional learning self-taught with books 1.1.3 Experience-based learning 1.1.3.1 Trial & Error (by doing) 1.1.3.2 Learning from others (entrepreneurs, customers and suppliers) 1.1.4 Informal learning: acquiring knowledge and information 1.1.4.1 Reading books, magazines, watching TV, news and studies 1.1.4.2 Online information (Google, Social Media, internet) 1.1.4.3 Information from suppliers, customers, trainers, competitors, reps, Welsh Government courses and schemes, fairs, courses, exhibitions, brochures, literatures and research 1.1.4.4 Information from networking (online and face-to-face) 1.1.5 Learning with Digital Platforms &ICTs (NET & ICTs) 1.2Styles of learning 1.2.1 Flexible learning style 1.2.2 Auditive learning style 1.2.3 Visual learning style 1.2.4 Experiential learning style 1.2.5 Online and networking style Source: F. Tomos, 2016, 2019 (Interviews, 2015)

(1) Learning (EED) theme explores the methods of learning and the styles of learning, women entrepreneurs employ in order to ensure business growth and success. According to the thematic analysis, there are five main methods of learning: (a) The formal classbased learning, which the majority of women entrepreneurs proved to have taken through the main stream of education, by studying at one of the colleges or by studying at a University for a degree or a postgraduate course. The formal class-based method, is based on individuals, learning within a class-based environment, with the delivery of the learning, and the class managed by a teacher/lecturer; (b) The second method of learning, discovered within the study, was the formal non class-based, which is focused on women entrepreneurs learning with books by a self-taught method, or learning from mentors and role models such as fathers and parents entrepreneurs, and family members like young or adult children, with knowledge and expertise in a particular area, or from husbands 263

entrepreneurs having the required expertise; (c) The third method of learning that emerged from the research is experience-based learning.

Most of the women

entrepreneurs interviewed, answered that they prefer to learn by doing, by trial and error, or learning by asking other entrepreneurs, suppliers or even customers with particular expertise, knowledge and specific desire to buy certain products, certain quality or services; (d) The fourth method of learning emphasised by women entrepreneurs was the informal learning and acquiring knowledge and information. Thus, the majority of women entrepreneurs acquired knowledge and information by reading books and magazines, watching TV and the news, by searching online for the information or accessing the social media and goggling. In addition to this, most of them learn from the knowledge and information acquired from the suppliers, reps, customers, trainers, competitors, from courses delivered by the Welsh Government and from fairs, exhibitions and various literatures, such as brochures; (e) The fifth method of learning found by the thematic analysis, was learning with Digital Platforms & ICTs. The author discovered that women entrepreneurs learn with and from Facebook, Twitter, Instagram, by using iPhone, Androids, tablets and iPad. The second matter investigated by this first theme was the styles of learning that women entrepreneurs employ in reaching success and business growth. According to their responses, the author of this research produced five styles of learning: flexible, auditive, visual, experiential and online, and networking. The author provides below a few examples to demonstrate the main methods and styles of learning, women entrepreneurs use in order to achieve success (Table 6.16, Illustration 1). Table 6.16: Methods and Styles of Learning, Illustrations, Learning (EED) Illustration 1: Learning: methods of learning & styles of learning, example quotes: Methods of learning Formal learning class-based “I went to the College and have done level two and level three [in] Beauty Therapy and level three [in] Holistic Therapies...” (P2) “I went to the university and I studied Police Science [because] I wanted to join the Police. I finished that and I changed my mind completely. I decided to go to the College and to Beauty”. (P20) “I have trained for three years in V College, in Hair and Beauty. I also have done different courses, since qualifying level three in Hair Dressing in the College” (P9) 264

Formal learning non class-based (learning from mentor, role models, family and selftaught) “My dad called me to start and work in his business, cleaning staff at the age of twelve...I have seen my dad as a role model for years, so I just asked anything what I was stacked on...” (P13) “My best method of learning was my nun, because she taught me how to crochet and knit when I was eight. I just learn from books and YouTube.” (P25) “[I learned to use Facebook and Twitter from] the children. The kids! ... My daughter is twenty and she is at University X and my son is fourteen in the local High School.” (P17) Experience-based learning (trial & error, other entrepreneurs, suppliers, customers) “I would probably go with experience-based, [because] I am quite a ‘hands on’ person.” (P15) “I suppose learning over the years has been ‘trial and error”.” (P1) “...learning has been done by contacting other businesses in practice, for the moment. I found that inter business learning...works really well...” (P34) Informal learning: acquiring information and knowledge (reading books and magazines, online information, networking, suppliers, courses, fairs, exhibitions, research) “...I do a lot of research at home in the evenings...” (P37) “I do use internet to search for different subjects, different things like menus. I had to do different courses for food hygiene, but the rest of that is research on internet.” (P33) “Mostly, if I need some information, I’ll go to Google ... I am not afraid to phone people and ask for help or contact people by email.” (P26) “...books, what the suppliers send me, different companies send me...like little bibles...you get all the details about the products, all the ingredients and what they are good for, that sort of thing...But you learn from customers every day.” (P17) “You have to learn through exhibitions, agents, magazines, literature that is sent to you and the brochures from all different countries.” (P8) “The informal learning and the experience in certain fields help in a lot of instances. That type of learning helps a lot more than the formal learning... Informal learning gives you a lot more insight into whatever area you are heading.” (P7) Learning with Digital Platforms & ICTs “...but I get a lot of information through Google...” (P8) “I am learning all the time on Facebook and the platform on Facebook is more user and learner friendly...” (P7)

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“We do a lot of online research.” (P27) “We use Facebook and Google... The social media is awesome.” (P36) Styles of learning Flexible learning style “Flexible, everything has to be flexible, because we have to run the business at the same time.” (P27) “You can’t go on a course because it takes you out of the business. Sometimes you are too tired to do an evening course and you have other commitments.” (P8) Visual and auditive learning style “I think is all down to what I learned following people older than me, and watching what they do and just observing and trying to do better for myself, asking questions, and being not stubborn (...).” (P13) “...listening, on internet...from the competition, just anyway.” (P32) “Watching what others were doing, observational [styles of learning].”(P6) “For my self is watching and observing...” (P10) “...but when it comes to clothes [my memory] it is almost photographic.” (P10) Experiential learning style “I enjoy experiential learning, I like to be ‘hands on’ because I make my own products.” (P26) “...literally is it like playing with the clothes, dressing a manechin, doing a window, having customers to try things on and basically experimenting different colours, different textures”. (P10) Online and networking style “I learn online...I learn from my colleagues.” (P32) “There are a lot of Government sites which offer you an online training, in order for you to do it yourself...” (P27) Source: F. Tomos, 2016, 2019 (Interviews, 2015); Note. P – Participant

(2) Digital Platforms & ICTs (NET & ICTs) theme investigates whether women entrepreneurs use Digital Platforms & ICTs for learning and business. Furthermore, the theme investigates women entrepreneurs’ preferences for ICTs such as iPad, iPhones, Smart Phones, tablets, computers and laptops, and women entrepreneurs’ preferences for Digital Platforms such as Facebook, Twitter, Instagram, Pinterest or LinkedIn, and their usage for business and for learning. Below the author presents the master template design (Table 6.17) for the theme validation by recurrence. The table contains all the valid themes, included in the Final Template of the second super ordinate theme. The table is followed by the Final Template for the second super ordinate theme, which is the Digital Platforms & ICTs (Table 6.18). 266

Table 6.17: Master Template Design for theme validation by recurrence, Digital Platforms & ICTs Theme Participants Recurring Percent/Validation Theme Two: Digital Platforms & ICTs 2.1 Digital Platforms & ICTs usage for learning 2.1.1 Internet and YouTube usage for P29, P26, P24, P10, P18, P20, P30, P21 learning

22%/Yes

2.1.2 Google and Google Analytics P37, P36, P35, P8, usage for learning P18, P20, P12, P30, P13 2.1.3 Digital Platforms usage for P35, P34, P24, P9, learning (Facebook, Twitter) P18, P17, P4, P21, P22, P19 2.1.4 Digital Platforms accessed via P34, P32, P31, P18, laptop, tablets, iPad and iPhone for P6, P37, P33, P9, learning P7, P8, P7, P17, P1, P6

24%/Yes 27%/Yes 38%/Yes

2.2 Digital Platforms & ICTs usage for business 2.2.1Internet, YouTube, Google search P6, P11, P29, P32, and websites usage for business P19, P4, P30, P13, P37, P12 2.2.2 Digital Platforms usage for P4, P19, P21, P30, business (Facebook, Twitter, Skype, P12, P6, P3, P2, Pinterest, Instagram, Ettzi and P18, P17, P23, P20, LinkedIn) P15, P14, P22, P13, P9, P7, P27, P26, P36, P34, P32 2.2.3 Computers, laptops and tablets P19, P6, P18, P20, usage for business P15, P11, P10, P8 2.2.4 iPad, iPhone, Smart Phone and P19, P18, P17, P15, Android usage for business P14, P11, P10, P9, P7, P29, P34, P19 2.2.5 Cloud-based platform for P19, P12, P30, P27, business P33, P35, P10, P7

27%/Yes 62%/Yes

22%/Yes 43%/Yes 22%/Yes

2.3 Preferences for Digital Platforms & ICTs usage for learning 2.3.1Women entrepreneursâ&#x20AC;&#x2122; preferences in using Google and YouTube for learning 2.3.2 Women entrepreneursâ&#x20AC;&#x2122; preferences for ICTs in accessing Digital Platforms for learning

P37, P35, P13, P8, P17, P31, P36, P4

22%/Yes

P19, P4, P37, P34, P1, P17, P15, P11, P31, P33, P32

30%/Yes

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2.3.3 Women entrepreneurs’ P37, P36, P34, P7, 22%/Yes preferences in using Digital Platforms P17, P9, P19, P21 for learning (Facebook, Twitter) 2.4 Preferences for Digital Platforms & ICTs usage for business 2.4.1 Women entrepreneurs’ preferences in using Digital Platforms for business (Facebook, Twitter and Instagram) 2.4.2 Women entrepreneurs’ preferences in using iPad, iPhone and tablets for business

P4, P36, P37, P32, P35, P34, P27, P26, P19, P24, P14, P13, P10, P9, P8, P7, P23, P15, P20, P2, P3, P6 P34, P33, P32, P35, P31, P14, P11, P10, P9, P8, P7, P15, P6, P1, P19

59%/Yes

41%/Yes

Table 6.18: Final Coding Template, Digital Platforms & ICTs Box 7 The Final Coding Template for the Interviews with thirty seven women entrepreneurs Theme Two: Digital Platforms & ICTs 2.1 Digital Platforms & ICTs usage for learning 2.1.1 Internet and YouTube usage for learning 2.1.2 Google and Google Analytics for learning 2.1.3 Digital Platforms usage for learning (Facebook and Twitter) 2.1.4 Digital Platforms accessed via iPhone, laptop, tablets and iPad for learning 2.2 Digital Platforms usage for business 2.2.1 Internet, websites, YouTube and Google usage for business 2.2.2 Digital Platforms usage for business (Skype, Facebook, Twitter, Pinterest, Instagram, Ettzi and LinkedIn 2.2.3 Laptop, Computers and tablets usage for business 2.2.4 iPad, iPhone, Smart Phone and Androids usage for business 2.2.5 Cloud-based platform for business 2.3 Preferences for Digital Platforms & ICTs usage for learning 2.3.1 Women Entrepreneurs’ Preferences for using Google and YouTube for learning 2.3.2 Women Entrepreneurs’ Preferences in accessing Digital Platforms for learning 2.3.3 Women Entrepreneurs’ Preferences in using Social Media for learning 2.4 Preferences for Digital Platforms usage for business 2.4.1 Women Entrepreneurs’ Preferences in using Digital Platforms for business (Facebook, Twitter, Instagram) 2.4.2 Women Entrepreneurs’ Preferences in using ICTs for accessing for Digital Platforms (tablets, iPad, iPhone) Source: F. Tomos, 2016, 2019 (Interviews, 2015)

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The high recurring percent confirmed the validation of three particular themes which were included within the Final Template: (a) Digital Platforms usage for business; (b) iPad, iPhone and Androids (ICTs) usage for business and (c) women entrepreneurs’ preferences for Digital Platforms & ICTs. They indicated that 62% of 37 women entrepreneurs used Digital Platforms for business and 43% of them used ICTs such as iPad, iPhones and Androids for business purpose. The super ordinate theme: Digital Platforms & ICTs includes the following four themes: (1) Digital Platforms & ICTs usage for learning; (2) Digital Platforms & ICTs usage for business; (3) women entrepreneurs’ preferences for Digital Platforms & ICTs usage for learning; (4) women entrepreneurs’ preferences for Digital Platforms & ICTs usage for business. This super ordinate theme contains first and second level themes only. The thematic analysis indicates that women entrepreneurs use internet and YouTube, Google, Google Analytics, Social Media, iPad and tablets for learning. Most of the digital platforms are accessed by women entrepreneurs, through the laptop and iPhone. Similarly, they use Google search, Social Media, computers, laptops, tablets, iPad, iPhones, Smart Phones and Androids for business.

About 22% of 37 women

entrepreneurs interviewed had embedded the cloud-based platform within their businesses. Finally, women entrepreneurs interviewed in this study, preferred Google, YouTube, Facebook, Twitter, iPhone, iPad, tablets and laptop usage for learning. Further, women entrepreneurs prefer Facebook, Twitter, Instagram and Google, iPad, iPhones and tablets usage for business. An amazing achievement for women entrepreneurs was demonstrated to be the introduction of the cloud based platform, which allows them flexibility in accessing the system from anywhere, by 22% of 37 interviewees (P19, P12, P30, P27, P33, P35, P10, and P7). The researcher provides below a few examples, which demonstrate women entrepreneurs’ usage and preferences for ICTs and NET (Table 6.19, Illustration 2): Table 6.19: Digital Platforms & ICTs, Illustrations Illustration 2: Digital Platforms & ICTs, example quotes: Digital Platforms & ICTs usage for learning “I watch video on YouTube and I look at other makers and designers on Facebook, so, I teach myself.” (P26) “It is good learning for all learners, because we have Facebook, Twitter and we also have a website.” (P24)

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“I just goggle [to find information].” (P37) “[I learn] ... listening to the clients and to what they want. Obviously, social media...” (P9) “I do have a laptop. I use Twitter, Facebook and YouTube. I use them all. They have demonstrations on YouTube on how to do different styles.” (P6) Digital Platforms & ICTs usage for business “I haven’t yet mastered Instagram, Twitter or LinkedIn. The one I am using [for business] is Facebook.” (P37) “We use Facebook, Instagram and Twitter. We have got a website online...” (P9) “Mobile phones, I use them to contact people...”; “...for communication with customers, suppliers and family.” (P8) “Marketing is done through Facebook and Twitter.” (P17) “With the iPad we actually use for payment as well, so the iPad is crucial to myself and the business. Like I said, it will take payment through, or being able to take pictures and instantly get them up into the Facebook and Twitter.” (P10) “Facebook has been really, really good, although we use Twitter as well. Therefore, the iPad, the iPhone are in this as much, it is very quick, it happens ‘there and then’. We take pictures of the stock...we can instantly put them up for the customers...” (P10) “I promote the shop by social media, Twitter, Facebook and Instagram, which is really good because it shows...” (P34) “Yes, I use them for both [learning and business]. I use it all the time. Google is amazing for images. I use Facebook to promote my business, to tell people where my office is. I use Twitter for quick information, every day probably.” (P32) Women Entrepreneurs’ preferences in using Digital Platforms & ICTs for learning “For learning is definitively, Google!” (P13) “I mean this is going back to Google, you can find answers to everything in your life on Google.” (P17) “For learning I think would be a little bit on the iPad and probably Twitter...” (P34) I think again, my preference is Facebook. I am learning all the time on Facebook and the platform on Facebook is more user friendly, rather than Twitter.” (P7) Women Entrepreneurs’ preferences in using Digital Platforms & ICTs for business “I think Facebook, Twitter and Information Technology are like perfect, because people from all around the world will see what you put out there.” (P13) “But Twitter is easier than Facebook.” (P17) 270

“I use them all for different things. So, Facebook is very good for reaching people who you already know. Twitter is good. I think, not so much [for] knowledge-based things, if you want to share, just [for] comments and to give opinions on certain things that you already read elsewhere...” (P18) “I am trying to promote through social media and via the different platforms, on iPhone, iPad or on the laptop I guess if I am at home.” (P34) “With Facebook you have got more opportunities to put across what you wanted to do. With Twitter, you are restricted to certain amount of characters and I like to talk a lot. Twitter does not give me the free rein to go on a little bit. Facebook is my choice.” (P7) Source: F. Tomos, 2016, 2019 (Interviews, 2015)

(3)Women Entrepreneurs’ Success (WES) In this theme, the author explored women entrepreneurs’ perceptions regarding the impact of Learning and Digital Platforms & ICTs upon entrepreneurial success and business growth. It was particularly important to explore their perspective on the financial and non-financial measures of the entrepreneurial success. Furthermore, the theme also investigated the way women entrepreneurs define terms such as: entrepreneurial success from a gender and non-gender perspective, and business growth. It was very important to find out how they define themselves as a particular category of business people, and what are in their view, the other factors affecting women entrepreneurs’ success and business growth. In addition, it was of significant value to discover whether they enjoy being entrepreneurs. The author paid specific consideration, and attention, to the reasons why women entrepreneurs enjoy the entrepreneurial process. As a result of these analyses, the author of this thesis created two models: (1) ‘Women entrepreneurs’ reasons of enjoyment’ (Model 1, Figure 6.2) and (2) ‘Various factors affecting women entrepreneurs’ success’ (Model 2, Figure 6.3). The recurring percent from the Master Template for theme validation, indicating 35% to 38% recurrence, demonstrates that a reasonable percent of women entrepreneurs from the sample under analysis believe that Learning (EED) and Digital Platforms & ICTs (NET & ICTs) have an impact upon WES. A higher recurrence percent of 41% indicates the presence of various factors, which affect upon entrepreneurial success and business growth, such as: customer relationship, location, community, economic climate, networking, the quality of the products and services, family and women’s entrepreneurial profile (Model 2, Figure 6.3). Almost 62% indicating the recurrence within women entrepreneurs’ answers confirm the supposition 271

that women entrepreneurs enjoy being entrepreneurs. It was completely effective to find out the reasons for enjoyment, such as: freedom, financial independence, control, ownership, satisfaction, challenge and self-esteem. It is therefore important to link these reasons to entrepreneurial success and find solutions to success and business growth (Model 1, Figure 6.2). The author provides in the tables below, the Master Template for the validation of the themes by recurrence (Table 6.20), the Final Coding Template with the themes (Table 6.21) and examples to illustrate women’s perspectives (Table 6.22) on these themes: Table 6.20: Master Template Design for theme validation by recurrence, WES Theme Participants Recurring Percent/Validation Theme Three: Women Entrepreneurs’ Success 3.1 Learning has impact on women entrepreneurs’ success Learning and training are important for women entrepreneurs’ success 3.2 Digital Platforms & ICTs have impact on women entrepreneurs’ success Digital Platforms & ICTs are important for women entrepreneurs’ success 3.3Financial Measures for women entrepreneurs’ success 3.4Non Financial Measures for women entrepreneurs’ success 3.5Various factors affecting women entrepreneurs’ success 3.6 Defining women entrepreneurs’ success, women entrepreneurs and entrepreneurial success

3.7 Defining business growth

P18, P23, P15, P6, P11, P9, 94, P31, P37, P35, P34, P33, P5 P6, P5, P2, P18, P17, P16, P15, P13, P9, P8, P31, P26, P35, P33 P15, P5, P13, P8, P7, P31, P25, P19, P12, P30 P17, P10, P9, P24, P21, P19, P12, P30, P7, P8, P15, P13, P11 P5, P3, P2, P21, P4, P18, P15, P7, P37, P35, P34, P20, P12, P28, P35 P2, P6, P18, P17, P23, P16, P20, P15, P13, P11, P10, P9, P8, P7, P30, P31, P29, P19, P28, P27, P26, P24, P35, P34, P33, P32 P5, P18, P17, P16, P20, P11, P13, P10, P9, P8, P31, P29, P26, P24, P37, P36, 272

35%/Yes

38%/Yes

27%/Yes 35%/Yes

41%/Yes

70%/Yes

49%/Yes

3.8Enjoyment of being a woman entrepreneur and the reasons of enjoyment

P34, P33, P35, P12, P32, P30 P3, P5, P18, P23, P20, P15, P8, P7, P31, P29, P28, P26, P25, P24, P36, P37, P34, P35, P33, P21, P32, P4, P19

62%/Yes

Table 6.21: The Final Coding Template, WES Box 8 The Final Coding Template for the Interviews with thirty seven women entrepreneurs Theme Three: Women Entrepreneurs’ Success 3.1 Learning and training are important for women entrepreneurs’ success 3.2 Digital Platforms & ICTs are important for women entrepreneurs’ success 3.3 Financial measures for women entrepreneurs’ success 3.4 Non financial measures for women entrepreneurs’ success 3.5 Various factors affecting women entrepreneurs’ success 3.6 Defining women entrepreneurs’ success, women entrepreneurs and entrepreneurial success 3.7 Defining business growth 3.8 Enjoyment of being a woman entrepreneur and the reasons of enjoyment Source: F.Tomos, 2016, 2019 (Interviews, 2015)

Table 6.22: Women Entrepreneurs’ Success, Illustrations Illustration 3: Women Entrepreneurs’ Success, example quotes: Learning and training are important for women entrepreneurs’ success “It is very important because somebody especially in my business comes in not knowing anything.” (P23) “I think the training is very important.” (P23) “...I do think that long term learning in a classroom setting will probably be [the] best, because will enable me to focus and probably get the most out of the learning process.” (P15) “Yes, definitively [learning affects success].” (P33) “Totally, training is a massive part of our business.” (P35) “Yes, I think [learning] is the best way that I can move the business forward...” (P34) Digital Platforms & ICTs are important for women entrepreneurs’ success “It does [ICTs & Digital Platforms] and certainly with the marketing frame we have.”(P35) “I think [information technology] is a massive part of the business success, like Facebook.” (P33) “The technology? Yes! Our business is getting bigger every day and we update our Facebook every day and we have customers saying that they have seen us on the 273

Facebook...they said that there was a post we put on the Facebook and that’s why they came into our store.” (P13) “...because everybody has a Smart Phone, an iPhone or an iPad, so, you can always get in touch with them. Yeah, it has a big impact!” (P9) “I think they are important...they are more like followers...it just shows the popularity of the business. Like the more followers you got...the more people will know about the products...I think the growth of these...will coincide with the popularity of the business.” (P5) Financial measures for women entrepreneurs’ success “Well, turnover and profit, and increase in customers, increase in customers’ loyalty, yeah.” (P5) “I measure with the profit or...” (P13) Non-financial measures for women entrepreneurs’ success “...we are still open in the middle of the recession...It is people who come through the door.” (P15) “[I measure with]...the customer satisfaction.” (P13) “Happiness I suppose. I think that will be for me anyway.” (P17) “The fact that I still enjoy and find it challenging, and I am able to further my business if I want to.” (P8) “...By surviving as a business woman twenty eight years.” (P11) “...to see that people are enjoying what I am giving them...” (P7) Various factors affecting women entrepreneurs’ success “...the fashion trend...” (P9) “...more people coming to the town.” (P15) “It is important for business owners to understand what is going on in the area.” (P15) “I think the bigger impact is how much effort you are putting in your business.” (P6) “If you are married, you tend to have the household...They tend to look after their children more...when the children get older as well, you got to find out what do you want to do again.” (P17) “...competition...online retailers” (P7) Defining women entrepreneurs’ success and entrepreneurial success “...I think a lot of this is confidence, it is growing I think.” (P35) “Final goal is like a bigger shop, bigger kitchen and to be able to offer proper meals...” (P36) “The success would be strong minded and determined...being taken seriously...” (P34) “Success is to be ‘established’, ‘respected’, and to have strong relationship with your customers and your colleagues.” (P32) “Multitasking...Honestly, stubborn and just hard work. It is the only way to get success, if you are prepared to work hard.” (P33) “...it is a way of life...It is a hobby; it is not just a job or a business.” (P25) “I feel that I am very successful, in the way that I reap, I suppose is my happiness. I really do appreciate the fact of doing something that I actually love and it is not like work at all. It is actually balancing beautifully with the family. I get to work with some lovely girls and the customers, ‘up cherry on the top’, really.” (P10) “I feel very privileged just to be doing something that I absolutely love.” (P10) “...I feel satisfied with that.” (P11)

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“...customer satisfaction...people enjoying coming into the shop...making money as well...” (P34) “...I look as an individual...regardless whether you are a woman or a man, you will make a decision and you will do the best what you can with any business that you have. It’s not about me it’s about my learner and my staff.” (P24) Defining business growth “In my cash flow forecast, in my accounts and [having] more customers. (P37) “We are looking to year on year growth and it is a kind of percentage above last year takes.” (P35) “Everybody needs more customers, but competition is also good for the business...It makes you give a better service. Better service, better business. The customers will come to you, than to anybody else.” (P36) “It is growing your business at a pace where you stay fair and honest.” (P32) Enjoyment of being a woman entrepreneur and the reasons of enjoyment “I just wanted to do since I was a little girl...I was always inspired and dreamt to do. I just like being in control...I love and I am passionate about this place.” (P37) “It is control element... to be completely honest...I can make my own decision and drive the business in a particular direction if I want an influence on that.” (P35) “The challenges. The fact that you have only yourself to answer to, if anything goes wrong, which are your fault.” (P36) “Yes and no. I do because I really love it, but it is extremely hard work and you need a lot of help and support...It gives you independence. We are obviously your own boss...you are not following any other guidelines...from other bosses above...” (P34) “Just feeling independent. I feel in control, I feel that I have choices and I like being my own boss.” (P32) “Sometimes...Just because I am my own boss. Everything what I am doing here, is for my children and I like the fact that I can provide for my children.” (P33) “Yes. I never thought I would. I am a quiet person by nature and I was always been used to the classroom and children...I have learned to toughen up a little bit...” (P31) “I love it. Because I like seeing, people achieve. I like seeing learner achieve...” (P24) “It gives me a lot of flexibility. It makes things a lot easier for me to manage.” (P15) Women entrepreneurs “You do have to have confidence and ‘going on’ instinct. You also need many behind you. ...if you have children, you have to organise childcare and family. You have to be very driven and [also] to be able to let things go...” (P29) “We have got different qualities as men and women. Women tend to be more soft and possible more approachable...We need the men. Definitively, we need the men to be firm and often to deal with difficult situations... I learned to grow a little bit of a thick skin, I think.” (P31) “I think it takes a certain personality to stand up and say ‘I can do this and I am capable! It tends to be mainly men but a lot of women come with more drive as well...” (P14) “Is somebody who can stand on her feet and have her own opinion [and] can build the business and [to] be successful.” (P9) “I don’t see myself as an entrepreneur...even though I suppose realistically that is what I am. I feel absolutely privileged just to be doing something that I absolutely love.” (P10) 275

“Strong, strong...quite determined persons...” (P17) “Motivated. Is somebody who goes out to achieve something and achieve it and utterly seeking to achieve it and making an effort to achieve.” (P6) Source: F. Tomos, 2016, 2019 (Interviews, 2015); Note: P – Participant

(4)The following super ordinate theme is CoPs & networking. The purpose of this theme was to discover whether women entrepreneurs interviewed, belong to Communities of Practice and networking groups. A particular attention was given to finding out if CoPs & networking have any influence upon entrepreneurial learning, entrepreneurial success and business growth in the context of Digital Platforms & ICTs. About 24 of 37 women entrepreneurs interviewed (65%) belonged to various networks and professional associations, both official and unofficial groups. The author found two types of CoPs & networking groups: (1) an unofficial type of CoPs & networks and (2) official CoPs & networks. The first type of networks, was divided by the author into two subgroups, such as: (a) Local Community Groups and High Street Shopping Centre Groups, with the main purpose of collaboration and helping each other for business development and growth; (b) networking with customers both by emails and online through the means of Facebook (social media). The main purpose for this second type of groups was business promotion. The second type of CoPs & networks was classified by the author of this thesis as official networks, including the following groups and associations: the Federation of Small Businesses, the Healthcare Inspectors for Wales, Professional Bodies regarding Nutrition, Holistic Therapies Society, the Guild of Dry Cleaners and Launderers, Professional Groups for Arts and Crafts, British Florists Association, the National Training Federation for Wales, Mum’s Network with online Forums and breakfast Clubs, Women in Business Groups and Welsh Women Enterprising Network. The main purposes, for such network groups and Communities of Practices & networking groups, were the following: meeting people, finding information and help with various issues encountered within their businesses, complying with the legislation, receiving the licence of practice, professional values and ethics, legal help and advice, training, acquiring knowledge, sharing information, encouragement, support, increase in motivation and confidence to succeed in business. Based on the analysis of this theme, the researcher designed the third Model, entitled: ‘the Benefits of CoPs & networking’ (Model 3, Figure 6.4). Because of this analysis, the author suggested that the CoPs & networking phenomenon impact positively and beneficially upon WES. It also follows that the networking is facilitated by the means of 276

Digital Platforms & ICTs. The author provides in the tables below the Master Template for the validation of the themes by recurrence (Table 6.23), the Final Coding Template with the themes (Table 6.24) and the examples to illustrate womenâ&#x20AC;&#x2122;s perspectives on these themes (Table 6.25): Table 6.23: Master Template Design for theme validation by recurrence, CoPs Theme Participants Recurring Percent/Validation Theme Four: Networking & Communities of Practices 4.1 Networking Defined 4.1.1 Official CoPs & Networking Groups

P18, P17, P9, P8, P31, P27, P24, P26, P35, P36, P32, P21, P30 4.1.2 Non official Networking Groups P23, P14, P13, P11, P10, P9, P7, P29, P25, P36, P34, P33, P4, P19, P30 4.2 Networking online with customers, P18, P17, P23, P14, suppliers, entrepreneurs, friends and P13, P11, P10, P9, local businesses P8, P7, P29, P27, P25, P24, P34, P33, P36, P4, P21, P19, P30 4.3 Networking for a purpose P5, P17, P18, P15, P23, P9, P21, P10, P11, P9, P36, P8, P7, P29, P19, P24, P32, P27, 4.4 Types of CoPs & networks

35%/Yes

4.4.1 Traditional networks and CoPs

32%/Yes

4.4.2 Online networks

4.5 Advantages and benefits of CoPs & networks

P18, P17, P14, P10, P9, P31, P24, P35, P33, P32, P21, P19 P6, P23, P14, P13, P11, P10, P9, P7, P29, P24, P36, P34, P33, P32, P19 P21, P23, P17, P18, P4, P13, P11, P8, P9, P26, P10, P7, P24, P26, P35, P33, P36

41%/Yes

46%/Yes

49%/Yes

46%/Yes

Source: F. Tomos, 2016, 2019 (Interviews, 2015); Note: CoPs â&#x20AC;&#x201C; Communities of Practices; P - Participant

277

Table 6.24: The Final Coding Template, CoPs & Networking Box 9 The Final Coding Template for the Interviews with thirty seven women entrepreneurs Theme Four: Communities of Practices & Networking 4.1 Networking Defined 4.1.1 Official CoPs & Networking Groups 4.1.2 Non Official CoPs & Networking Groups 4.2 Networking online with customers, suppliers, entrepreneurs, friends and local businesses 4.3 Networking for a purpose 4.4 Types of networks 4.4.1 Traditional, face-to-face networks 4.4.2 Online Networks 4.5 Advantages and benefits of CoPs & networking Source: F. Tomos, 2016, 2019 (Interviews, 2015); Note: CoPs – Communities of Practices

Table 6.25: CoPs & Networking, Illustrations Illustration 4: CoPs & Networking, example quotes: Networking Defined: Official & Non Official CoPs & Networking Groups “Yes, I am part of a few networks, a Professional Body regarding Nutrition and Women Entrepreneurs Network.” (P18) “The only group I am really belonging to is a local group which is Women in Business.” (P17) “Yes, I do [belong to the Small Business Federation]. “I am registered with Healthcare Inspectors Wales.” (P20) “I am part of the Holistic Therapy Society.” (P2) “Whereas now, I find the shops are beginning to work together...In fact you don’t compete but you collaborate.” (P8) “...Facebook groups.” (P29) “...we belong to High Street Shopping Centre...” (P36) “I belong to Facebook. I got one Association. It is a Group because there are only four Dog Groomers Groups.” (P6) Networking online with customers, suppliers, entrepreneurs, friends and local businesses “We do network with the customers... [we stay in touch with them] ...by phone and social media.” (P9) “Yes. I have got the business followers from Facebook, Twitter, Instagram and of course, the database that I have got to email out information [which] is sent out to [the] customers.” (P34) “On Facebook I run my own page and in this way I actually communicate with my team because they are scattered all over the UK. I find that very important to communicate and be able to be in touch with people.” (P23) “Yeah, we speak to other hairdressers and beauticians all the time...We try to help each other.” (P9) “I do now network with other businesses, trying to work together.” (P29) 278

Networking for a purpose “...it helps you to get confidence as well...” (P17) “...we just encourage each other ...we can help each other...” (P17) “...connecting with people...just listening to people, asking the right questions, always contributes to my own business.” (P18) “We have cooperated events when we have seminars...” (P2) “...the shop itself and the lovely customers have been like a...Club.” (P10) “[I belong to] the National Training Federation for Wales...It is more beneficial for networking, by meeting with other people...we get further contracts.” (P24) Types of networks: Online & Face-to-Face “...Mum’s Network, for instance, where you would have breakfast Clubs...where likeminded people used to get together, to go online and go to these Forums...” (P23) “...a local group which is Women in Business. This is a group of ladies who have their own businesses...and meet once a month.” (P17) Advantages and benefits of CoPs & Networking “...likeminded people [Mum’s Networks] used to get together, to go online and to go to these Forums...” (P23) “I think it is like day to day running of things. It is how you deal with certain things...and obviously, connecting with people...just listening to people, asking the right question...” (P18) “That’s quite nice, because we keep our opinions on business and try to be supportive to each other...” (P17) “...because I know if I have any problems here, they are behind me, they are good as an organisation [Small Business Federation].” (P17) “Yeah, we just encourage each other and if we had a bad week, or we found particularly difficult to find information on something, we can help each other to go through...it helps your confidence...” (P17) “Just locally, I get the lady near my coffee bar, she just started to sell. So, I help her to promote her business in our establishment.” (P14) “...a community thing where they have a buffet and people speaking how to improve the businesses, how to interact with the customers and you can learn a lot from there.” (P13) Source: F. Tomos, 2016, 2019 (Interviews, 2015)

(5)The fifth super ordinate theme is the last theme under analysis and is entitled Entrepreneurial Activity/Process and Entrepreneurial Profile (EA & EP). This theme emerged from the thematic analysis and is a blended and complex theme, in the sense of encompassing various elements such as: entrepreneurial process/activity, entrepreneurial capabilities and profile, the modality of starting up an enterprise and the engine behind starting up an enterprise and becoming a woman entrepreneur. The analysis of this theme indicates that women entrepreneurs started their enterprises as a result of a passion, opportunity, retirement, desire of ownership, a dream, the need of flexibility and balance in family and business life, health issues, the desire of independence, support, and 279

encouragement from husbands and families. Most of them were sole traders, in family business, in partnership with husbands, fathers, or having a franchise. For some women entrepreneurs, the businesses were related to their hobbies, some were creative and artistic, developing a unique business within a niche market and some of them started with no experience in the field.

Other important aspects that emerged from the

investigation of this theme are related to the reasons of starting an enterprise, and the modality of setting up the business. Additionally, the author managed to extract from this analysis an effective definition of the entrepreneurial process and to design two more models such as: ‘Entrepreneurial Activity/Process’, and ‘Women capabilities and characteristics’ (Model 4, Figure 6.5; Model 5, Figure 6.6). The author provides in the tables below the Master Template for the validation of the themes by recurrence (Table 6.26), the Final Coding Template with the themes (Table 6.27) and the examples to illustrate the validity of those themes (Table 6.28): Table 6.26: Master Template Design for theme validation by recurrence, EA & EP Theme Participants Recurring Percent/Validation Theme Five: Entrepreneurial Activity and Entrepreneurial Profile 5.1 Women entrepreneurs capabilities and characteristics 5.2 Women entrepreneurial activity/process defined 5.3 The engine/reason of starting up an enterprise & becoming a woman entrepreneur

5.4 The modality of starting up an enterprise

P4, P3, P17, P18, P35, P34, P33, P15, P9, P10, P24, P21, P36, P6, P30, P12 P4, P36, P26, P35, P21, P31, P29, P24, P7, P11, P13, P8, P23, P16, P20, P15 P1, P18, P37, P34, P33, P4, P12, P21, P29, P27, P25, P24, P7, P36, P24, P19, P12, P31 P15, P30, P4, P11, P10, P28, P27, P14, P8, P7, P26, P20, P31, P11, P17, P13

Source: F. Tomos, 2016, 2019 (Interviews, 2015)

280

43%/Yes

49%/Yes

43%/Yes

Table 6.27: The Final Coding Template, EA & EP Box 10 The Final Coding Template for the Interviews with thirty seven women entrepreneurs Theme Five: Entrepreneurial Process/Activity and Entrepreneurial Profile 5.1 Women entrepreneurs capabilities and characteristics 5.2 Women Entrepreneurial Process defined 5.3 The reason of starting up an enterprise and becoming a woman entrepreneur 5.4 The modality of starting up an enterprise Source: F. Tomos, 2016, 2019 (Interviews, 2015)

Table 6.28: EA & EP, Illustrations Illustration 5: Entrepreneurial Process/Activity and Entrepreneurial Profile, example quotes: Women entrepreneurs capabilities and characteristics “Strong, strong...quite determined persons...” (P17) “Motivated. Is somebody who goes out to achieve something and achieve it and utterly seeking to achieve it and making an effort to achieve.” (P6) “I would say very brave. I think you must be clever as well...” (P3) “...stubborn and hard work...” (P33) “...strong minded and determined and successful and being taken seriously...” (P34) “It’s not about me. It’s about my learner and my staff.” (P24) Women Entrepreneurial Process defined “...likeminded people [Mum’s Networks] used to get together, to go online and to go to these Forums...” (P23) “I think it is like day to day running of things. It is how you deal with certain things...and obviously, connecting with people...just listening to people, asking the right question...” (P18) “[It is ] talking to customers...serving the people and being happy to do it...it is nice to see how they walk into your shop and feel how pleasurable it is and to do shopping...I feel satisfied with that. We also do a service that is difficult to find nowadays...alterations and repairs.” (P11) “Yeah, obviously! It is a risk from money point of view. It is always a risk that the business might work or might not and you depend very much of the customers. It is a risky process.” (P3) “I think is keeping your business consistent and having in mind where you need to be and every day just work a little bit towards that. (P15) “...we have two small children and we have to joggle...” (P15) “I make sure that the lights are on in the shop [and everything] looks presentable. Then, I try to make my paperwork done and throughout the day I am around the customers. I do a bit of networking on Facebook and I look to the other businesses in the area. I try to keep up to date with the town information...” (P15) “In the morning I do yoga or I work out classes in the gym, I go to my job as an architect or I work on my business. So I answer emails, contents for Twitter, Facebook...” (P18) “...teaching them over the phone, over the computer...” (P23)

281

The reason of starting up an enterprise and becoming a woman entrepreneur “My interest for food and hygiene came from my own healing from a skin condition...” (P18) “...I studied three D and landscape...I have been doing exhibitions and shows [and] I met with creative designers...” (P34) “I left the Police...and I opened my own coffee shop...” (P33) “I did research via internet to get the business off the ground.” (P33) “So, I decided and my husband persuaded me to open up my own shop, because this is my hobby and I just made it into a business.” (P13) The modality of starting up an enterprise “I myself had no experience in carpet trade...My husband has worked with his father...” (P1) “...I am the owner of the business...” (P33) “...my husband and I left our professions and decided to start a business.” (P31 Source: F. Tomos, 2016, 2019 (Interviews, 2015)

6.7 Focus Group and Interviews Content Analyses In order to increase the validity and reliability of the results, the author of the thesis conducted a third type of analysis: Focus Group and Interviews Content Analyses. (1) The first theme under scrutiny was Learning. The majority of women from the FG indicated that, they learn with Digital Platforms & ICTs (FGP1, FGP2, FGP4, and FGP5), also, 20% mentioned the online role models, and 20% learned by reading books: “Yeah, I use the internet every day. I use for both learning and business...Definitively, on social media.” (EED, Methods of learning, FGP1)

The main methods of learning employed by women entrepreneurs from the interviews were as follows (Table 6.29): (1) social learning (observation-based, role model); (2) adult learning (experience-based) (EED, P2, P5, P17); (3) lifelong learning/informal (errors, everyday life, attending conferences, associations, networks) (EED, P1, P32); (4) entrepreneurial learning/informal (EED, P34, P8). “I suppose learning over the years has been ‘trial and error’” (EED, Methods of learning, P1) The main model of learning used by women entrepreneurs is the Andragogical Model of Learning, which is self-directed, participative and reflective, leading women entrepreneurs towards the achievement of the self-actualization (Maslow, 1993): “I learn best through sharing with other people who already have similar experience...” (EED, Methods of learning, P18) 282

The author of the thesis highlighted also, the way women entrepreneurs learn: (a) online (P17), (b) to suit their learning needs (P30) and (c) according to the particular stage of their business life cycle: beginning (P20; P34; P15), growth (P5; P19; P12), maturity (P16; P7; P1; P25) and decline (P4). Table 6.29: Women Entrepreneurs Learning Methods (Interviews) WE Learning Participant Method Women Entrepreneurs Methods Number Percent -Trial & Error P1, P33, P36, Adult -Adult Courses P15, P2, P34, Learning 9 24% -ExperienceP18, P24, P19 Based -Inter-business learning -By doing -Informal P5, P17, P3, P7, Lifelong 10 27% -Reading P4, P32, P8, Learning -Listening P17, P35, P21 -Agents -Exhibition -Role Model P13, P6, P10, Social 16 43% -Observational P20, P12, P19, Learning -Online P2, P27, P32, & Digital learning P20, P25, P18, Platforms -Social Media P17, P5, P9, P4 -You Tube Source: F. Tomos, 2017, 2019

(2) The second theme analysed with Content Analysis (CA) was Digital Platforms & ICTs. About 60% of women entrepreneur participants within the FG answered that, they use Digital Platforms for learning and business, and only 20% use for personal life (FGP3; FGP5). “A lot of my business comes from Facebook, Twitter... I use daily the iPad, Smart Phone...” (NET & ICTs, FG, FGP3) “...I have two Facebook pages. One is my personal one and one is my work one. I use Facebook and Twitter.” (NET & ICTs, FG, FGP5) The CA of 37 interviews with women entrepreneurs discovered that, women entrepreneurs used networking technologies (LinkedIn, Facebook and Twitter), social networking, cloud computing, and mobile technologies (Digital Platforms & ICTs, Is: P5, P26, P20, P19). The author provides below a few examples:

283

“...We are on Twitter quite a lot, Instagram... We do use social media, to get a lot of information out there.” (NET & ICTs, Is, P5) “Utilizing Facebook and now Ettzi selling platform, it is incredible.” (NET & ICTs, Is, P26) “...our entire system runs from Cloud-based platform, and that keeps a track on the stock... generating monthly reports.” (NET & ICTs, Is, P12) The analysis indicated also that, Gen Y (41%) has higher connectivity and participation in online communities, than Gen X (38%) (Table 6.30): Table 6.30: Generation Y & X. Age versus Connectivity Generation Yes No Age Participants Percent Participants 18-37 P2, P5, P13, Gen Y P33, P34, P6, (1980-2000) P7, P9, P15, 41% P20, P26, P37, P29, P35, P12 38-75 P17, P18, P24, P1, P8, P11, Gen X P27, P32, P36, 38% P16, P28, P31 (1961-1979) P3, P10, P14, P23, P25, P4, P19, P21

Percent -

16%

Source: F. Tomos, 2017, 2019

(3) The third theme analysed with CA was CoPs & networking. The author analysed 37 interviews with CA.

The analysis highlighted the role of socialization in acquiring

knowledge, the benefits from the social relationships and membership, and the role of CoPs and networking. The following examples provide evidence of the crucial role CoPs & networking play for women entrepreneurs, in acquiring knowledge and information, and achieving business success. “I am part of Holistic Therapy Society. They are Professional Guild Beauty Therapist. I receive letters, magazines, we have cooperated events...seminars...” (CA, CoPs & networking, Is, P2) “[networks] ...connecting with people...just listening to people, asking the right questions, always contributes to my own business.” (CA, CoPs & networking, Is, P18)

284

The CA for the FG indicated that 20% of the women entrepreneurs (FGP1) believe that CoPs & networking are a catalyst for business and personal life, and 20% answered that social media is ‘a voice’ for women (FGP5). The majority of women entrepreneurs answered that ‘face-to-face women only’ networks are encouraging and transparent (FGP4, FGP5, FGP2, FGP3). (4) The fourth theme analysed with CA was WES. The focus of the analysis was on the meaning and the interpretation given by the women entrepreneurs to ‘success’. About 40% of FG women indicated that, the meaning of WES is ‘a good reputation’ (FGP1, FGP2), 20% indicated ‘financial stability’, 40% indicated ‘balance in life’ and independence and the majority answered ‘happiness for self and others’ (FGP1, FGP3, FGP4). Similarly, the CA of the interviews with women entrepreneurs provided the following answers: (1) 10.8% financial stability and financial independence (P1, P2, P17, P18); (2) 21.6% customer satisfaction and quality products/services (P1, P2, P5, P24, P34, P36, P7, P19); (3) 24.3% flexibility, control, style of life and ownership (P18, P7, P26, P13, P33, P4, P12, P21, P30); (4) 5.4% surviving a long period of time. Below the author offers a few examples: “I measure success by customers’ loyalty” (CA, WES, Is, P5) “...being independent and stable...” (CA, WES, Is, P13) “...success as a woman entrepreneur is basically being able to juggle home, life, a husband, two children and a business and hopefully, to do well in both.” (CA, WES, Is, P7) (5) The last theme analysed was Entrepreneurial Activity and Entrepreneurial Profile. The CA demonstrated the existence of gender issues. Thus, 40% of women entrepreneurs from FG indicated ‘motherhood, childrearing, childcare and family responsibilities’ and 40% indicated ‘male culture and glass ceiling’ as well.

The majority of women

entrepreneurs from FG emphasised the need of ‘flexibility, independence and time balance’. Similarly, the CA of the interviews provided the following information: (1) 21.6% of women entrepreneurs had a sense of belonging and role identity (P31, P37, P12, P17, P24, P34, P23, P26); (2) 10.8% highlighted the barriers of male culture, segregation and glass ceiling (P16, P35, P12, P34); (3) 10.8% emphasised personal barriers such as: 285

motherhood, childrearing, childcare, lack of childcare policies and flexibility (P15, P17, P18, P21). In the next table (Table 6.31), the author provides further details: Table 6.31: EA & EP (Reasons of starting entrepreneurship & Role Identity) Reasons WE Participants Percent Lack of jobs, interest, the P24, P19, P16 8.1% desire to achieve Motherhood, childrearing, P17, P33, P7, P9, P10, P15, P23, 32.4% wives, maternity leave, P25, P29, P35, P19, P21. childcare Children getting older, P17, P30, P36 8.1% later stage in life Health and healing issues P8, P18, P17, P19 10.8% Being Mums, being role P11, P7, P21, P12, P4 13.5% models for children, having parents entrepreneurs Financial freedom, P33, P34, P6, P21, P37 13.5% providing for the children, Control, independence Source: F. Tomos, 2017, 2019

From the table above (Table 6.31) it is suggested that, one of the main reasons of starting entrepreneurship was â&#x20AC;&#x2DC;motherhood, childrearingâ&#x20AC;&#x2122;. Therefore, the author offers more details regarding women entrepreneurs and the number of children they have (Table 6.32): Table 6.32: Women entrepreneurs & Children (CA, Interviews) Number of Children WE Participants None P30, P1, P22, P5, P13, P18, P24, P34, P3, P14, P16, P20, P26, P28, P31 One P2, P32, P6, P9, P11, P35, P37, P30, P19 Two P17, P27, P33, P36, P7, P8, P10, P15, P23, P25, P29, P24, P21 Adult Children P26, P8, P11, P27, P36 Total women with 22 children Total women without 15 children

Percent 40% 25% 35% 13.5% 60% 40%

Source: F. Tomos, 2017, 2019

About 60% of women entrepreneurs had young children when they started their businesses. In addition, 24.3% of women started/joined a family business in partnership with their husbands, 5.4% were only partners within the business, and 2.7% were partners 286

with their parents. Examples of personal/gender issues (inadequate/lack of childcare policies) are provided by the author below: “We try not to pay for childcare, unless we do, because is very expensive” (CA, Gender/Policies, Is, P15) “I am not just a business woman, I am a family woman as well, I have got a young baby and a husband” (CA, Gender/Mother&Wife, Is, P9) “I had two small children [and] I couldn’t go in full time work, so I thought this will really suit me with the hours” (CA, Gender/Motherhood, Is, P23) “...At the moment my priority it has to be my son. I have a three years old son...” (CA, Gender, Childcare, Is, P35) “It is a lot of stress involved...I have to try and still maintain a family life...women find more difficult than men, because of the domestic responsibilities posed on us...” (CA, Gender, Household, Is, P19) The results of the qualitative analysis with CA enhanced the outcomes of quantitative data analysis, and qualitative data analyses with IPA and TA. Following the emergent results, the author of the thesis strengthened the emergent theoretical models (Fig 6.2; Fig 6.3; Fig. 6.4; Fig 6.5; Fig 6.6; Fig. 6.9), and reinforced and adjusted the emergent themes from the tables (Tables 6.33; 6.34). 6.8 Summary of Section Six Quantitative data analysis was rooted in a Survey with 150 women entrepreneurs. The author tested the Hypotheses and answered the Research Questions by means of statistics with SPSS.

Thus, the author employed exploratory research methods, correlation,

regression, modelling, FA, TFA, and partial correlation. Although, the hypotheses were supported within the exploratory research methods, there were contradictory results within FA and TFA, which required further investigation by using qualitative data analyses. The researcher employed mixed methodology design. Qualitative data was based on the analyses of 37 interviews with women entrepreneurs in the South East Wales and a Focus Group with five women entrepreneurs (WE), participants to a networking event. The number for the FG was sufficient for this analysis, as the minimum required 287

in a FG is three participants. Qualitative Data was analysed with IPA, ThA, TA and CA. The extremely laborious and innovative procedures used by the researcher led to better understanding of the results from Quantitative Data Analysis, and improved interpretation of results. Moreover, Qualitative Data Analyses indicated the crucial role of the CoPs & networking and Gender, and provided the rationale behind the Women Entrepreneurs choice of starting entrepreneurship. The next section discusses Data Interpretation.

288

Figure 6.2: Reasons of Enjoyment.

REASONS OF ENJOYMENT

• • •

Behavioural

Independence Flexibility Juggling

• • • •

Social

• • •

Communicating Seeing People Equal to men Social Identity/Role

• • • • •

Personal

Innovation

Self-Concept Satisfaction Flexibility Autonomy Career

Creativity Innovation Uniqueness

Power Control

• • • •

Working for yourself Control Ownership Glass ceiling

Vision Family & Gender • • • • •

• • •

Parental Care Having free time Motherhood Childrearing Work/Life Balance

Challenge Dream Hobby

Financial stability • •

289

Financial Independence Survival

Figure 6.3: Various factors affecting women entrepreneurs’ success Various Factors Affecting Women Entrepreneurs’ Success

Commercial

Emotional

Competition Big Shops Online Retailers

Friends & Family Support

Cognitive Experience in the field, sector and activity Knowledge

Economic & Politic Recession Money Economic Climate Risk

Personal

Fashion

Family Responsibilities Children Care

Brand Season Makes

Social (Networking)

Relational

Good Knowledge of the Local Area Location A Sense of Community Collaboration

Customer Understanding Customer Loyalty Customer Financial Power Buying Power of the Community

Reputation

Gender

Quality of the Product Quality of the Service Customer Satisfaction

Supportive Networks Motherhood Childrearing Glass Ceiling Policies

290

Figure 6.4: Benefits of Networking & CoPs

COGNITIVE Information Knowledge Learning Training

SOCIAL

PERSONAL & GENDER

Learn from the success of others Gain authority & boast your career Gaining social skills Social identity A Voice

Immediate contact & feedback Breaking through the Glass Ceiling Avoiding personal and social barriers

BENEFITS of Networking & CoPs ECONOMICAL & FINANCIAL Business expansion & promotion Business Growth & Development Increase in the number of customers

EXPERIENTIAL Participation in local events, fairs and exhibitions

EMOTIONAL Sharing & Collaboration Helping each other Acting as a Community

291

Figure 6.5: Women Entrepreneurs’ Capabilities & Characteristics

• Motivated and passionate • Photographic, visual, creative • Creative • Innovative

• Brave, hard, strong • Taking risk, clever • Determined, confident • Independent, belief

Power & Ownership

Emotional & Artistical

Social & Personal/ Gender

Active & Energetic

• Sharing • Building a social life • Mums & wives • Motherhood • Childrearing • Equal to Men

• Multitasking • Persistent • Hard working • Dynamic

292

Figure 6.6: A Model of Entrepreneurial Activity & Entrepreneurial Profile

LEADERSHIP

MANAGERIAL

LEARNING & TRAINING

Promotion Building reputation Risk

Marketing and promotion Sales Law, Taxes Finances Accounting

Information & Knowledge

Planning for survival and growth Trends Vision

SALES & CUSTOMER RELATIONSHIP

Customer service Customers relationship Customer Database Customer Feedback Customer satisfaction Quality Service Quality Product

Research , gathering information Human Resources & Staff training Reports

SOCIAL

Local Community Planning for events Social Identity

Considering Gender Issues Networking & Collaboration

293

Learning & training Self taught

PERSONAL AND GENDER Family Responsibilities Wives Balance in life Motherhood Childrearing

Personal Matters & Goals Self- Concept Passion/Career

DIGITAL PLATFORMS & ICTs

Using creatively Digital Platforms & ICTs

DAILY ROUTINE

Selling Dealing with customers Stock Management Recording Sales

Communicating with customers & additional services Social Media

(alterations, maintenance, fitting, guidance, advise, conselling)

294

CREATIVITY & INNOVATION

Creativity Innovation Dream

Uniqueness Niche market

Table 6.33: Emergent Themes from Qualitative Data Analysis (Focus Group & Interviews) Emergent Super Ordinate Themes Themes & Sub-themes 1. Learning 1.1 Methods of Learning Lifelong Learning/Adult 1.1.1.Formal learning class-based 1.1.2 Formal learning non class-based Adult Learning 1.1.2.1 Learning from mentors and family members 1.1.2.2 Traditional learning self-taught with books 1.1.3 Experience-based learning 1.1.3.1 Trial & Error (by doing) 1.1.3.2 Learning from the experience of others 1.1.4 Informal learning: acquiring knowledge & information Lifelong Learning 1.1.4.1. Reading books, magazines, watching TV, news, studies Social Learning 1.1.4.2 Digital Platforms (Google, Social Media, Internet) 1.1.4.3 Information from suppliers, customers, reps, trainers, competitors, Welsh Government courses, fairs, exhibitions, literature, research 1.1.4.4 Information from Face-to-Face & online networking 1.1.5 Learning with Digital Platforms & ICTs 1.2 Styles of Learning 1.2.1 Experiential learning style 1.2.2 Networking & online style 1.2.3 Auditive learning style 1.2.4 Visual learning style 1.2.5 Flexible learning style 2. Digital Platforms & ICTs 2.1 Digital Platforms & ICTs usage for learning 2.1.1 Social Media usage for learning (Facebook & Twitter) 2.1.2 Digital Platforms accessed via iPhone, laptop, tablets and iPad for learning 2.1.3 Internet and YouTube usage for learning 2.1.4 Google and Google Analytics for learning 2.2 Digital Platforms & ICTs usage for business 2.2.1 Digital Platforms usage for business (Skype, Facebook, Twitter, Pinterest, Instagram, LinkedIn, Ettzi) 2.2.2 iPad, iPhone, Smart Phone and Androids usage for business 2.2.3 Internet, websites, YouTube and Google usage for business 295

2.2.4 Laptop, computers and tablets usage for business 2.2.5 Cloud based platform for business 2.3 Preferences for Digital Platforms usage for learning 2.3.1 Women Entrepreneurs’ preferences in accessing Social Media for learning 2.3.2 Women Entrepreneurs’ preferences in accessing Digital Platforms for learning 2.3.3 Women Entrepreneurs’ Preferences for using Google and YouTube for learning 2.4 Preferences for Digital Platforms &ICTs for business 2.4.1 Women Entrepreneurs’ Preferences in using Social Media for business (Facebook, Twitter, Instagram) 2.4.2 Women Entrepreneurs’ Preferences in using ICTs for accessing Digital Platforms (tablets, iPad, iPhone) 3.Women Entrepreneurs’ Success 3.1Learning and training are important for women entrepreneurs’ success 3.2 Digital Platforms are important for women entrepreneurs’ success 3.3 Various factors affect women entrepreneurs’ success 3.4 Financial measures for women entrepreneurs’ success 3.5 Non financial measures for women entrepreneurs’ success 3.6 Women entrepreneurs defined 3.7 Various perspectives on women entrepreneurs’ success definition & measurement 3.8 Various perspectives on business growth definition 3.9 Enjoyment of being a woman entrepreneur and reasons of enjoyment 4.Communities of Practice and 4.1 CoPs & Networking defined Networking 4.1.1 Official Networking Groups and CoPs 4.1.2 Non Official Networking Groups 4.2 Networking online with customers, suppliers, entrepreneurs, friends and local businesses 4.3 Dual aspect of CoPs & Networking: traditional Face-to-Face and online 4.4 Women entrepreneurs acquire knowledge and information through traditional Face-to Face networks. 296

5.Entrepreneurial Process Entrepreneurial Profile

4.5 Women entrepreneurs acquire knowledge and information through online participation in informal and online community groups. 4.6 Women entrepreneurs network with customers. 4.7 Women entrepreneurs participate in community-centred networks through social media/digital platforms 4.8 Women join networks to help their businesses. 4.9 Women entrepreneurs prefer women only networks. 4.10 Traditional Face-to-Face networks, support, inspire, encourage and keep women entrepreneurs informed. 4.11 Networks support social life, friendship and provide crucial information for businesses 4.12 Advantages and benefits of networking & 5.1 Women entrepreneurs capabilities and characteristics 5.2 The reason of starting up an enterprise and becoming a woman entrepreneur. 5.2.1 Ownerâ&#x20AC;&#x2122;s sector experience 5.2.1 Ownerâ&#x20AC;&#x2122;s knowledge & studies 5.2.3 Motherhood & Childrearing 5.3 The modality of starting up an enterprise 5.3.1 Opportunity & innovation 5.3.2 Partnership with husbands and family members (Father/Investors) 5.3.3 Challenge and choice at a certain period in life 5.3.4 Health issues 5.4 Entrepreneurial Identity 5.4.1 Professionals & Freelancers 5.4.2 Owners of business 5.4.3 Mums & Wives 5.4.4 Business Women 5.4.5 Parents with Family Responsibilities 5.5 Entrepreneurial process & Policies 5.6 Entrepreneurial process & gender issues 5.6.1 Gender is an issue in certain business sectors to be overcome by networking 5.7 Entrepreneurship & Policies 5.7.1 Adequate Entrepreneurship Policies 5.7.2 Adequate Social Policies

Source: F. Tomos, 2017, 2019

297

Figure 6.7: Theoretical Entrepreneurship Model for Women Entrepreneurs’ Success (Qualitative Data) WOMEN ENTREPRENEURS’ SUCCESS Defining women entrepreneurs’ success Women entrepreneurs defined Business Growth defined Enjoyment & reasons of enjoyment Various factors affecting women entrepreneurs’success Financial measures Non-financial measures of women entrepreneurs’ success

LEARNING Methods of Learning Experience-based -Trial & Error -Learning from others Learning with Digital Platforms & ICTs Informal learning: acquiring knowledge & information: -Online information -Information from various sources -Information by Face-to-Face & online Networking Formal learning class-based Formal learning non class-based -Learning from mentors -Traditional learning with books

DIGITAL PLATFORMS & ICTs Digital Platforms & ICTs Usage for Learning -Digital Platforms usage for learning (Facebook & Twitter) -Digital Platforms via iPhone, iPad, laptop and tablets for learning -Internet, YouTube and Google usage for learning Digital Platforms & ICTs Usage for Business -Digital Platforms usage for business (Skype, Facebook, Twitter, Pinterest, Instagram, LinkedIn) -iPad, iPhone, Smart Phone and Androids usage for business -Internet, website, YouTube, Google for business -Cloud –based platform for business Preferences for Digital Platforms & ICTs Usage for Learning -Social Media for learning and Gender Preferences for Digital Platforms & ICTs Usage for Business -Digital Platforms for business & Gender -Women Entrepreneurs’ preferences for ICTs (tablets, iPad, iPhone) in accessing Digital Platforms

Styles of Learning

-Experiential learning style -Online & Networking learning style -Auditive learning style -Visual learning style -Flexible learning style

COMMUNITIES OF PRACTICES & NETWORKING CoPs & Networking defined -Official Networking Groups & CoPs Non-Official Networking Groups Networking for a PURPOSE -Women entrepreneurs join networks to help their businesses -Networks support social life & friendship Women entrepreneurs acquire Knowledge by Face-to-Face networks Women entrepreneurs acquire knowledge and information by online participation Types of Networks -Online & Face-to-Face networks Networking with customers, suppliers, entrepreneurs, friends and local communities Women Entrepreneurs participate in community-centred networks by means of Social Media Benefits & Advantages of CoPs & Networking -Networking is crucial for the business Women entrepreneurs prefer women only networks Breaking Glass Ceiling and Barriers by Networking

ENTREPRENEURIAL PROCESS & PROFILE Reasons of setting up an enterprise & becoming a woman entrepreneur Modalities of starting up an enterprise Women entrepreneurial process defined Women Entrepreneurs capabilities & characteristics Entrepreneurial Identity Types of entrepreneurial activities Gender is not an issue in the business world Gender is an issue for a woman entrepreneur -Gender is an issue in certain business sectors (construction, telecommunications) -Gender can be overcome by participating in networks Entrepreneurial research in the past ignored gender issues

298

Figure 6.8: Andragogical Model of Learning:

METHODS OF LEARNING

STYLES OF LEARNING

PREFERENCES FOR LEARNING University & College Environment LEARNING NEEDS: Digital Platforms & ICTs Marketing & Promotion Accounting

Methods: Formal, classbased; Traditional with books; Lecturer delivery Styles: Auditive; Visual; Online; Women Networks.

Methods: Digital Platforms usage (Facebook & Twitter, LinkedIn); Digital Platforms accessed via iPhone, laptop, iPad, Tablets; Google & Google Analytics; YouTube. Styles: Flexible, Online and Networking

Methods: Acquiring knowledge and information by participation, communication and sharing; Women only networks. Styles: Face-to-Face and online networking by means of Digital Platforms & ICTs

Digital Platforms & ICTs Environment

Communities of Practices & Networking Environment

Method: Experience-based learning (Trial & Error); Learning from entrepreneurs, customers, suppliers Style: Experiential, Flexible, Online, Face-to-Face, Visual and Networking Entrepreneurial Environment

Methods: Self-taught; Informal by searching for news and reviewing the press.

Methods: Role model-based, Formal learning non class-based Styles: Flexible learning

Styles: Flexible; Traditional with books; Online women entrepreneurs role models. Personal Environment

Source: F. Tomos ÂŠ 2017, 2019

299

Familial Environment

Table 6.34: Solutions to Research Questions: Q3; Q5; Q6 Research Question Solution/Outcome from Analysis Research Question 3: What are the Quantitative Data Analysis models, methods, styles of learning Experience-based (20%) women entrepreneurs employ, and what Multiple methods (role model, asking, are their learning needs and preferences doing, applying) (52.7%) in the context of Digital Platforms & Learning needs: Digital Platforms ICTs? (15.5%); marketing, sales and promotion (16.9%); Styles of learning: interactive (88%); networking (50.7%). Learning with Digital Platforms & ICTs: YouTube (46.7%); Facebook (75%); mobile phones (75.3%); wireless and internet at home (86.7%). 64.7% (of 150) have multiple entrepreneurial competences (sales, marketing, management; promotion, accounting, Facebook). Qualitative Data Analysis Andragogical Model of Learning (Figure 4.49) Styles of learning: flexible informal with Digital Platforms and ICTs; Networking (Focus Group). Methods of learning: traditional classbased, experience-based, role model-based (Focus Group). Methods of learning: experience-based learning (trial & error). (Interviews, TA); experience-based (learning from entrepreneurs, customers, suppliers) (Interviews, TA); acquiring information and knowledge from suppliers, customers, trainers, Government courses, reps, fairs, exhibition, CoPs, etc.). Styles of learning: flexible, auditive, visual, experiential, online, networking (Interviews). Communities of Practices: customers, suppliers, other entrepreneurs, women entrepreneur groups, associations. Research Question 5: How do women Quantitative Data Analysis learn and acquire knowledge in the Factor Analysis (FA EED): Learning from context of CoPs & networking and information, communication, participation Digital Platforms & ICTs, in order to and sharing; learning by networking; succeed? Factor Analysis (FA NET): Digital Platforms & ICTs for business and learning.

300

Factor Analysis (FA CoPs): Digital Platforms & ICTs help participation in networking and CoPs. Qualitative Data Analysis Methods of learning: Digital Platforms & ICTs (Facebook and Twitter, Google, YouTube, laptops, iPad, iPhones, tablets, internet). Face-to-Face networking and online networking with suppliers, customers, women entrepreneurs (CoPs) (Interviews). Preferences: iPad, iPhones, Tablets (Is). Research Question 6: What is the Role of Quantitative Data Analysis CoPs & networking? A) Exploratory Relationship Analysis (Categorical/Scale Variables): (1) CoPs & networking * WES – moderate relationship, Chi-Square=56.69, p<0.05, Cramer V=0.31; (2) EED * CoPs & networking significant positive relationship, rho=0.215, sig=0.008, p<0.01; (3) NET & ICTs * CoPs & networking – moderate significant relationship, r=0.310-0.406, sig.=0.000. B) Exploratory Partial Correlation: Impact of NET&ICTs * WES is controlled by CoPs & networking, r=0.202, sig.=0.007, p<0.01 (one-tailed). C) FA CoPs&networking, 85.6% explained variance in dataset; labels: (1) ICTs help CoPs&networking; (2) Digital Platforms & ICTs helps CoPs & networking; KMO=0.947, BTS, sig=0.000. D) TFA CPN, r=0.576-0.942; KMO=0.954, Variance explained 79.5%; (1) Laptops & computers help CoPs (0.962); (2) Mobile phones help CoPs (0.947). TFANET * TFAMSC, Factor extraction, R=-0.404, sig.=0.000, p<0.01; partial correlation, Controlling variable TFACPN; TFAEED * TFAMSC, Factor extraction: R=-0.197, sig. = 0.000, p<0.01, partial correlation, Controlling variable = TFACPN. Qualitative Data Analysis Focus Group: Method of Analysis: IPA & TA. Emergent Theme: CoPs & networking. Majority of WE belong to CoPs & networking groups. WE gain support, legal help, and encouragement; 301

WE acquire knowledge through networking. Networks: online/Face-toFace/official/unofficial. FtF – very successful, impact upon WES/BG. Major theme – CoPs & networking impact on entrepreneurial learning. Final Coding template. Recurrent theme: 20%. Unique theme: at least 10%; Controversial theme: at least 30% - Gender: Women only networks – successful for learning and supporting WE. Interviews: Method of Analysis: IPA & TA. Superordinate theme – CoPs & networking. 65% (of 37) belong to networks, professional association, official/unofficial networks. M3 (Fig 4.45) ‘Benefits of CoPs & networking’. CoPs * WES, positive impact; CoPs & networking affect WES/BG by NET & ICTs. Recurrent theme: 20%. Final Coding Template. CoPs & networking influence upon learning (EED) and WES. Official/Unofficial networks used for acquiring knowledge, information, legal advice, training, encouragement and business promotion. Interviews/Method of Analysis – CA Crucial role of CoPs & networking for WE in acquiring knowledge, information and achieving success. Source: F. Tomos, 2017, 2019

302

Figure 6.9: Theoretical Business Model for Women Entrepreneurs’ Success (Final) WOMEN ENTREPRENEURS’ SUCCESS

LEARNING

Defining women entrepreneurs’ success Women entrepreneurs defined Digital Platforms & ICTs impact on women entrepreneurs’ success (Laptops, PC, Mobile Phones and Tablets) (Twitter & Facebook) Learning determines women entrepreneurs’ success Business Growth defined Enjoyment & reasons of enjoyment Various factors affecting women entrepreneurs’ success Financial measures Non-financial measures of women entrepreneurs’ success

Methods of Learning Experience-based: -Trial & Error -Learning from others Learning by CoPs & Networking through participation, communication and sharing information; Learning with Digital Platforms & ICTs; Informal learning: acquiring knowledge & information: -Online information -Information from various sources -Information by Face-to-Face & online Networking Formal learning class-based; Formal learning non class-based: -Learning from mentors -Traditional learning with books

DIGITAL PLATFORMS & ICTs

Styles of Learning

-Experiential learning style -Online & Networking learning style -Auditive learning style -Visual learning style -Flexible learning style Preferences for Styles of Learning Types of learner

COMMUNITIES OF PRACTICES & NETWORKING CoPs & Networking defined -Official Networking Groups & CoPs Non-Official Networking Groups Networking for a PURPOSE -Women entrepreneurs join networks to help their businesses -Networks support social life & friendship Women entrepreneurs acquire Knowledge by Face-to-Face networks Digital Platforms & ICTs help participation in CoPs & Networks (Laptops, PC, Mobile Phones) Digital Platforms helps CoPs & Networks (Twitter & Facebook) Women entrepreneurs acquire knowledge and information by online participation Types of Networks -Online & Face-to-Face networks Networking with customers, suppliers, entrepreneurs, friends and local communities Women Entrepreneurs participate in community-centred networks by means of Digital Platforms Benefits & Advantages of CoPs & Networking -Networking is crucial for the business Women entrepreneurs prefer women only networks

Digital Platforms & ICTs Usage for Learning -Social Media usage for learning (Facebook & Twitter) -Digital Platforms via iPhone, iPad, laptop and tablets for learning -Internet, YouTube and Google usage for learning Digital Platforms & ICTs Usage for Business -Social Media usage for business (Skype, Facebook, Twitter, Pinterest, Instagram, LinkedIn) -iPad, iPhone, Smart Phone and Androids usage for business -Internet, website, YouTube, Google for business -Cloud –based platform for business Mobile applications usage for business Preferences for Digital Platforms & ICTs Usage for Learning -Social Media for learning Preferences for Digital Platforms & ICTs Usage for Business -Social Media for business -Women Entrepreneurs’ preferences for ICTs (tablets, iPad, iPhone) in accessing Digital Platforms

ENTREPRENEURIAL PROCESS & ENTREPRENEURIAL PROFILE Reasons of setting up an enterprise & becoming a woman entrepreneur Modalities of starting up an enterprise Women entrepreneurial process defined & Creativity Women Entrepreneurs capabilities & characteristics Entrepreneurial Identity Types of entrepreneurial activities Gender is not an issue in the business world Gender is an issue for a woman entrepreneur -Gender is a 2016 issue in certain business sectors (construction, telecommunications) -Gender can be overcome by participating in networks Motherhood & Child Rearing/ Flexibility/Work/life balance Personal & Social Barriers/ Glass Ceiling/Policies

303

CHAPTER SEVEN: DATA INTERPRETATIONS AND DISCUSSIONS Figure 7.1: The Structure of Chapter 7 DATA INTERPRETATIONS AND DISCUSSIONS

CHAPTER 7: DISCUSSIONS AND INTERPRETATIONS

INTRODUCTION ANALYSIS OF THE RELATIONSHIP /CORRELATIONS between VARIABLES

FACTORS IMPACTING ON WOMEN ENTREPRENEURS’ SUCCESS

THEORETICAL CONTRIBUTIONS OF THE THESIS

LEARNING AND ACQUIRING KNOWLEDGE

MODELS OF LEARNING

DATA STORAGE & MANAGEMENT

VALIDITY AND RELIABILITY

304

CHAPTER 7: DISCUSSIONS & INTERPRETATIONS 7.1 Introduction to Chapter 7 This chapter synthesises the empirical findings from quantitative and qualitative data, and relates them to the literature review. Further, the chapter analyses the hypotheses originated from the literature review, explores the emergent consequences for the objectives and research questions and answers the research questions according to the main themes: learning, CoPs & networking and Digital Platforms & ICTs. The following sections of this chapter are entitled conform to the research questions, hypotheses and objectives developed in the literature review of the thesis. The evidence from the mixed methodology used in this thesis is compared with the previous research mentioned in the literature review. The structure of each factor employed within quantitative analysis is discussed and compared with the results from qualitative data analysis, according to the main themes of the thesis: Learning, Digital Platforms & ICTs and CoPs & networking. The chapter ends with the presentation of the main theoretical business model for women entrepreneurs’ success, the andragogical model of learning, and a few additional theoretical models emergent from quantitative and qualitative data analysis of this thesis. Finally, the author emphasises the contributions of the thesis to theory and practice and the new knowledge introduced by this study. 7.2 The Analyses of the Relationship and Correlation between Learning, CoPs & networking and WES This section of the chapter addresses the second objective of the thesis, hypotheses one and four, research questions two and four: Objective 2: The thesis ascertains if there is a significant relationship and a correlation between Learning, Digital Platforms & ICTs and WES. H1: ‘There is a significant relationship between Learning, Digital Platforms & ICTs and WES’. RQ2: Is there a significant relationship between Learning, Digital Platform & ICTs and WES? In order to determine (1) the existence or absence of a relationship between different groups of independent variables and the group of dependent variables, the author used a dependence method such as the standard multiple regression (Sharma, 1996). 305

Furthermore, this method has the capability to determine also, the impact of the independent variable upon the dependent variable (Sharma, 1996). In addition to this, the author used Factor Analysis, which was the interdependence method that attempted to find the smallest number of factors, in control of the correlation/relationship between large groups of variables (Sharma, 1996). In this thesis, Factor Analysis was used as a reduction technique for the complex and large amount of data, to decrease the number of variables to a small, manageable number of super-variables (Howitt and Cramer, 1999; Pallant, 2013). The main components of TFA EED which accounts for 25.3% of the variance (this percent value is considered significant) in the variable under analysis are: (1) The usage of networking (0.913); (2) Learn from information, participation, sharing (0.900). These results are supported by the outcomes of qualitative data analysis (FA, Labels, Table 5.55), and theme one, interviews, ‘Learning’, which is validated by a recurring percent of 35% and 41%, and Focus Group, and CA. According to Higgins and Elliott (2011) Learning is a combination between participants and their interaction within the process of learning. This statement is consistent with the outcome of TFA EED. These results are supported by research on informal learning, and entrepreneurial learning and gender (Mumford, 1995; Reece and Walker, 2007; Ettl and Welter, 2010; Boeren, 2011; Czerkawski, 2016). The outcome from TFA EED is also consistent with research on social and adult learning by Bandura and Walters (1963) and Maslow (1970). The main components of TFA NET, which accounts for 32.3% (significant percent value) of the variance in the variable are: (1) Mobile applications usage for business (0.667); (2) Twitter usage for business (0.636). The results are strengthened by the analysis from Table 5.55 (FA, Digital Platforms & ICTs (NET & ICTs) Labels). These results are supported by the outcomes of qualitative data analysis, theme two interviews ‘Digital Platforms and ICTs’ which is validated by a recurring percent of 62% and 43% and the Focus Group (Table, 4.101) and CA. The results are also supported by research on mobile technologies and their impact on small businesses (Pal, 2011; John and Gratton, 2013, Lilleker, 2013; Alshamaila, Papagiannidis and Li, 2013; Mell and Grace, 2011; Doherty, Carcary and Conway, 2015). (Table 6.19, Illustration 2, P10, Is; Table 6.4, Illustration 3, FGP5). The main components of TFA MSc, which accounts for 48.1% of the variance in the variable are: (1) Digital Platforms & ICTs affect business success (0.801); (2) Facebook 306

affects business success (0.775).

These results are supported by the outcomes of

qualitative data analysis (interviews and focus group), theme three interviews ‘women entrepreneurs’ success’ validated by a recurring percent of 38%, and the Focus Group. Jones, Borgman and Ulusoy (2015) confirmed that social media has a positive impact on business success. Research by Penrose (1980) and Drucker (2015) confirmed also the results of TFA MSc. Examples that support these statements are in the thesis (Table 6.22, Illustration 3, P33, Is; Table 6.5, Illustration 4, FGP4). According to the results of the analysis, there is a significant strong relationship between the independent variables and the dependent variable, which is women entrepreneurs’ success (TFA MSc). The independent variables (TFA EED & TFA NET) accounted for 26% of the variance in the dependent variable. The first hypothesis is supported by the results of Quantitative Analysis. In addition, the analysis discovered two sub-hypotheses: Sub-H1a: ‘There is a significant relationship between Learning and WES’. Sub-H1b: ‘There is a significant relationship between Digital Platforms & ICTs and WES’. Research by Schumacher (2011) viewed learning as ‘key to everything’, confirming thus, the predictive character of ‘learning’ in regard to WES, and consequently, supporting ‘Sub-H1a’. Further research by Roomi and Harrison (2008) confirmed a link between ‘learning’ and WES and the role that ‘learning’ has for WES (Mitchelmore and Rowley, 2013). Furthermore, gender and familial issues are essential elements embedded within entrepreneurial learning and impacting upon WES (Ettl and Welter, 2010). Further, research highlighted the role of additional components of ‘learning’, such as, Models of learning (Reece and Walker, 2007; Knowles, 1970; 1981; Kolb, 1984; Boeren, 2011; Czerkwaski, 2016) and women entrepreneurs’ learning needs (flexibility, location, time and context) (Fayolle, 2013) and the ‘self-concept’ (Maslow, 1993; 1970; Knowles, 1981) for WES. Similarly, research suggested a link between Digital Platforms & ICTs and WES (McCann and Barlow, 2015; Wang et al., 2010; Pocatilu, Boja and Ciurea, 2013). According to the discussions in the literature review section, there is no academic work investigating empirically, the relationship between Learning, Digital Platforms & ICTs, and WES. Factors affecting WES were studied ‘in isolation’ and not empirically in rapport with other factors (Reijonen and Kompulla, 2007).

There is a significant

relationship between Learning, Digital Platforms & ICTs, and WES. These results are 307

validated by the outcomes of qualitative data analysis (Focus Group and Interviews) of this thesis. Examples are provided in the thesis (Table 6.22, Illustration 3, P34, Is; P33, Is; Table 6.3, Illustration 2, FGP1). H4: ‘There is a correlation between Learning, Digital Platforms & ICTs and WES’. RQ4: Are there correlations between Learning, Digital Platforms & ICTs and WES? The correlation analysis, after factor extraction, indicated that hypothesis four is supported and there are correlations between Learning, Digital Platforms & ICTs and WES. As mentioned above, there is no academic research, which analysed empirically such correlation, but only isolated aspects of business growth or entrepreneurial success (Reijonen and Kompulla, 2007). The thesis emphasises the role of entrepreneurial learning. There are very few empirical studies on entrepreneurial learning (Marvel, Davis and Sproul, 2016, p. 611), and consequently, on the relationship between such aspects of Learning and Digital Platforms & ICTs and WES. Moreover, WES is approached by the author of the thesis, from women’s perspective (Costin, 2012), and the interpretations given by women entrepreneurs from SE Wales to WES, significantly impact upon the outcome of the analyses. There are different perspectives of women entrepreneurs on WES, including parental, relational, familial, existential, social, cultural, temporal, identity/gender, enjoyment, financial and even health perspectives (Dalborg, von Friedrichs and Wincent, 2012; Costin, 2012; Brush et al., 2004). There are academic studies acknowledging the influences of formal education on business growth (Hexham and Capillaries, 2010), and studies indicating the role of IT for education and business development (Brush, 2000). Recently, a study by Hashi and Krasniki (2011) highlighted the impact of technology and networking upon business growth. Nevertheless, there are not yet empirical studies of large samples, exploring the correlation between Learning, Digital Platforms & ICTs and WES. Consequently, this thesis is a contribution to the field of entrepreneurship and particularly, to women entrepreneurship. There is a significant relationship between Learning, Digital Platforms & ICTs and WES. Also, there is a correlation between Learning, Digital Platforms & ICTs and WES. However, there are contradictory results, in the sense that, the exploratory analysis confirmed a positive relationship, whilst the multiple standard regression analysis 308

indicates Pearson Correlation having significant negative values.

Thus, there is a

significant strong negative correlation between TFA NET and TFA MSc, with r=-0.505 (sig. = 0.000, for p<0.01) and significant weak/moderate negative correlation between TFA EED and TFA MSc, with r=-0.197 (sig. = 0.008 for p<0.05). In order to have sufficient reliable evidence and to be able to understand, and to have a correct interpretation of the results, the author used further analyses, such as descriptive statistics and the inferential statistics. From descriptive statistics, the author found that 79.7% of 149 valid cases answered that Learning is enhancing business success, due to knowledge and information.

Further, 90% of 150 valid cases answered that new emerging

technologies increased business success (Section E: Learning * Women Entrepreneurs’ Success). Additionally, from the inferential statistics, the analysis of Cronbach Alpha = 0.852 demonstrated good degree of internal consistency between the items of the fourth scale (Section E: The impact of various factors on women entrepreneurs’ success/business success) and high mean rating for Digital Platforms & ICTs and Learning (4.30; 4.25; 4.08; 3.59; 3.36). Consequently, these results strengthen and validate the results from FA and multiple standard regression analysis, and confirm the existence of a significant relationship and a correlation between the above variables. The author analysed all the aspects of such relationship, and concluded that, the negative outcome could be the result of the following: (1) the differential effect of various elements within the super variable under analysis; (2) women entrepreneurs’ perceptions and interpretations of entrepreneurial success, which, do not match and do not equal to ‘Learning’ or to ‘Digital Platforms & ICTs’ only, but is a far more complex phenomenon; (3) a controlling variable (CoPs & networking) that control the relationships between ‘Learning * WES’ and ‘Digital Platforms & ICTs * WES’; (4) Only certain independent sub-variables determine WES; (5) SPSS limitation in its TFA mechanics (single fixed factor extraction to be used for regression/correlation analyses); (6) SPSS lack of complex statistics on TFA/FA and modelling.

Descriptive statistics define ‘WES’ as

“independence and financial stability” (12.6% of 142 valid cases); “customer satisfaction” (12.7% of 142 valid cases); “work satisfaction and life balance” (4.2% of 142 valid cases), suggesting thus, the embedment of gender issues within it. The author used triangulation for data collection (Survey, FG, Is) and analysis (Exploratory, Correlation, SMRA, IPA, ThA, TA, CA) to avoid errors, to have a better interpretation and to validate the outcomes (Flick, 2015; Arksey and Knight, 1999). The author provides examples, in the thesis, with participants’ opinions on the above matters, which 309

led to the mentioned conclusion, that it is a relationship controlled by ‘networking and CoPs’ (Table 6.6, Illustration 4, FGP4; Illustration 5, FGP4, FGP5, FGP2). 7.3 Factors Impacting on Women Entrepreneurs’ Success Objective 1: To investigate the impact of Learning and Digital Platforms & ICTs on WES. RQ1: What is the impact of Learning and Digital Platforms & ICTs on WES? RQ6: What is the role of CoPs & networking? H2: ‘Learning has a positive impact on WES’. H3: ‘Digital Platforms & ICTs have a positive impact on WES’. First, ‘Learning’ has an impact upon WES and enhances business success. The results from the inferential statistics support partially the hypotheses and answer the research question.

Nevertheless, the results from the exploratory analyses indicate a positive

impact of some items belonging to the super variable ‘Learning’, upon WES. Despite obvious contradictions, the answers from the participants in the survey (open questions) confirm that education and Learning affects WES. It seems that, a huge impact, upon the results, had the way women entrepreneurs perceive ‘entrepreneurial success’. Examples with participants’ answers, regarding the impact of ‘Learning’ on WES are provided in the thesis. These responses support and validate the outcomes from the exploratory analyses (Appendix C, Survey, R4, R20, and R41; Table 6.22, Illustration 3, P34, Is). Regarding ‘Learning’ and its effect on WES, there are a few studies with various interpretations. Thus, some studies discussed the role of education as an essential resource (Schumacher, 2011), other studies argued about the role of entrepreneurial competences for business growth (Mitchelmore and Rowley, 2013) and finally, some authors (Histrich and Oztürk, 1999) emphasised the effect of education on performance and success. Barkham et al. (1996) highlighted that, the educational background and work experience, affect business growth. These results are in line with research by Penrose (1959).

Although, there are studies approaching the relationship between

learning and business growth, however, there are no studies using MMR. Thus, further important findings from the analysis of this research, discovered that, H2 is half supported by TFA and fully supported by exploratory analysis. Although, there is an impact of ‘Learning’ upon WES, the ‘r’ value is negative, indicating that this effect is 310

controlled by another variable. More analysis conducted by the researcher showed that a control/moderating variable ‘Networking & CoPs’ is impacting upon this relationship. Consequently, further empirical analysis, demonstrated a significant positive relationship between ‘CoPs & networking’ and WES (TFA CoPs * TFA MSc). This is confirmed also by the research, which indicates that WE derive benefits from social relationships, membership to associations, and CoPs & networking (Felício, Couto and Caiado, 2014). Moreover, significant positive relationships between TFA EED and TFA CoPs, and between TFA NET and TFA CoPs indicated clearly that, ‘CoPs & networking’ is a controlled variable for the relationships between TFA EED * TFA MSc and TFA NET * TFA MSc. These assumptions are validated by the results of the qualitative analysis and by previous academic research (Madsen, Neergaard and Ulhøi, 2003; Lafuente and Rabetino, 2011). It infers that, there is a relationship between ‘Learning’ and WES, controlled by network & CoPs. The significance of networking is also emphasised by Henari (2012), who argued that social networking (Granovetter, 1973) is the means for entrepreneurial success (WES) and business growth (Carter and Cannon, 1992; Dowson et al., 2011). This assumption is also supported by Roomi (2009) and Tan, Zhang and Wang (2015). Also, Bridget et al. (2009) created a type of equation trying to demonstrate that networking is a component of the ‘success equation’. This assumption is supported by other authors (Sotiropoulos, 2014; Pérez-Aróstegui and Martìnez-López, 2014), and validated by the results from the qualitative data analysis (Table 6.3, Illustration 2, FGP1). Many authors (Richardson, 1969; Fillis, 2007; St-Pierre and Audet, 2011), underlined the following factors: learning, IT, networking and knowledge, as contributors to the entrepreneurial success. There is an increasing role of the innovative technologies to SMEs growth (Moore, 2004) and lately, an emphasis was placed on the role of global communication technologies, web-based and networking technologies (Facebook, Twitter) for global growth and development (Meyer and Xia, 2012). These assertions confirm the impact of Digital Platforms & ICTs upon WES. However, the Pearson coefficient indicated the existence of a negative correlation between Digital Platforms & ICTs and WES. Consequently, hypothesis three is also half supported by TFA. Digital Platforms &ICTs predict WES and this fact was demonstrated by the positive 90% of 150 valid cases which answered: ‘Digital Platforms enhances business success’. However, the negative ‘r’ value implies a controlling variable, which is ‘CoPs & networking’. These findings support the following triangulated theories (perspective which is 311

considered by the author of this thesis as contribution to knowledge): Social Capital theory (women entrepreneurs benefit from belonging to CoPs and participating in networks) (Felício, Cuoto and Caiado, 2014; Roomi, 2009; Tan, Zhang and Wang, 2015; Sappleton, 2009; Granovetter, 1973; Coleman, 1988a; Putnam, 1995; Ottósson and Kyver, 2010); Social Learning theory (learning is an interactive process) (Higgins and Elliott, 2011; Bandura, 1977; O’Leary, 2017; Martin, Lord and Warren-Slith, 2018); Adult and Lifelong Learning theory (Malcolm Knowles – Andragogy) (Jarvis, 2004; Jordan, Carlile and Stack, 2008). Consequently, the following two hypotheses are fully supported: H2a: ‘The impact of Learning on WES is controlled by CoPs & networking’. H3a: ‘The impact of Digital Platforms & ICTs on WES is controlled by CoPs & networking’. The interpretation of these results resides also in the IT complementarity, as impacting together with other factors upon WES, not alone (Sotiropoulos, 2014; Pérez-Aróstegui and Martìnez-López, 2014). For a better understanding of the term ‘complementarity’, the author provides below the complete definition: “...complementarity represents an increase in the value of a resource, since it occurs when this resource produces greater benefits in the presence of another resource than when that resource is used alone.” (Pérez-Aróstegui and Martìnez-López, 2014, p. 119) 7.4 Theoretical Contribution of the Thesis: A Theoretical Business Model for Women Entrepreneurs’ Success Objective 3: To develop a Theoretical Business Model that can be used by women entrepreneurs to adopt Learning, Digital Platforms & ICTs, CoPs & networking, within their businesses in order to assure success. This thesis develops the concept of Women entrepreneurs’ success by exploring the impact of Learning and Digital Platforms & ICTs upon WES. The thesis also, attempts a new approach to methodology by combining two philosophical paradigms, and brings a contribution to the theoretical foundation of MMR, by blending the quantitative (survey) and qualitative (focus group and interviews) methods in an innovative manner.

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The initial conceptual research framework (Figure 3.4) was created by the author of this thesis from

extensive

collection of significant

literature from various

disciplines/subjects, such as: economics, business, entrepreneurship, management, psychology, sociology and education. Following the conceptual framework, and based on the blending process of the findings from quantitative data analysis (survey), and qualitative data analysis (Focus Group and Interviews), plus the preliminary discussions which accompanied these findings, the author of the thesis found sufficient evidence to conceive a theoretical business model for WES, that includes the results of this research (Figure 6.9). The use of mixed methodology, which allowed MMR, led to both hypotheses testing and theory generation. Hence, the author attempted to create a connection between the analysis of findings from quantitative and qualitative data analysis, and the original conceptual research framework, in order to generalise a theory by this theoretical business model. Consequently, the model can be considered as a reference for future testing hypotheses. The theoretical model is embedded within both deductive and inductive research approaches. The deductive research approach permitted the author of this thesis to collect literature on Learning, Digital Platforms & ICTs, CoPs & networking, and to blend them with the entrepreneurship theory, learning theory, and social capital theory in view to create this model. The inductive research approach enabled the author to collect the data and analyse the findings, discover patterns and emergent themes, which led to the final theoretical business model. The rationale of such theoretical business model is to enhance womenâ&#x20AC;&#x2122;s capability to learn, acquire information and knowledge, within the context of Digital Platforms & ICTs, by means of CoPs & networking. In other words, the consequence of using such theoretical business model is the effective integration of Learning, Digital Platforms& ICTs, and CoPs & networking, into small businesses owned by women entrepreneurs. The theoretical business model offers a viable solution to WES by incorporating into their businesses the following components: Learning, Digital Platforms & ICTs, and CoPs & networking. Finally, the model enables testing the hypotheses regarding the relationships between Learning, Digital Platforms & ICTs, WES and CoPs & networking.

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7.5 Models of Learning Objective 4: To find out a model of andragogical learning, methods of learning with digital platforms & ICTs, and learning preferences, learning needs, styles of learning women entrepreneurs employ to acquire knowledge in order to achieve success. RQ3: What are the models, methods and styles of learning, women entrepreneurs employ, and what are their learning needs and preferences in the context of Digital Platforms & ICTs? A model of learning depicts the way individuals learn and develop their learning. This thesis expands the concept of Learning by exploring and finding solutions for women entrepreneurial learning and creating an Andragogical learning model adapted and embedded within women’s needs and contexts. In this thesis, women entrepreneurs are regarded as a specific category of adult learners, framed by certain contexts and acting according to given circumstances. The way women entrepreneurs learn (Marvel, Davis and Sproul, 2016), embeds some of the elements of the models of learning created by Dewey, Lewin and Kolb (Kolb, 1984; Dewey, 1910) and consistent with research by O’Leary (2017). As they are social learners (Pedler and Burgoyne, 2017), their way of learning seems to incorporate elements of Bandura and Walters’s (1963) ‘social learning model’ and not only that, but elements of Maslow’s hierarchy of needs are required, when women entrepreneurs select the way they need to learn (Lovell, 1980; Dewey, 1910; Davis, 2012). This is confirmed in research by Wenger (2000), Martin (2001) and Martin, Lord and Warren-Smith (2018). It is also translucent that women entrepreneurs have the capability to answer simple questions as ‘what’ and ‘why’ in the learning process, without requiring high benefits, which apparently leads them to a direct way of the perceived ‘success’ (Dewey, 1933; Larwood and Wood, 1977). The findings of this thesis indicated that these statements are valid and supported by the empirical research on women entrepreneurs.

Entrepreneurial Learning (Marvel, Davis and Sproul, 2016), is a

continuous growing process (Kolb, 1984; Dewey, 1933; Bandura and Walters, 1969; Kotter, 1988).

Furthermore, women entrepreneurs learn also, by observation and

imitation, as they need role models to inspire them (Miller and Dollard, 1941; Bandura, 1986; Austin and Nauta, 2016; Kyrgidou and Petridou, 2013). Moreover, McGrath et al. (1995) underlined the role of country and the cultural context, when shaping women entrepreneurial learning (Ettl and Welter, 2010). Similarly, Lave 314

(1988) argued about ‘situated learning’ and stated that learning depends on the context and culture (SE Wales). Tynan et al. (2009) emphasised the importance of networking effect (Davis, 2012; Czerkawski, 2016), and the demand to differentiate (Martin, 2001; Davis, 2012), when considering women’s training. The power of networking on learning (Martin, 2001; Sharafizad, 2018; Martin, Lord and Warren-Smith, 2018), and its effect was depicted in early research by Bloom (1964, p.187) as “external stimuli which impinge upon individual” together with their role in sharing ‘knowledge’ or ‘information’ and creating knowledge (Dewey, 1921; Nonaka and Reinmoeller, 2000; Nonaka and Takeuchi, 1985). According to Keeley-Browne (2007), interaction and cooperation are fundamental principles of learning (Davis, 2012; Czerkawski, 2016; O’Leary, 2017; Martin, Lord and Warren-Smith, 2018). In his book on adult learning, Minton (2005, p.10) emphasised that learning is experiential (Sarri, 2011; O’Leary, 2017) and “learning and growing are cyclical” (Deakins and Freel, 1998). Recently, Jarvis (2004) introduced the concept of adult learning (Czerkawski, 2016) and the imperative of continuous learning. Tomos et al. (2016) give more information on adult learning, and andragogy, which is the art of teaching adults, in a complex study on models of adult learning for women entrepreneurs. Despite the fact that Maslow (1998), in his later writing on management, emphasised the need of ‘self-actualization’ for men entrepreneurs/managers [sic], according to the findings of this thesis, it seems that women entrepreneurs are also aiming for ‘self-actualization’ and the ‘self-concept’ with a different meaning, is very much an element component of WES. As a result, of the blending process of the above arguments and issues with the findings from quantitative and qualitative data analysis, the author designed a complex Andragogical Model of Learning, for women entrepreneurs. The model considers six different types of context/environments, (including the entrepreneurial context), that are assumed to impact upon women entrepreneurs’ learning, leading to particular learning styles and methods. Also, from the Figure 6.8 it can be observed that at the centre of the learning model is the CoPs & networking environment, which is essential for all the other environments or contexts. According to the findings, and the literature review, the learning model has the following components: (1) the university environment characterised by formal class-based learning and auditive and visual learning styles; (2) Digital Platforms & ICTs environment which is flexible and online, based on social media accessed through iPad, iPhone, laptops, tablets; (3) entrepreneurial environment, which 315

is experience-based learning, flexible, online or face-to-face and networking; (4) personal environment rooted into self-taught and informal methods with flexible styles of learning; (5) familial environment, originated from role model-based and non-formal methods of learning featured by flexibility; (6) CoPs & networking environment, characterised by acquiring knowledge and information through participation and sharing, with face-to-face or online learning styles. The Andragogical Learning Model endeavours to embed women entrepreneurs within various contexts, and attempts to acknowledge their particular styles and methods of learning which can lead to WES. It is clear that women entrepreneurs employ a participative learning embedded in networks & CoPs (Lave and Wenger, 1991; Wenger, 2000; Tomos et al., 2016; Martin, Lord and Warren-Smith, 2018; O’Leary, 2017). Based on the analysis of findings, the author concludes that women entrepreneurs use a combination of learning methods and styles, and the most used are the experience-based and role model based learning, with flexible informal styles, and learning through networking. The findings are consistent with previous research (Kolb, 1984; Wenger, 2000; McClelland et al., 2005; WBC, 2018; FSB, 2017; O’Leary, 2017; Martin, Lord and Warren-Smith, 2018). Examples, from the survey (open questions), Focus Groups and Interviews, with the participants’ answers regarding methods, styles of learning and their preferences for learning in the context of Digital Platforms & ICTs and CoPs & networking are provided in the thesis (Table 6.2, Illustration 1, FGP1, FGP4; Table 6.4, Illustration 1, FGP2; Table 6.16, Illustration 1, P1, P15, P26, P13, Is). In conclusion, women use Digital Platforms & ICTs for learning, and prefer a flexible style, visual, auditive, observational and experiential or ‘trial and error’.

Digital

platforms & ICTs mediate networking and virtual learning for women entrepreneurs (Indrupati and Henari, 2012; Gertner, 2013). Some women entrepreneurs prefer to use Facebook for business and others consider that Twitter is easier than Facebook (P13; P17, Table 6.19, Illustration 2, Interviews). Also, they do promotion via social media, by using various ICTs devices, such as: iPhone, iPad and laptop (P7; P34, Table 6.19, Illustration 2, Interviews). Some women entrepreneurs prefer to learn with Google (P17, Table 6.19, Illustration 2, Interviews) and others with iPad and digital platforms (P7; P34, Table 6.19, Illustration 2, Interviews). Finally, the descriptive statistics show that 15.5% of women indicated digital platforms as learning needs and 16.9% of women entrepreneurs needed marketing, promotion and sales knowledge. This is confirmed by recent research 316

conducted by FSB (2017). Furthermore, the results indicated the essential role of CoPs & networking, and 50.7% of 150 women entrepreneurs were networking learners. About 67.1% of 150 women entrepreneurs belong to CoPs & networking groups. This fact leads to the demand for networking knowledge and information, and the correct provision and delivery of teaching and learning through networking. Moreover, 72% of 150 valid cases, acquired business knowledge after starting their businesses. This leads to the further conclusion that, women entrepreneurs need to have assistance and learning support along the business process and according to business cycles/phases. The majority of businesses were micro businesses with no employees or â&#x20AC;&#x2DC;0-9â&#x20AC;&#x2122; employees (95.3%). These findings are supported by recent statistics (House of Commons, 2018). The big majority of the firms 67.3% were firms with less than 10 years; 35.3% were firms with less than three years, and 19.3% were firms with 20 years or more. This fact implies that the Government and HEIs have to meet their learning needs according with their stage in business life or cycles and their maturity, and they need to assess periodically their learning needs. About 65.4% were women entrepreneurs with age between 41 to 61 years old. Consequently, professionals with skills must update their digital knowledge and needs, as well as their business knowledge. As the majority of women entrepreneurs have families to support and little time to travel or learn, they do need to be approached in a correct manner, according to their availability and affordability. Finally, the author of the thesis surveyed the answers from the open questions of the survey with questionnaires, the responses from the participants in the focus group and interviews, the descriptive statistics and the answers from modelling, and attempted to answer the last part of the research question (RQ3). Thus, in order to acquire knowledge and information that leads to WES and business growth, the learning needs required by women entrepreneurs, and indicated by the quantitative and qualitative data analysis are: ICTs (R130; R79), marketing, finance and bookkeeping (R140; R104; R80; R40), Digital Platforms (Facebook, Instagram and Twitter) (R110; R85), legislation (R122), management (R80), promotion (R79); selling and buying (R41), taxes (R6), event management (R41), cooking and baking (R55), arts and skills specific to the sector of activity and business (R92) (Survey, Open Questions, Appendix C).

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7.6 Learning and Acquiring Knowledge Objective 5: To explore the role of CoPs & networking for women entrepreneurs’ learning, and acquiring knowledge and information, required in view to achieve success, in the context of Digital Platforms & ICTs. Women entrepreneurs’ perceptions and definitions of the following terms and concepts: entrepreneurial success; business growth; entrepreneurial process/activity; women entrepreneurs. RQ5: How do women entrepreneurs learn and acquire knowledge and information in the context of CoPs & networking and Digital Platforms & ICTs in order to achieve entrepreneurial success? RQ6: What is the role of CoPs & networking? First, it is important to highlight that, in order to enhance the understanding and the interpretation of the results, the author of this thesis conducted additional analyses, such as inferential statistics on the analysis of the relationships between various types of data and variables. For instance, the author conducted analyses on two scale variables and two categorical variables, as follows: (1) ‘Learning preferences’ (section B: Entrepreneurship Education, Q14) and ‘Participation in networks & CoPs’ (section D: Participation in networks & CoPs, Q4). The results indicated a significant positive moderate relationship between ‘flexible formal learning’, ‘flexible informal learning’, ‘experience-based learning’, ‘role-based model learning’ and ‘CoPs & networking’. The second relationship under analysis was between (2) CoPs & networking * Learning (section B, Q12; section D, Q3). The results indicated a significant positive relationship between two categorical variables, with Spearman Correlation, rho=0.215, sig. = 0.008, p<0.01. The third relationship analysed was between Learning * CoPs & networking (section B, Q14; section D, Q4) which indicated a significant moderate relationship between two scale variables, with Pearson value, R=0.220-0.324, sig. = 0.000, p<0.05. These outcomes demonstrate and support the significant role of CoPs & networking for women entrepreneurs’ learning. Further, the author strengthened and validated these results with the results from qualitative data analysis (Focus Group and Interviews). Examples with participants’ answers, regarding the role of ‘CoPs & networking’ in learning and acquiring knowledge, are provided in the thesis (Table 6.3. Illustration 2, FGP1; Table 6.7, Illustration 6, FGP5; Table 6.5, Illustration 4, P17, Is).

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In addition to the above information, in the Appendix B, the author provides a list with the networks, associations and groups, to which women entrepreneurs belong. Women learn by interaction, informally, participative, through flexible heterogeneous face-toface and virtual CoPs & networks, which support and mediate women entrepreneursâ&#x20AC;&#x2122; learning. Digital platforms such as Facebook, LinkedIn and Twitter, and ICTs support CoPs & networks and mediate learning. This findings are in line with other research (Wenger, 2000; Senge, 2014; Martin, Lord and Warren-Smith, 2018; Etkowitz et al., 2010; Indrupati and Henari, 2012; Sharafizad, 2018; Rui, Cuervo-Cazurra and Un, 2016). The second part of the fifth objective of the thesis, which is the last objective of this thesis, places emphasis on women entrepreneursâ&#x20AC;&#x2122; perceptions and definitions of the following terms and concepts: entrepreneurial success; business growth; entrepreneurial process/activity; women entrepreneurs. In order to achieve this last objective, the author gathered information collected by means of survey, Focus Group and interviews, and provided valid and well-formulated definitions, featured by both uniqueness and relevance. There are various definitions and perspectives upon these terms, as well as there is a lack of common agreed definitions. However, what this thesis brings is the novelty of the unique perception, as well as a multi focal perspective of women entrepreneurs in South-East Wales, UK, upon these terms. Furthermore, by gathering together data and information, by means of MMR and triangulation of data collection and analysis, the author was able to display various opinions and to design a well-formulated, complex, comprehensive, relevant and valid definition of women entrepreneurs. (1) Entrepreneurial process (womenâ&#x20AC;&#x2122;s entrepreneurship) defined: The author of the thesis used triangulation for data collection (survey, open questions; focus group; interviews) and data analysis (IPA, TA, ThA and CA). This approach enhanced the interpretation, and increased the understanding of the meaning of the concepts. Examples, belonging to each method involved within the data collection and analysis, are provided in the thesis (R19, R 38, R113, R82, R118, R122, Survey, Open Questions, Appendix C; Table 6.8 Illustration 7, FGP2; Table 6.28, Illustration 5, P3, P11, P15). A comprehensive definition designed by the author and rooted in the responses given by the participants in the survey, focus group and interviews, is highlighted below.

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Women’s entrepreneurship is defined as a challenge, a dream and a passion, which involves commitment, hard work and multitasking, as well as struggling between family responsibilities (motherhood, childrearing and childcare, household) and business. This process is described as innovative, creative and financially rewarding, offering women autonomy, flexibility, work/life balance, and financial independence, the opportunity to share with others, to help the family and community, and provide quality products and service to customers. Besides these, the entrepreneurial process gives women the opportunity to overcome gender barriers by networking, to compete in the market, and to develop capabilities such as management, leadership, networking, learning, creating, communicating and prospecting. From the qualitative data anaylsis, the author yielded a Model of Entrepreneurial Activity and Process (Figure 6.6). The definition of entrepreneurial process is multidimensional, and comprises the following components: (1) personal and family; (2) community & social identity; (3) social networking with customers, suppliers, other women entrepreneurs, government, CoPs, family and friends; (4) learning and training; (5) creativity and innovation; (6) social & gender; (7) business capabilities; (8) risk; (9) planning and forecasting; (10) routine based activities, common to other businesses (cashing, ordering stock, selling, secretarial, administrative); (11) activities and capabilities specific to sector and type of activity. (2) Entrepreneurial success (women entrepreneurs’ success) defined: After analysing various responses given by the participants in the survey, Focus Group and interviews, the author decided to group the definitions to WES in nine categories and according to nine perspectives: (a) gender perspective; (b) sector and type of activity perspective; (c) satisfaction, self-esteem and confidence perspective; (d) financial perspective; (e) customer relationship perspective; (f) education & ICTs perspectives; (g) networking; (h) survival perspective; (i) various factors perspective. Following the examples, provided in the thesis, the author produced the definition for the concept ‘WES’ (Table 6.8, Illustration 7, FGP4; Table 6.6, Illustration 5, FGP4, FGP5; Table 6.22, Illustration 3, P5, P13, P17, P32, P23, P33, Is; R4, R47, Survey, Open Questions, Appendix C). Women entrepreneurs’ success depends on the type of business and sector of activity and implies satisfaction, enjoyment (Maslow, 1943; Schumpeter, 1934), passion, financial 320

independence and overcoming gender barriers, flexibility, motherhood, parental care, childrearing, and having free time, supporting own family, popularity of the business, reputation for quality of the products and services, survival, good relationship with customers, networking with other women entrepreneurs, sharing and learning, having access to NET & ICTs, being confident and achieving business growth and finally, having money and profit. Maslow (1943), Schumpeter (1934) and Dalborg, von Friederichs and Wincent, (2012), support these results and interpretations. The following are the groups of factors affecting women entrepreneurs’ success: emotional, personal, social (networking), gender, commercial, economic and politic, fashion, relational and reputation (Model 2, Figure 6.3). The following are the reasons of enjoyment for women entrepreneurs: independence, flexibility, juggling (behavioural); communicating and seeing people (social); self-esteem and satisfaction (personal); parental care and having free time (parental and family); creativity, innovation and uniqueness (innovation); working for yourself, control and ownership (power and control); challenge, dream and hobby (vision); financial independence (financial stability) (Model 1, Figure 6.2). Also, related to WES, are the benefits of CoPs & networking, as follows: learning from the success of others, gaining social skills (social); learning, training and having knowledge and information (cognitive); immediate contact and feedback (personal); participation in events, fairs and exhibitions (experiential); sharing and collaborating (emotional); business expansion and growth (economic and financial) (Model 3, Figure 6.4). Further factors affecting WES, emerging from the analysis, were classified by the author of the thesis, and entitled ‘women entrepreneurs’ capabilities and characteristics’ (Model 4, Figure 6.5). These were grouped into four categories: power and ownership, emotional and artistical, active and energetic, and the last category, ‘social and personal’. (3) Business growth (for women entrepreneurs) defined: Business growth was considered by some authors to be equal to ‘entrepreneurial success’. Nevertheless, further research indicated that business growth was part of the entrepreneurial success and was regarded as a component of this. Women entrepreneurs have various opinions regarding the meaning of the term. According to their perceptions, the author grouped them initially into eight categories: development and expanding perspective, financial perspective, customer perspective, increase in sales perspective, phenomenological perspective, educational perspective, success perspective and gender 321

perspective. Consequently, in the thesis, the author gives examples with definitions on ‘business growth’ provided by the women entrepreneur participants in the survey, Focus Group and interviews (Table 6.6, Illustration 5, FGP1, FGP5; Table 6.22, Illustration 3, P35, P36, P37, Is; Table 6.5, Illustration 4, FGP5; Table 6.6, Illustration 5, FGP2; Table 6.8, Illustration 7, FGP4). Following the examples, the author yielded a thorough definition on ‘business growth’. In conclusion, business growth could be regarded as a financial and non-financial phenomenon. From the (A) financial perspective, business growth, indicate an increase in sales, expressed as a percentage, and showing a higher percent in the current year compared to the percent from the previous year. In addition, business growth indicates an increase cash and increase in profit. From the (B) non-financial perspective, business growth implies expanding the business, in the sense of opening more shops or employing more people and serving more customers. Another non-financial perspective regards business growth as a growing entrepreneurial phenomenon of businesses owned by women. Finally, the last (C) non-financial perspective on business growth indicates personal achievement, enjoyment, satisfaction, better knowledge, information and education, better relationships with customers, suppliers and other women entrepreneurs, better networks and participation, a better access to online information, work/life balance, and the embedment of digital platforms & ICTs into their businesses. These results are supported by the results from research by Costin (2012) and Dalborg, von Friedrichs and Wincent (2012). (4) Women entrepreneurs defined. The last concept discussed in this section is ‘women entrepreneurs’. This definition is of a crucial benefit for academics, practicians, economists, analysts, ONS, statisticians, Labour Force Surveys, Labour Market, DWP, FSB, Government, HEIs, policy makers, Women’s Business Council, House of Commons, and women entrepreneurs.

The

triangulation, used in data collection and analysis, helped the validation, as well as the authenticity, and the originality of the final definition, which is a contribution to knowledge, and particularly, to the field of entrepreneurship. Examples of women entrepreneurs’ definition is provided in the thesis (R2, R7, R10, R28, R46, R50, R60, R119, R131, Survey, Open Questions, Appendix C; Table 6.6, Illustration 5, FGP2, FGP3, FGP5; Table 6.22, Illustration 3, P10, P14, P29, P31, Is).

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From the above examples (a selection only), one can see that ‘women entrepreneurs’, is a very complex and multifaceted concept in the field of entrepreneurship. Nevertheless, it requires to be defined and have a thorough definition, in order for this field to advance and be able to compare results from various research studies. It also transpires that the definition has a gender component embedded within it. After analysing a large range of definitions and based on the above relevant perceptions, the author of the thesis was able to yield a final definition for this important concept. Thus, the definition embeds a personal feminine characteristics perspective. According to this perspective, (1) women entrepreneurs are defined as strong, driven, brave, determined and risk taking people; they also have the capability to do what they love and have passion for. They are mothers, girlfriends and wives, capable to work flexible and around the family and children, successfully, as multitaskers. From this viewpoint, they are positive, motivated and happy. (2) A second perspective upon the definition of ‘women entrepreneurs’, implies the gender issue. Women entrepreneurs are different from their male counterparts. This affirmation is supported by Ahl (2006) who stressed upon the essentiality of seeing women and men as different, without under estimating or undermining ‘women’ as entrepreneurs. Despite of heavy criticism of women entrepreneurs (Ahl, 2006), in author’s opinion, women and men entrepreneurs need each other, in the sense that, they complement each other and can work in harmony particularly if they are part of a family business (partnership – husband and wife). Nevertheless, some women entrepreneurs, as mentioned above, need to adapt their personality and characters within a though business world, labelled as a ‘men’s world’. In summary, the final definition produced is the following: Women entrepreneurs are a distinct and unique category of people, talented, passionate, risk takers, motivated by the desire to support their families, to be a role model for their children, for others women entrepreneurs, and to bring a contribution to the family, community and society, despite the glass ceiling, cultural barriers (Coleman, 2010; Knorr, 2011; Clark Muntean, 2013) and stereotypes (Bradley, 1996; Ahl and Marlow, 2012), and gender discrimination in certain sectors (Markues, 2017). They aspire to gain financial independence and autonomy (Gertner, 2013), to think for them, and to gain knowledge (Drucker, 2015) and confidence. Women entrepreneurs are multitaskers, courageous, dynamic, with interpersonal and networking skills, who wish to have equal status with 323

men (Ahl and Nelson, 2010; Ahl and Marlow, 2012), and to be recognised by them in the field of entrepreneurship, but who also have different aspirations, perceptions and characteristics. Within this specific category, one has to acknowledge the heterogeneity of women within the category of women entrepreneurs, due to different perceptions, beliefs, ethnicity, nationality, culture, gender, social status, financial means, education, knowledge, access to Digital Platforms & ICTs, and religious belief. Finally, women entrepreneurs have an identity. They are mothers, wives, girlfriends, entrepreneurs, managers, artists, freelancers, professionals or just business people, with both intrinsic and extrinsic motivators. These findings support previous research in the field, regarding social identity and status, and motivations (Stanworth and Curran, 1986; Gouldner 1957; Gouldner, 1958; Kuratko et al., 1997). 7.7 Validity and Reliability of the Results The statistics in this thesis assisted the author as follows: (1) to test the hypotheses and confirm that the measures, used to test the hypotheses, are actually appropriate for what they measure; (2) the conclusions are accurate; (3) the outcomes from the analyses are consistent. The reliability, which is the indicator of the measure’s internal consistency, was evaluated in this case by using Cronbach’s alpha or coefficient alpha (Zikmund et al., 2010). The study designed four scales with a coefficient alpha varying between 0.600 to 0.900, indicating a fair to very good reliability (0.60 to 0.70 indicates fair reliability; 0.70 to 0.80 indicates good reliability and 0.80 to 0.95 indicates very good reliability) (Zikmund et al., 2010). The MMR enhanced the confidence in data analysis and the validity of the results. Validity is the indicator, which measures the accuracy (Zikmund et al., 2010). The author ensured that the measures are accurate and have convergent validity, which was indicated by the high level of reliability, demonstrating the relationships between the variables/constructs, which are rooted in the literature review (Zikmund et al., 2010). Also, the external validity which ensures the generalization of the results from the sample to the women entrepreneur population in SE Wales/UK was assured by the random selection of the sample and the adequate ratio of cases per variable under observation. Further, the replication of the study assures generalisability, and furthers the research in the field of entrepreneurship. The exploratory factor analysis demonstrated that the items of the constructs were interrelated and followed a solid investigation. The author ensured that the constructs used in the analysis had ‘fair to very good reliability’. Nevertheless, as a result of the limitations of this research, the author 324

recommends generalization to Wales only, and further research with a larger sample, at the United Kingdom level, which will ensure an increase in generalizability of the findings. 7.8 Data Storage & Management The hard data, collected by means of survey with questionnaires, will be kept by the researcher for five years, according with the University of South Wales Regulations. The audio data collected for the Focus Group and 37 interviews will also be kept in audio folders, saved by the author of the thesis on external devices, conform to the USW Regulations.

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CHAPTER EIGHT: CONCLUSIONS & CONTRIBUTIONS Figure 8.1: The Structure of Chapter 8 CHAPTER 8: CONCLUSIONS AND CONTRIBUTIONS

LIMITATIONS & RECOMMENDATIONS

CONCLUSIONS

MAIN FINDINGS CONTRIBUTIONS THEORY & PRACTICE

Source: F. Tomos ÂŠ 2016

8.1 Conclusions This main aim of the thesis was to explore the impact of Learning and Digital Platforms & ICTs on WES in the context of CoPs & networking. Although, the thesis answered the research questions, addressed the main aim and objectives of the research, and tested and confirmed four hypotheses, other hypotheses emerged. These new statements are based on innovative triangulation of theories (focal, background and data theories) and MMR design. Also, following a mixed approach to philosophical paradigms (Kirkwood and Campbell-Hunt, 2007) new perspectives and models emerged from the quantitative and qualitative analysis and.

These led to a better interpretation of the results and an

enhanced meaning of the research. Although, the research is predominantly positivist, the author used a second paradigm, the phenomenological paradigm to improve the understanding and enhance the interpretations of the findings. Thus, the thesis started with a survey with 450 women entrepreneurs, which was paralleled by 37 interviews with women entrepreneurs and a focus group with five women entrepreneurs from South East Wales, UK. The thorough literature review indicated the main aspects and limitations of the current research: (a) single data collection method; (b) single type of measurement; (c) lack of theory triangulation; (d) lack of research on the relationship between factors affecting 326

business WES/growth; (e) lack of MMR complex, within the field of entrepreneurship, and mixed philosophical paradigms; (f) lack of research into the meaning of the following concepts: WES, women entrepreneurs, women’s entrepreneurship and entrepreneurial process; (g) lack of research into the role of CoPs & networking for WES.

As a

consequence of these gaps in knowledge, the author of this thesis found a novel research approach to this research topic. The objectives of this research were as follows. The third and main theoretical objective of this thesis was to develop a theoretical business model that can be used by women entrepreneurs to adopt Learning and Digital Platforms & ICTs, in the context of networking & CoPs, within their businesses in view to assure success. The research accomplished the main theoretical objective by testing four hypotheses and by creating a novel theoretical business model. WES is considered as a major concept, together with the assumptions that, women entrepreneurs use digital platforms & ICTs, and learn or acquire information and knowledge, within the context of CoPs & networking, and supported by CoPs. The second objective was to find out, whether there is a significant relationship and a correlation between the variables of the research (Learning, Digital Platforms & ICTs and WES). In line with the results of the analysis, besides the main hypothesis, H1, the author defined the following emergent sub-hypotheses: Hypothesis 1: There is a significant relationship between Learning, Digital Platforms & ICTs and WES. Sub-Hypothesis 1a: There is a significant relationship between Learning and WES. Sub-Hypothesis 1b: There is a significant relationship between Digital Platforms & ICTs and WES. The results of the analyses demonstrated a significant relationship between Learning and WES, as well as between Digital Platforms & ICTs and WES. Furthermore, there is a significant relationship between Learning, Digital Platforms & ICTs and WES. This confirms the relationship between the variables, and suggests the achievement of the second objective of the thesis. Hypothesis 2: ‘Learning has a positive impact on WES’; Hypothesis 3: ‘Digital Platforms & ICTs have a positive impact on WES’;

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With regard to the first objective of the thesis, the analyses demonstrated the existence of a two effects: a positive impact supported by the exploratory analysis, and a negative impact confirmed by the quantitative analysis. This objective was achieved by testing H2 and H3 and by further exploratory analysis, which confirmed the impact. Learning is supported by technologies and controlled by CoPs & networking. Digital Platforms and ICTs act as a complementary element and not alone on WES (Sotiropoulos, 2014; PérezAróstegui and Martínez-López, 2014). These results are consistent with research by Gertner (2013), Schumacher (2011), Maslow (1970; 1993), Fayolle (2013), Kolb (1984), Bandura and Walters (1963), Jones, Borgman and Ulusoy (2015), Alshamaila, Papagiannidis and Li (2013), and Pocatilu, Boja and Ciurea (2013). The quantitative analysis indicated also, additional emergent hypotheses, which confirmed the essential role of CoPs & networking and led to the accomplishment of objective five. Sub-Hypothesis 2a: The impact of Learning on WES is controlled by CoPs & networking Sub-Hypothesis 3a: The impact of Digital Platforms & ICTs on WES is controlled by CoPs & networking There is indeed a controlling effect of CoPs & networking upon the relationship between Learning and WES and a mediating effect of CoPs & networking upon the relationship between Digital Platforms & ICTs and WES. This indicates that all women entrepreneurs need to acknowledge the crucial role of CoPs & networking for learning, acquiring knowledge, and information, in providing encouragement, support and friendship, and as a means for social life. The exploratory quantitative analyses discovered additional eight emergent hypotheses and twelve emergent sub-hypotheses, demonstrating the essential role of CoPs & networking for Learning, WES, Digital Platforms & ICTs and their relationships. These results are supported by Hanson and Blake (2009), McCann and Barlow (2015), Bogren et al. (2013) and Sharafizad (2018). The results are consistent with research by Granovetter (1973), Audretsch and Keilbach (2004), Roomi (2009), Tan, Zhang and Wang (2015), and Felício, Couto and Caiado (2014). These results are also, in line with Bogren et al. (2013) who confirmed the relationship between personal and business networks and women willingness to grow the businesses. Secondly, the results indicate that Digital Platforms & ICTs alone cannot impact upon the entrepreneurial success due to IT complementarity (Sotiropoulos, 2014; Pérez-Aróstegui and MartínezLópez, 2014). Although, they are essential for communication and information, their effect is increased and made sufficient within CoPs & networking, no matter that these 328

are face-to-face, or virtual. Third, the results suggested also, that, women entrepreneurs need to be actively involved in networking both face-to-face and online. The effect of using Digital Platforms & ICTs and acquiring information and knowledge or learning, increases when women entrepreneurs join networks, and are active actors within CoPs & networks. Hypothesis 4: There is a correlation between Learning, Digital Platforms & ICTs and WES. Hypothesis 4a: There is a correlation between Learning and WES. Hypothesis 4b: There is a correlation between Digital Platforms & ICTs and WES. Further hypotheses deducted from the results of the analyses showed that, there is indeed a correlation between the variables of the research: Learning, Digital Platforms & ICTs and WES. However, what is essential is the positive effect of CoPs & networking upon WES, and upon each variable of the research, as well as upon the relationship of the variables. This confirms and validates the essential role of CoPs & networking for WES, both as a mediator and as an independent variable. The results lead to the development of further hypotheses: Hypothesis 5: ‘There is a significant positive relationship between ‘CoPs & networking and WES’. Hypothesis 6: ‘There is a significant positive relationship between Learning and CoPs & networking’. Hypothesis 7: ‘There is a significant positive relationship between Digital Platforms & ICTs and CoPs & networking’. The multiple impacts of CoPs & networking upon WES, Digital Platforms & ICTs, and Learning, and upon the relationship between these three variables, validate the essential role of CoPs & networking for women entrepreneurs. This is consistent with the research conducted by Tomos et al. (2016). The last objective is objective four, regarding the Andragogical Model of learning, which was achieved by developing a learning model rooted within quantitative and qualitative data analyses. The Andragogical Model of Learning is in line with research by Bandura and Walters (1963), Jarvis (2004), Kolb (1984), Maslow (1980), Reece and Walker (2007), Davis (2012), Sarri (2011), O’Leary (2017), Sharafizad (2018), Martin, Lord and Warren-Smith (2018) and Czerkwaski (2016). Below, the author provides a novel Theoretical Business Model (Figure 8.2): 329

Figure 8.2: Theoretical Business Model for WES AML WES

EED

NET & ICTs

EA & P

BDI CoPs & Networking AML – Andragogical Model of Learning; EA&P – Entrepreneurial Process & Profile; BDI – Background & Demographic Information.

8.2 Main Findings Learning - comprises models, methods and style of learning, women entrepreneurs’ learning needs and preferences, as well as competences and entrepreneurial knowledge. According to the exploratory quantitative analyses, Learning predicts WES. There is a significant moderate correlation between Learning * WES. Nevertheless, TFA indicated a weak relationship and impact of Learning upon WES. However, an in-depth analysis, based on the combined results, such as FA, TFA and CA of FG and Interviews, led to the conclusion that Learning is a significant predictor of WES. The analyses indicated that women entrepreneurs learn from information, participation and sharing, learn informal, by CoPs & networking. The main methods of learning are lifelong learning (errors, conferences, associations, and networks), adult learning (experience-based), social learning (role-based learning) and Digital Platforms & ICTs.

This research supports

studies by Edwards and Muir (2012) regarding adult learners and their own perspective on Learning and Fayolle’s (2013) research about the characteristics of learners and their learning needs. The results are in line with research by Bandura and Walter (1963), 330

Fontana (1995), Maslow (1980), Kolb (1984), Jarvis (2004), Wenger (2000), Senge (2014), Oâ&#x20AC;&#x2122;Leary (2017), Martin, Lord and Warren-Smith (2018) and Indrupati and Henari (2012). The main styles of learning are flexible, informal, participative, networking, visual and auditive. The main model of learning is the Andragogical Model of Learning. This is in line with research by Reece and Walker (2007), Knowles (1970), Mezirow (1981), Kolb (1984), Maslow (1980), Bogren et al. (2013), Sharafizad (2018), and Loibl and Leuders (2019). The thesis emphasised WE learning needs and their periodical assessment. This infers adequate entrepreneurship policies for opportunities and skills (Tsai et al., 2014). The second predictor is Digital Platforms & ICTs, which comprises global communication technologies, data-sharing technologies, web-based technologies, networking technologies and cloud-based platform. The quantitative and qualitative analyses demonstrated that Digital Platforms & ICTs is a strong predictor for WES. TFA indicated that mobile applications usage for business and Twitter usage for business are particularly essential for WES. FA, indicated as crucial components for business, the Digital Platforms (McCann and Barlow, 2015); whilst, internet, search engines, and YouTube were essential components for business and learning. There is a relationship between the usage of Digital Platforms & ICTs and the age of WE. Thus, Gen Y (18-37 y. o.) has a higher (41%) connectivity and participation in online communities than Gen X (38- 75 y. o.) (38%). There is also a relationship between women entrepreneursâ&#x20AC;&#x2122; interpretation of gender issues and their type of business partnership (Husband & Wife Partnership).

There is also a significant moderate

correlation between Digital Platforms & ICTs * WES. The thesis emphasised also the role of cloud computing and cloud platforms for the new businesses. This is consistent with research by Doherty, and Conway (2015). The third variable to be discussed is CoPs & networking, which is crucial, as controlling variable, for the impact of Learning/Digital Platforms & ICTs upon WES, and for the relationship between Learning, Digital Platforms & ICTs and WES. CoPs & networking comprises Membership to CoPs & networks, Type of Participation and Digital Platforms. The FA indicated that Digital Platforms & ICTs help CoPs & networking, whilst TFA indicated that mobile phones and laptops/computers help CoPs & networking. Qualitative Data Analysis informs the strong impact of social media, iPhone, iPad, tablets and cloud-based platforms on WES. There are significant strong correlations between 331

CoPs & networking * WES, CoPs & networking * Digital Platforms & ICTs. The results are consistent with research by Teece (2005), Dewey (1921), UlhĂ¸i (2005), Granovetter (1973), and Sullivan and Ford (2015). The predictors of the model TFAEED, TFANET and TFAMSC account for a large variance in the dependent variable TFAMSC (WES) (26%). In addition, TFACPN has a significant impact upon both IVs (independent variables) and DV (dependent variable). The majority of WE from FG indicated personal barriers (motherhood, childcare, childrearing, family responsibilities). About 60% of WE had children when they started the business, and about 59.4% of WE confirmed that the reasons of starting entrepreneurship were the following: motherhood, maternity leave, childcare, childrearing, providing for children, being role model for children. This infers the need of adequate social policies able to support and encourage women entrepreneurship. The results support research by Pines, Lerner and Schwartz (2010), Rafferty (2014), Nieuwenhuis and van Gerven (2015) and Clark Muntean (2013). Consequently, the research supports also studies by Rubery (2015) regarding the need of entrepreneurship and social policies periodical assessment.

This study is in line with research on

entrepreneurial identity and entrepreneurial learning (Edwards and Muir, 2012; Donnellon, Ollila and William Middleton, 2014). Furthermore, the thesis highlights the role identity of WE and supports research on gender role identity and the sense of belonging, by Zimmerman and West (1987) and Ely (1995). Additionally, the author of the thesis designed five models emergent from the findings of qualitative data analysis: WE capabilities and characteristics (Fig. 6.5), Model of Entrepreneurial Process and Profile (Fig. 6.6), Benefits of CoPs & networking (Fig. 6.4), Reasons of Enjoyment (Fig. 6.2) and Various Factors Affecting WES (Fig. 6.3). The thesis provided comprehensive definitions of the main terms of the research. 8.3 Contributions to Knowledge: Theory & Practice The thesis contributes a triangulated theory, by blending entrepreneurship theories (success/growth & technological innovation) with, theories of learning, and social capital theory, and data theories, within a theoretical research framework and a conceptual research framework that is tested. Although, there is academic research focused on Learning and even on Digital Platforms & ICTs and success, however, these topics are approached by the authors in a fragmented manner and not holistically. As a result, this 332

thesis brings a contribution to theory, by undertaking a holistic and relational perspective upon WES, which is still considered as being unexplored. The thesis contributes also to women entrepreneurship literature through the empirical tests applied to the relationship between the main variables: WES, Learning, Digital Platforms & ICTs and CoPs & networking. Anderson, Drakopoulou and Jack (2012) acknowledged the current situation of the entrepreneurship research as being fragmented, despite the complexity of the entrepreneurship phenomenon.

Consequently, by linking together Learning, Digital

Platforms & ICTs and WES, and presenting the relationship and the correlations between them, as well as the controlling role of CoPs & networking, the author of the thesis, introduces a new interdisciplinary and holistic perspective on women’s entrepreneurship phenomenon, and brings a contribution to the theory of entrepreneurship. Furthermore, the way these components are mixed, and their operationalisations, differs and leads to a different perspective upon this phenomenon. The research is the first of its kind in the UK, and the first in the world to apply the Theoretical Business Model for WES and an Andragogical Model of Learning for WES. The Welsh Government, in view to increase women entrepreneurs’ success, can use the proposed theoretical business model and the andragogical model. The thesis explores learning in entrepreneurship and therefore, this study is the first to investigate learning from women’s perspective and to design an Andragogical Model of learning for WES. According to Marvel, Davis and Sproul (2016, p. 611), “very few studies examine learning in entrepreneurship”. The training and skills development for women entrepreneurs will have positive implications for the development and growth of their enterprises, as well as for their personal development, professional career, selfconcept, and success. As a result of this thesis, policy makers should place emphasis upon ‘training and development’ for women entrepreneurs.

This thesis will also have

implications for HEIs, in assessing women entrepreneurs’ learning needs and providing training in a flexible manner, through CoPs & networking, Face-to-Face or by means of Digital Platforms & ICTs. In addition to this, the study incorporates a significant percent (69.3%) of women owned businesses located in High Street and commercial streets (Appendix B, Table 2), and offers a theoretical framework for survival and success for women owned SMEs, including businesses located in the High Street, SE Wales, affected by the present business climate, and the collapse of larger retailers.

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However, the main theoretical contribution of the thesis is the elaboration and the testing of the conceptual research framework that applies entrepreneurship theory, learning theory, and its perspectives and social capital theory to WES. Further, this conceptual research framework led to a new integrative framework that assisted the interpretation of the relationships between Learning, Digital Platforms & ICTs, CoPs & networking, and WES. Also, through the empirical analysis, the thesis contributes to business growth and success literature. Further, by using a mixed paradigm approach, the thesis brings another theoretical contribution, which is the enhancement of the debatable literature on the entrepreneurshipâ&#x20AC;&#x2122;s philosophical perspectives. The thesis also contributes to the theory of entrepreneurship and the development of the field of entrepreneurship, by creating a theoretical research framework, a theoretical research model, a research methodology and a research design. The thesis supports the assumption of a more adequate theoretical model of entrepreneurship, and accepts the necessity for different measures of success for women entrepreneurs (Allen and Truman, 1988; Tomos and Thurairaj, 2019; Tomos et al., 2019). In addition to these, the thesis contributes to the theoretical foundation of MMR, by using MMR and justifying the need of this research method (Bruyat and Julien, 2000; Tomos et al., 2015). In this regard, the study is one of the first in the world, complex pioneering work, contributing to the foundation of MMR as the third research methods, within the field of entrepreneurship. The thesis developed the theories of learning, entrepreneurship and social capital, by creating an Andragogical Model of Learning and A Theoretical Business Model for Women Entrepreneurs, and challenges data theory, in fact MMR theory, by the introduction of a mixed paradigm philosophy. Finally, another contribution to knowledge consists in the novelty of operationalisation of the concepts of WES, CoPs & networking, Learning and Digital Platforms & ICTs.

This opens the opportunity for field

development, by allowing analysis replication at a larger scale (national/international), and advancement by comparing results based on common operationalisation. The lack of sectoral and gender data constitutes a barrier to the quality of policies. As a direct consequence, FSB (2018) suggests a larger sample for survey with women businesses owners. Hence, this thesis contributes with enhanced and accurate data for better analysis, improved recommendations and advice for policy makers, in regard to learning needs and preferences, styles and methods of learning, used to update knowledge 334

and achieve success, by women entrepreneurs with business located in High Streets, commercial streets, participant to exhibition, fairs and networking events. The goal of this thesis is to provide a set of good practical recommendations able to help women entrepreneurs to achieve success. Thus, based on the discussions of practical implications of this research, the author of the thesis provides recommendations for women entrepreneurs, HEIs, Government, ONS, Labour Market, economists, analysts, Small Business Federation, networks and CoPs, Consultants, Welsh economy, Women’s Business Council, House of Common, the United Kingdom economy, and various practitioners. First, the research contributes to the development of small businesses with women entrepreneurs, by highlighting women entrepreneurs’ learning needs, styles, models and methods of learning, required to survive, and achieve entrepreneurial success. Women entrepreneurs are asked to understand their learning needs, the role and importance of networking, and the factors affecting entrepreneurial success.

Second, the study

identified women’s preferences for Digital Platforms, and which are the most used technologies for networking and acquiring knowledge and information, and gives advice to SBF and other governmental bodies to use and adopt the same technologies, and embed the same learning methods and styles of learning, in order to meet women entrepreneurs’ leaning needs.

Third, the research provides information regarding the role of the

contextual/environmental factors for women entrepreneurial learning.

Further, the

learning should be provided according with the business phase or business cycle of each entrepreneur or group of entrepreneurs (Carter and Cannon, 1986).

Fourth, great

importance should be given to their personal needs, to the CoPs & networking groups and their approach to learning and diffusion of information (Knorr, 2011). Fifth, the findings indicate the need of the periodic assessment of women entrepreneurs’ learning needs, motivation, their preferences for learning and their learning methods (Lovell, 1980; Dewey, 1933; Bandura, 1986; Brush, 2000; Moore, 2004; Marvel, Davis and Sproul, 2016). Women entrepreneurs need to be trained by practitioners who are fully aware of their learning needs and their approaches to learning and IT (Brush, 2000; Moore, 2004). The training can be conducted either face-to-face, online or by means of various groups, associations, networks and CoPs, to which women entrepreneurs belong to, in order to meet their individual needs or group needs. This study informs the Welsh Government and business consultants regarding the learning needs of women entrepreneurs, and the 335

best way they can be approached, their styles and methods of learning, and provides an Andragogical Model of Learning, for the usage by women entrepreneurs in general, as social and adult learners, and especially for women entrepreneurs with businesses located in High Street or Commercial Streets (Lovell, 1980). This is essential for diffusion of information, knowledge and learning and furthermore, for achieving success in business. 8.4 Limitations and Recommendations As a result of various factors impeding upon the complete success of a research, this research has also some limitations that needs to be highlighted and discussed. The author attempts to address some of these limitations in the lines below. First, the author created a survey questionnaire with blended elements from three tested questionnaires (Buckley, 2009; Grosch, 2011; Tomos et al., 2011). According to the literature review and the aim and objectives of this research, the author of this thesis, with the permission of the authors of the questionnaires, adapted and used the questions to suit the needs of this research. By doing such, the author assured continuity of her research and the opportunity to link previous research conducted by the author, with the results of this thesis, in view to validate its outcome. The author of the thesis used four attitude scales in sections B, C, D and E of the survey questionnaire. However, there was a limitation, consisting in the fact that, according to Oppenheim (1992) there should be a minimum five statements within a scale, in order to have a high internal consistency. Nevertheless, the first Likert scale from section B had only four statements, which attracted only a â&#x20AC;&#x2DC;fairâ&#x20AC;&#x2122; value of the Cronbach alpha. Also, there were three more questions with only two statements, which were classified as closed questions by the author, for the same reason. Second, with regard to bivariate analysis, even though the author employed cross tabulations breakdown and associations between the variables of the research, there is still a limitation (Oppenheim, 1992). As a result of the large volume of data and information and MMR and time constraints, the author was unable to divide the data into sub-groups of women entrepreneurs, according to their age. This limitation was partially removed, by using CA for FG and Interviews, and by grouping the younger women and the older women, into Gen Y and Gen X and analysing the relationship between the age, and women adherence to the usage of media technology, and their connectivity and

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participation in online communities. In addition, this lack in inferential statistics for the Survey was solved by looking into descriptive statistics of the thesis. Third, the author indeed used MMR in order to increase the reliability and validity of the results of this research. Nevertheless, the MMR tested the relationship and the impact, thus predicting the effect of the factors/independent variables upon the dependent variable. Despite the fact that, this is a hypotheses tested research, it would be helpful to test also the causation. Another limitation consisted in the fact that this is a cross sectional study developed at a certain moment in time. Consequently, for the validation of the results, the replication of the study together with the development of a longitudinal study across a longer period, will increase the reliability and ensure generalisability of these results at the national level (UK).

Therefore, the author will not recommend the

generalisation of the results at the United Kingdom level, but South East Wales or Wales only. Fourth, the research started with the survey and developed in parallel interviews and a focus group. However, some of the participants in the survey, accepted also to participate within the interviews. To prevent single data source bias, the author provided the opportunity for the participants to choose only one of the data collection technique, in other words to opt for the interview only and avoid the survey with questionnaires. The fifth limitation was with regard to using Factor Analysis with one single factor extraction for further analyses such as correlations and multiple standard regressions. To prevent biased interpretations, the author conducted additional factor extractions and analyses, based on the Eigenvalue coefficient (Pallant, 2013), and combined the results, and used these outcomes for the final interpretation of factor analysis, correlation and regressions. These, enhanced the interpretations and increased the validations of the technique. In this thesis, the author explored the impact of Learning and Digital Platforms & ICTs on WES. Nevertheless, the results and the limitations of this thesis, indicate the directions for the next research. The pioneering study of the impact and relationship of Learning and Digital Platforms & ICTs on WES, and the role of CoPs & networking, was rooted within a combined paradigm philosophy and in using MMR both parallel and sequential. Despite the novelty of the research topic and the implied benefits for women entrepreneurs, as a result of the mentioned limitations, (a) further research is required 337

with new research instruments, or (b) a replication of the research with a larger sample, at the national/international levels.

Further research could focus on conceptual

definitions in view to propose agreed final definitions of the terms and concepts defined by the author of this research. This will prepare the way for generalisation of agreed definitions and comparison with further research studies in the field of womenâ&#x20AC;&#x2122;s entrepreneurship. The author believes that further potential research could be developed on qualitative growth, by presenting growth from a qualitative perspective, such as: survival, stability, reputation and good relationship with customers, quality of products and services, satisfaction, enjoyment, life-work balance, flexibility and time with family, social media metrics (McCann and Barlow, 2015, p. 277). This recommendation is also supported by the outcome of the research conducted by Dalborg, von Friederichs and Wincent (2012) and McCann and Barlow (2015). Further, more research could be developed on women entrepreneursâ&#x20AC;&#x2122; feedback on using Digital Platforms & ICTs and their impact on business development. This can be approached in a comparative manner with the feedback from men entrepreneurs. Another direction that could be emphasised is the development of a research into the role of networking and business associations for the entrepreneurial success in a comparative manner considering both women and men entrepreneurs. Also, advisable, would be to develop an international research on WES and factors affecting entrepreneurial success in various European and non-European countries across the Globe, in an effort of promoting womenâ&#x20AC;&#x2122;s entrepreneurship. A wider research with larger sample, conducted across Wales with women owned businesses in High Street, as an enhancement of this present research, with funding from HEIs and the Welsh Government. Finally, the role of regional, national and international CoPs & networks for WES is another direction for the research.

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APPENDICES: APPENDIX A1: STATISTICS IN EUROPE AND UK Table 1: Employment rates (women and men aged 20-64) in EU member states 2004/ 2009: Countries Women % Men % Gender Gap % Year

2004

2009

2004

2009

2004

2009

EU-27

59.4

62.5

75.6

75.8

16.2

13.3

68.0

68.2

82.1

79.6

14.1

11.4

Source: Eurostat: Labour Force Survey (LFS), annual average, EC (2011, p. 30) Note: A positive gap indicates a higher unemployment rates for women in comparison with men, while the opposite is true for a negative gap.

Table 2: Unemployment rates (women and men aged 15 yrs and over) in EU 2004/2009 Countries Women % Men % Gender Gap % Year 2004 2009 2004 2009 2004 2009 EU-27 9.8 8.8 8.5 9.0 1.3 -0.2 UK 4.2 6.4 5.1 8.6 -0.9 -2.2 Source: Eurostat: Labour Force Survey (LFS), annual average, EC (2011, p. 32) Note: A positive gap indicates a higher employment rates for men in comparison with women, while the opposite is true for a negative gap.

Table 3: Employment rates for women/men aged 25-49 depending whether they have children, EU 2009: Countries Men % Women % EU-27 UK

Without children

With children

Without Children

With Children

81.8

90.3

77.0

65.6

89.9

82.2

65.4

Source: Eurostat: Labour Force Survey (LFS), annual average, EC (2011, pp. 36-37)

Table 4: Educational attainment (at least upper secondary level) aged 20-24 in EU 2009: Countries Women % Men % EU â&#x20AC;&#x201C; 27

81.4

75.9

81.3

77.4

Source: Eurostat: Labour Force Survey (LFS), annual average, EU (2011, p. 41)

Table 5: Gender segregation in occupation and in economic sectors in EU in 2009: Countries Gender segregation in Gender segregation in economic occupations % sectors % UK

24.7

19.5

Source: Eurostat: Labour Force Survey (LFS), annual average, EU (2011, p. 44) Note: Gender segregation is calculated as the average national share of employment for women and men applied for each occupation.

Table 6: Sex distributions of senior ministries in national governments in EU in 2010: Countries Women % Men % EU - 27

Source: Eurostat: Labour Force Survey (LFS), annual average, EU (2011, p. 48)

339

Table 7: Analysis of the number of enterprises by enterprise size class, non-financial business economy, in 2008 Countries Total number Micro % Small % Medium-Sized Large % of enterprises % (thousands) EU-27

20,994

92,0

6,7

1,1

0,2

1,731

89,3

8,8

1,5

0,4

Source: Eurostat: Key figures on European business, EC (2011, p. 12)

Table 8: Key indicators for the non-financial business economy 2008: Countries Number of Employment Turnover (EUR enterprises (thousands) 1,000 million) (thousands)

Value added (EUR 1,000 million)

EU-27

21,003.9

136,281.0

24,915.3

6,155.7

1,730.6

18,457.7

3,662.5

1,046.6

Source: Eurostat: Key figures on European business, EC (2011, p. 36)

Table 9: GEM 2011 Entrepreneurship Indicators. National Summary Sheet Entrepreneurship Indicators UK % France %

Spain %

Perceived opportunities

Perceived capabilities

Nascent Entrepreneurship Rate

4.7

4.1

3.3

Total early-stage Entrepreneurial Activity Rate (TEA)

7.3

5.7

5.8

Entrepreneurial Employee Activity Rate

4.3

3.9

2.5

Fear of Failure

Necessity Driven TEA Rate

1.3

0.9

1.5

Source: Adapted from GEM APS data

Table 10: GEM 2011 Entrepreneurship Indicators. National Summary Sheet: General Characteristics UK France

Spain

Population (x 1,000)

62,036

62,787

46,077

Area (x 1,000 km²)

242

548

499

Density (persons/km²)

255.4

113.8

91.1

GDP Per Capita (PPP) (USD)

35,974

35,049

30,622

Global Happiness Index %

7.1

6.6

7.2

Global Competitiveness Index %

5.4

5.1

4.5

Global Innovation Index %

(7/183)

(29/183)

(32/83)

Classification Phase of Economic Development

IDEs

Classification Entrepreneurship Profile

HEEA

LEA

Doing Business Index

Source: Adapted from GEM APS data Note: IDEs – Innovation Driven Economies; EDEs – Efficiency Driven Economies; HEEA – High Entrepreneurial Employee Activity; LEA – Low Entrepreneurial Activity; HEHA – High Entrepreneurial Activity and High Ambitions.

340

Table 11: Number of Enterprises in the private sector and their associated employment and turnover, by size of enterprise, UK start of 2011 Enterprises Employment(thousands) Turnover (£ millions)(1) All enterprises

4,525,765

23,391

3,052,558

SMEs (0-249)

4,536,445

13,760

1,489,255

All employers

1,178,745

19,707

2,850,127

With no employees(2)

3,364,020

3,684

202,431

1-9

968,545

3,651

403,871

10-49

173,405

3,469

460,500

50-249

30,475

2,957

422,454

250 or more

6,320

9,631

1,563,302

Source: Adapted from BIS – Department for Business Innovation and Skills, Statistics Note: (1) “All industries turnover” figures exclude Section K (Financial and insurance activities and Division 78 (employment activities); (2) “With no employees” comprises sole proprietorships and partnerships comprising only the self-employed owner managers and companies comprising only an employee director.

Table 12: Countries in Figures, 2009 Countries

Spain

France

United Kingdom

44,474,631

63,392,140

60,852,828

505,992

551,500

242,910

Population density (per km²)

91.1

115

251

Women %

50.7

51.4

Men %

49.3

48.6

Women in labour force %

Gender pay gap %

Women in p/t employment, 2006 %

Female tertiary students % in total for both sexes

Life expectancy at birth, female (yrs)

Life expectancy at birth, male (yrs)

Total Population (2007) Area (km²)

Source: UNECE, Statistical Division, 2011

Table 13: Countries in Figures, 2009 Countries

Spain

France

United Kingdom

Employment rate 2007 (change over previous year), %

3.0

1.3

0.7

Unemployment rate 2007 (change over previous year), %

8.3

5.3

Youth unemployment rate 2007 (change over previous year), %

18.2

18.7

14.4

Economic activity rate women %

Economic activity rate men %

1,413,803

2,084,064

2,104,330

GDP at current prices (millions of US Dollars, PPI) ¹

341

GDP at current prices per capita, US Dollars, PPI

31,506

35,049

34,620

Purchasing Power Parity (PPI), .../US Dollars (US= 1)

0.74

0.91

0.67

4,893,109³

11,585,736³

Gross External Debt (millions of US Dollars) Source: UNECE, Statistical Division, 2011 GDP – Gross Domestic Product; PPI – Purchasing Power Parity

Table 14: Employment by occupation groups, 2007, (%) Occupations Legislators, Professionals Clerks senior officers, managers

Craft

Plant & machine operators and assemblers

Gender

Male

Female

Male

Female

Male

Female

Male

Female

Male

Female

France

Spain

Source: UNECE, Statistical Division, 2011

Table 15: Participation in public life, 2007 (%) Government and Members of ministers Parliament

Judges

Central Bank Board members

Gender

Male

Female

Male

Female

Male

Female

Male

Female

France

Spain

Source: UNECE, Statistical Division, 2011

Table 16: Share of Businesses in the UK by size, 2018 Share of Business in the UK Businesses (%)

Employment (%)

Turnover (%)

Micro-Businesses (0-9 employees)

Small Businesses (10-49 employees)

Medium Businesses (50-249 employees)

Large businesses (250+ employees)

Source: BEIP, 2018; House of Common (Business Statistics, 2018)

Table 18: Business birth and deaths by region, in the UK Regions Births Births Rate (%) North West 47,465 16 North East 9,545 13 East Midlands 22,565 12 West Midlands 30,775 13 London 92,300 15 East 36,935 13 Wales 14,120 14 Scotland 21,565 12 Northern Ireland 6,855 11 United Kingdom 381,885 13

Deaths 36,405 9,075 22,740 26,280 86,270 37,770 10,725 20,430 4,940 356,815

Source: ONS, Business Demography, 2017; House of Commons, Business Statistics, 2018.

342

Deaths Rate (%) 12 12 12 11 14 13 10 11 8 12

Table 19A: Businesses by industries and sectors in the UK, 2018 Industry/Sectors Number of Businesses Agriculture, mining and utilities 192,000 Manufacturing 290,000 Construction 992,000 Total Services 4,194,000 Of which: Retail 556,000 Accommodation and Food 186,000 Arts and Recreation 276,000 Other Services 334,000 Source: BEIS, Business Population Estimates, 2018; House of Commons (Business Statistics, 2018)

Table 19B: Women Owned Business Sector Concentration (Female vs Male) Business Sector Female (%) Wholesale, retail trade, repairs 16 Hotels and restaurants 5 Real estate, renting and business 27 activity Health and social work 18 Other community, social and 18 personal services activity

Male (%) 11 3 26 3 10

Source: FSB, 2018

Table 20: Women Majority Owned Businesses – GVA Total/nation (million) Nation 2012 (£ million) 2015 (£ million) England 65,550 89,180 Scotland 4,978 8,826 Wales 3,306 4,161 Northern Ireland 1,800 3,384 United Kingdom (average) 75,635 105,551 Source: FSB, 2018

Table 21: Women Owned and Women led Businesses – Employment SMEs 2012 Wales/Majority Women Owned 102,708 (13.41%) Businesses Wales/Women led businesses 103,306 (13.49%) United Kingdom/Women 2,338,089 (9.79%) Owned Businesses United Kingdom/Women led 2,471,337 (10.34%) Businesses Source: FSB, 2018

343

2015 112,289 (13.27%) 115,495 (13.65%) 2,912,069 (11.26%) 3,246,747 (12.55%)

APPENDIX A2: DESCRIPTIVE STATISTICS Table 1A: The legal form of the business Frequency

Percent

Valid

Cumulative Percent

Percent Valid

public company

6.0

private company

24.7

30.7

community

2.0

32.7

family business

12.7

45.3

sole trader

53.3

98.7

multiple

1.3

100.0

150

100.0

interest company

selections Total Source: F. Tomos, 2019, SPSS

Table 1B: Type of ownership Frequency Valid

Percent

Valid

Cumulative

Percent

single owner

109

72.7

partnership female/male

10.0

82.7

partnership

4.7

87.3

partnership wife/husband

8.7

96.0

multipartners/others

4.0

100.0

150

100.0

female/female

Total Source: F. Tomos, 2016, SPSS

Table 1C: Firm initial size Frequency Valid

0-9 employees

Percent

Valid

Cumulative

Percent

143

95.3

10-49 employees

4.0

99.3

50-249 employees

100.0

150

100.0

Total Source: F. Tomos, 2016, SPSS

344

Table 1D: The age of the owner Frequency

Percent

Valid Percent

Cumulative Percent

Valid

18-25

6.0

26-30

9.3

15.3

31-40

19.3

34.6

41-50

26.0

60.6

51-60

26.7

87.3

61 or over

12.7

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

Table 1E: The year of creation Frequency Valid

Percent

Valid

Cumulative

Percent

before 1970

2.0

1971-1980

2.7

4.7

1981-1990

10.7

15.3

1991-2000

6.0

21.3

after 2000

118

78.7

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

Table 1F: The geographical location Frequency Valid

Percent

Valid

Cumulative

Percent

Wales

134

89.3

England

8.0

97.3

United Kingdom

2.7

100.0

150

100.0

Total Source: F. Tomos, 2016, SPSS

Table 1G: The type of business for women entrepreneurs Frequency Valid

Percent

Valid

Cumulative

Percent

Manufacturing

2.0

Retails

40.7

42.7

IT/Property

43.3

Promotion/Publicity

1.3

44.7

Consulting

1.3

46.0

Catering/Hotels

8.7

54.7

Beauty/Hairdressing

12.7

67.3

Health/Nutrition/Physiothe

2.7

70.0

rapy/Sport

345

Training/Education

1.3

71.3

Accounting/Finances

2.0

73.3

Arts/Crafts/Fashion Design

5.3

78.7

Services

2.7

81.3

Food/Hygiene

2.0

83.3

Jewellery

2.0

85.3

Others

4.0

89.3

Multiple businesses

10.7

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

Table 1H: The sector of the business Frequency Valid

Percent

Valid

Cumulative

Percent

manufacturing

6.7

whole sales and retails

54.0

60.7

health/social services

3.3

64.0

services/accommodation/

27.3

91.3

IT/Finance/Insurance

3.3

94.7

multiple selections

5.3

100.0

150

100.0

Frequency

Percent

Valid

Cumulative

Percent

cafes/restaurants

Total Source: F. Tomos, 2016, SPSS

Table 2A: Studies

Valid

Business/Management

10.7

Accounting/Finances

4.0

14.7

Marketing

1.3

16.0

Entrepreneurship

16.7

Technology/IT

2.0

18.7

Others

32.7

51.3

None

32.0

83.3

Multiple selections

16.7

100.0

(1,2,3,4) Total

150

Source: F. Tomos, 2016, SPSS

346

100.0

Table 2B: Business sector experience Frequency Valid

Missing

Percent

Valid

Cumulative

Percent

Yes

38.7

38.9

60.7

61.1

100.0

Total

149

99.3

100.0

150

100.0

missing answer

Total Source: F. Tomos, 2016, SPSS

Table 2C: Entrepreneurship experience Frequency Valid

Percent

Valid

Cumulative

Percent

Yes

50.7

28.0

78.7

Some Knowledge Total

21.3

100.0

150

100.0

Source: F. Tomos, 2016, SPSS

Table 2D: Business management experience Frequency Valid

Missing

Percent

Valid

Cumulative

Percent

Yes

52.0

52.3

47.3

47.7

100.0

Total missing answer

149

99.3

100.0

150

100.0

Total Source: F. Tomos, 2016, SPSS

Table 2E: Entrepreneurship courses before business Valid

Frequency

Percent

Valid Percent

Cumulative Percent

Yes

32.0

102

68.0

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

Table 2F: Entrepreneurship courses after starting business Valid

Frequency

Percent

Valid Percent

Cumulative Percent

Yes

42.0

58.0

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

347

Table 2G: Interactive learner Valid

Frequency

Percent

Valid Percent

Cumulative Percent

Yes

132

88.0

11.3

99.3

n/a

100.0

150

100.0

Total Source: F. Tomos, 2016, SPSS

Table 2H: Networking learner Valid

Frequency

Percent

Valid Percent

Cumulative Percent

Yes

50.7

48.7

99.3

n/a

100.0

150

100.0

Total Source: F. Tomos, 2016, SPSS

Table 3A: The usage of networking Valid

Frequency

Percent

Valid Percent

Cumulative Percent

Yes

111

74.0

26.0

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

Table 3B: Learn from information, participation and sharing Valid

Missing Total

Frequency

Percent

Valid Percent

Yes No n/a (following the filter question) Total

108 4 37

72.0 2.7 24.7

72.5 2.7 24.8

149

99.3

100.0

Missing answer

1 150

.7 100.0

Cumulative Percent 72.5 75.2 100.0

Source: F. Tomos, 2016, SPSS

Table 3C: Twitter for learning Frequency Valid

Percent

Valid Percent

Cumulative Percent

Yes

55.3

44.7

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

348

Table 3D: Wireless connection for learning (N=150, Valid) Frequency Percent Valid Percent Valid

Cumulative Percent

Yes

130

86.7

13.3

100.0

Total

150

100.0

Source; F. Tomos, 2016, SPSS

Table 4A: The usage of Digital Platforms & ICTs Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Missing

Yes

132

88.0

88.6

11.3

11.4

100.0

Total Missing answer

149

99.3

100.0

150

100.0

Total Source: F. Tomos, 2016, SPSS

Table 4B: Mobile internet usage for business Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Yes

137

91.3

8.7

100.0

Total

150

100.0

Source: F.Tomos, 2016, SPSS

Table 4C: Mobile applications usage for business Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Yes

109

72.7

27.3

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

Table 4D: Facebook usage for business Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Yes

118

78.7

21.3

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

349

Table 4E: Google usage for business Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Yes

116

77.3

22.7

100.0

Total

150

100.0

Source: F.Tomos, 2016, SPSS

Table 4F: Other social network usage for business Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Yes

43.3

56.7

100.0

Total 150 Source: F. Tomos, 2016, SPSS

100.0

Table 4G: Google Search for business Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Yes

135

90.0

10.0

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

Table 5A: Digital Platforms & ICTs help me to participate in CoPs Frequency

Percent

Valid Percent

Cumulative Percent

Valid

False

4.0

True

103

68.7

72.7

n/a

27.3

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

Table 5B: Facebook helps my participation in CoPs Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Yes

54.0

18.0

72.0

n/a

28.0

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

350

Table 5C: Twitter helps my participation in CoPs Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Yes

48.7

23.3

72.0

n/a

28.0

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

Table 5D: Women Entrepreneurs & Communities of Practice Valid

Missing

Frequency

Percent

Valid Percent

Cumulative Percent

Yes

100

66.7

67.1

16.0

16.1

83.2

n/a

16.7

16.8

100.0

Total

149

99.3

100.0

150

100.0

999

Total Source: F. Tomos, 2016, SPSS

Table 5E: Women Entrepreneurs & Networking Groups Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Missing

Yes

51.3

51.7

31.3

31.5

83.2

n/a

16.7

16.8

100.0

Total

149

99.3

100.0

150

100.0

999

Total Source: F. Tomos, 2016, SPSS

Table 5F: Mobile phones help participation in CoPs Valid

Frequency

Percent

Valid Percent

Cumulative Percent

Yes

64.7

7.3

72.0

n/a

28.0

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

Table 5G: iPad, tablets help my participation in CoPs Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Yes

55.3

16.7

72.0

n/a

28.0

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

351

Table 5H: Digital Platforms & ICTs increase business success (N=150, Valid) Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Yes

135

90.0

10.0

100.0

Total

150

100.0

Source: F. Tomos, 2016, SPSS

Table 6A: Entrepreneurial learning increase business success, (N=149, Valid) Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Missing

Yes

104

69.3

69.8

30.0

30.2

100.0

Total

149

99.3

100.0

150

100.0

999

Total Source: F. Tomos, 2016, SPSS

352

APPENDIX B: SAMPLING AND DATA COLLECTION Table 1: The frame list with networks, groups and associations of women entrepreneurs 1 The Networking Forum for Women in Business 2 Business Womenâ&#x20AC;&#x2122;s Link 3 Business Bubble Network 4 Cambridge Businesswomenâ&#x20AC;&#x2122;s Network 5 Fabulous Women 6 Forward Ladies 7 Handbags and Briefcases Associations Directory 8 British Associations of Women Entrepreneurs 9 Association of Accounting Technicians, Directory Wales 10 Yell. Com Directory 11 Oriflame Network 12 Avon Network 13 Highflying Divas, Essex 14 Metis Women 15 Rural Women Network 16 Surrey Chambers Business Women 17 I am a Woman Network 18 Prowess Women in Business 19 Connect Networking in Bristol 20 4 Networking 21 Women International Business Network (WIBN) 22 Chamber of Commerce 23 4 Networking 24 Dottie Ladies Club 25 Hair Dressing Association 26 Community Association with other Shops 27 British Florists Association 28 British Women Penarth 29 Interflora 30 Small Business Federation 31 National Training Federation for Wales 32 Ceramic Owners Association 33 Federation of Holistic Therapists 34 High Street Traders 35 Market Federation Committee 37 The Jewellery Society 38 Wales Craft Council 39 Artfinder 40 Welsh Women Enterprise Group Source: Author, 2015

353

Table 2: Survey with Questionnaires: Women Entrepreneurs in High Streets in SE Wales Location Association/Group Research type Number of Date of Collected Collection Questionnaires C - SE Wales Market Traders Fieldwork 4 22/09/2015 Association C - SE Wales High Street Traders Fieldwork 2 17/09/2015 C - SE Wales P – SE Wales P – SE Wales SE Wales B – SE Wales C – SE Wales Y – SE Wales P – SE Wales P – SE Wales C – SE Wales C – SE Wales B – SE Wales C – SE Wales C – SE Wales N – SE Wales Y – SE Wales P – SE Wales P – SE Wales Y – SE Wales B – SE Wales Y – SE Wales L – SE wales Y – SE Wales B – SE Wales H – SE Wales Y – SE Wales C – SE Wales C – SE Wales Y – SE Wales W – SE Wales P – SE Wales P - SE Wales

C – SE Wales P – SE Wales P – SE Wales C – SE Wales C – SE Wales C – SE Wales C – SE Wales C – SE Wales C – SE Wales C – SE Wales

Market Place High Street Traders High Street Trader Arts & Crafts Cardiff Festival High Street Traders Arcade Traders High Street Traders High Street Traders

Fieldwork Fieldwork Fieldwork Fieldwork

3 1 1 10

25/08/2015 24/08/2015 7/08/2015 21/08/2015

Fieldwork Fieldwork Fieldwork Fieldwork

10 1 1 1

3/09/2015 28/08/2015 01/08/2015 01/09/2015

ACCA High Street Cardiff Arts Festival High Street Traders Arcade Traders Market Place High Street Traders High Street Traders High Street Traders High Street Traders High Street Traders High Street High Street Traders High Street Traders Arcade Traders& High Street High Street Traders Young Entrepreneurs High Street Traders High Street High Street Traders High Street High Street Traders High Street Women Business Networking event

Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork

1 2 1 7 3 2 5 1 1 6 1 5 1 2 3

01/09/2015 04/09/2015 21/08/2015 04/09/2015 11/09/2015 11/09/2015 20/08/2015 05/08/2015 10/08/2015 07/08/2015 30/07/2015 30/07/2015 29/07/2015 29/07/2015 29/07/2015

Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork

3 1 1 1 3 2 4 4 12

28/07/2015 28/07/2015 05/08/2015 11/08/2015 14/08/2015 13/08/2015 13/08/2015 12/08/2015 12/08/2015

Arcade Traders High Street Traders High Street Traders High Street Traders Arcade Traders High Street Arcade Traders High Street Traders Arcade Traders Avon

Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Fieldwork Telephone

2 7 4 4 1 1 3 7 3 1

06/08/2015 04/08/2015 03/08/2015 18/08/2015 15/08/2015 18/08/2015 17/08/2015 17/08/2015 09/08/2015 05/08/2015

354

R â&#x20AC;&#x201C; SE Wales England England Various locations England England Various locations England

Oriflame

Telephone

06/08/2015

various Connect Networking Bristol various various

Email Emails

1 1

19/08/2015 31/07/2015

Email Email

3 1

23/07/2015 22/07/2015

various

Email(online)

24/07/2015 27/07/2015

Total Questionnaires Total Questionnaires Collected from WE on High Street

150 (100%) 104 (69.3%)

Source: F. Tomos, 2015, 2019

355

Pilot Study: Feedback on the Questionnaire 1.

How long did it take to complete the questionnaire?

.......................................................................................................................................2.

Did

you

understand all the questions? Yes

3. In your opinion, which question was not relevant for this research? ....................................................................................................................................... 4. Is there any question(s) that you think should have been included, but are not in the questionnaires? Yes

If ‘Yes’, please state: ................................................................................................... 5. What is your opinion regarding the section D? Are the suggested measures for success appropriate for women entrepreneurs? Yes

If ‘No’, please explain................................................................................................... 6. What do I need to change in this questionnaire? ....................................................................................................................................... ....................................................................................................................................... 7. What I do not need to change? .......................................................................................................................................

356

Statement of Informal Consent

I ..........................................................................agree to participate in this research project with the title: “The Impact of Entrepreneurship Education and New Emerging Technologies for Women Entrepreneurs’ Success and the Role of CoPs & networking”, conducted by PhD Research Student Florica Tomos from University of South Wales, United Kingdom. I understand that the purpose of this study is to hold a Focus Group on the above research topic and to discuss our general ideas about the topic. I understand that the study involve other participants and will last about 30 minutes and the conversation will be recorded. I understand that the participation within this study is voluntarily and that if I wish to withdraw from the study and leave, I may do so at any time. I understand that I have been asked not to talk about any of my own or others’ private experiences or opinions, that I consider too personal. I understand that all information will be kept confidential and the name of the people involve will be confidential. I have read and understood this information and I agree to take part in the study. Data..........................................

Signature.................................................................

If you have any concerns please contact the Researcher: Florica Tomos – floricatomos@southwales.ac.uk

357

Table 1: STATISTICS Location P- SE Wales B – SE Wales P – SE Wales P Network – SE Wales Total Table 2: STATISTICS Location Wales Wales/England

Questionnaires Incomplete Fail to cooperate Withdrawal Unreturned

Questionnaires 148 300

Wales TOTAL Table 3: STATISTICS Location Wales (Survey/Fieldwork/ Telephone) Wales/England (Survey/emails) Wales (Telephone survey) TOTAL

Table 4: STATISTICS Location Wales/England Wales Wales

2 450

Date 16/09/15 04/09/15 03/09/15 09/09/15

Type Survey (fieldwork) Online (email) survey Telephone survey N/A

Number 1 1 1 7 10 Situation Complete/Successful Incomplete/Unsuccessful Complete/Successful N/A

Questionnaires Distributed 150

Quest. Returned 140

Quest. Unreturned 10

93% Successful

300

292

97% Unsuccessful

100% Successful

450

150

302

Data Collection Survey Focus Group Interviews

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Situation

Number of Participants 150 5 37

Address to Women Entrepreneurs â&#x20AC;&#x201C; Online Survey

Dear Mme,

This email is addressed to women entrepreneurs, acting as business owners. I am conducting a research on behalf of University of South Wales and I therefore invite you, please participate within this 10 minutes survey by questionnaires. The result of this research is valuable and of benefit for all women entrepreneurs. It will inform policy makers, academics and Government about the learning needs of women entrepreneurs, and will highlight their contribution to the economy in the UK and across the world. Please take 10 minutes and complete carefully all the questions (each line) of this Questionnaire. I thank you for your participation. Please complete this Questionnaire as soon as possible and send this on my email address below: Florica.tomos@southwales.ac.uk

Kindest Regards,

Florica Tomos PhD Researcher University of South Wales Treforest, H331 01443482321

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Focus Group â&#x20AC;&#x201C; Questions

Please speak about the type of business you have and your business educational background. What are you daily activities?

Can you please define the following terms: Women Entrepreneurs, Entrepreneurial Success, and Business Growth?

How would you evaluate success?

How do you learn and what are your learning preferences in the context of new emerging technologies (Information Communication Technologies, Social media: Facebook, Twitter, iPhone, iPad, Mobile and Smart Phones, Androids, Tablets, Computers)? Do you use these for learning? Do you use them for business?

How do you acquire knowledge and information in the Context of Networking and New Emerging Technologies, in order to achieve success? Do you belong to any Business Association, Networking Group?

What is your opinion regarding the impact of Education Entrepreneurship and New Emerging Technologies (ICT) on women entrepreneursâ&#x20AC;&#x2122; success?

Is gender an issue (benefit/barrier) for you as a woman entrepreneur in the business world? Do you enjoy being a women entrepreneur?

What is your opinion about networking and business/professional associations for learning and success?

Thank you for participation!

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Interview â&#x20AC;&#x201C; Questions 1.

Business Sector Experience: Please speak about your business in general and your experience in the sector.

Learning style: What is your learning style? How do you learn? What type of learner are you?

How do you expect to learn?

Do you use the new emerging technologies for learning (Facebook, Twitter, iPhone, iPad, tablets, etc)?

Do you use them for your business?

How would you describe the role of Entrepreneurship Education for business success?

What are your learning needs?

What would you like to learn in order to improve the success of your business?

Does the networking help you to improve your learning?

10. Does networking help you to grow your business? 11. Do you belong to any Professional/Business Association? Please name it. Speak about their importance. 12. How important are in your opinion the ICTs and new emerging technologies (Facebook, Twitter, Linkedin, Yahoo Messenger, Google) for: a) Learning; b) Business success? 13. Which of the new emerging technologies are the most used for: a) Learning; b) Business success? 14. Please describe in your own words the following terms: a) Women Entrepreneurship; b) Women Entrepreneurs; c) Women Entrepreneursâ&#x20AC;&#x2122; success? 15. Do you enjoy being a woman entrepreneur? Why do you enjoy?

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Focus Group/Interviews Registration Form Name/Surname

Contact Details

Nationality

Email/Phone

Gender/Age

Business Name

Signature

Interview INVITATION I am inviting you to participate to an interview on the .................................August 2015 (12:00-15:30) at University of South Wales via phone, over Internet, via Skype or Face-to-Face on the following research topic: ‘The Impact of Entrepreneurship Education and New Emerging Technologies on Women Entrepreneurs’ Success and the Role of CoPs & networking’. Would you be able to participate? If you agree to come, could you please give me your contact details? Signature......................................................................................................................................................... Contact Details................................................................................................................................................ Name/Surname............................................................................................................................................... Mobile............................................................................................................................................................ Email.............................................................................................................................................................. My contact detail: Florica Tomos, H331, Faculty of Business & Society, University of South Wales, Treforest, CF37 1DL, telephone: 01443482321, Mobile: 077x87xxxxx. Florica.tomos@southwales.ac.uk Focus Group Agenda 1. 2. 3. 4. 5. 6. 7.

Topic: ‘The Impact of Entrepreneurship Education and New Emerging Technologies on Women Entrepreneurs’ Success and the Role of CoPs & networking’. Information Sheet Updates on the Survey Introducing the Mediator and her ROLE. Ethics/ Consent Questions Discussions

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Data Protection Act 1998 Research Consent Form Topic: The Impact of Entrepreneurship Education and New Emerging Technologies on Women Entrepreneurs’ Success and the Role of CoPs & networking Name of the Researcher: Florica Tomos PhD Research student Contact Details: Faculty of Business and Society, H331, Treforest, CF37 1DL Email address: florica.tomos@southwales.ac.uk Participant name: ......................................................................................................................................... Contact Details............................................................................................................................................. Email address............................................................................................................................................... Personal data to be collected: This research will record participants’ opinions regarding the impact of entrepreneurship education and new emerging technologies on women entrepreneurs’ success. The discussions will explore how women entrepreneurs learn.

Further, the discussions will focus on assessing whether the entrepreneurship

education and new emerging technologies have an impact on women entrepreneurs’ success. Please complete the following data, as outlined above, being used for this research project. .......................................................................................................................................................................... All personal data collected will be processed in accordance with the Data Protection Act 1998. Signature.......................................................................................................................................................... Date..................................................................................................................................................................

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INFORMATION FOR THE PARTICIPANTS (Focus Groups and Interview) Doctoral Thesis: ‘The Impact of Entrepreneurship Education and New Emerging Technologies for Women Entrepreneurs’ Success and the Role of CoPs & networking’ You are invited to take part in this research, to attend an interview/Focus Group on the.............................2015, at....................................................... It is very important for you to understand the topic of this research, and what it will involve. Please read the following information carefully. The PURPOSE of the Research There is an increasing role and contribution of women entrepreneurs to the national economic growth. Therefore, this research is aiming to find out the impact of entrepreneurship education and Information Communication Technologies on Women Entrepreneurs’ Success. The research is exploring the way women entrepreneurs learn, their learning methods and their learning needs, their satisfaction with learning and whether they use ICTs for learning and for business. Furthermore, the research is targeting to discover how women entrepreneurs measure ‘success’ and what is their interpretation and definition of ‘women entrepreneurs’. The results of this research is valuable and of benefit for all women entrepreneurs. It will inform policy makers, academics and Government about the learning needs of women entrepreneurs, and will highlight their contribution to the economy in the UK. The FRAMEWORK and the main Concepts used in this research New Emerging Technologies: Facebook, Twitter, Linkedin, Smart Phone, iPhone/iPad, Tablets, etc. Blended learning: class-based learning (traditional), and online learning with ICT. CoPs: Communities of Practices (Networks and Associations with people who share the same interest) Learning types and learning satisfaction. The REASON for your participation The research emphasises the role and the importance of women entrepreneurs to the national economy and the global economy. Further, they are a specific group with certain characteristics and various learning styles. They also can display preferences for particular ICT to be used for business and learning. Therefore, the purpose of the research is to find out what is your opinion within this interview and draw conclusions and recommendations, so that the Government, policy makers and HEIs will come and meet women entrepreneurs’ learning needs in order for them to achieve success. More INFORMATION: The discussion will be recorded. By agreeing to participate within the interview/Focus Group, we expect you to participate within the discussion with a level of commitment and express your pros and cons regarding the importance of entrepreneurship education and new emerging technologies for women entrepreneurs’ success. Also, we appreciate your opinions regarding the definition of terms such as: women entrepreneurs, success and women entrepreneurship.

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Note: This information is confidential and for the purpose of this research only. The participants are not allowed to develop the same research topic for the next three years, until this Thesis is completed and the results will be published. Data generated by this research will be archived in accordance with the Data Protection Act, 1998 and Government Information Act. The data will be used for the needs of the research. We thank you for your participation! Florica Tomos PhD Researcher University of South Wales 01443482321 Florica.tomos@southwales.ac.uk

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Survey QUESTIONNAIRE

27 May 2015 Dear Participant, I am a PhD research student at University of South Wales, Faculty of Business & Society. I am investigating the impact of Entrepreneurship Education and Emerging Technologies on Women Entrepreneurs’ Success and the Role of CoPs & networking. The attached Questionnaire is part of this research and will attempt to determine whether the Entrepreneurship Education and New Emerging Technologies have a positive impact on business growth and women entrepreneurs’ success. Your response is very important for the advancement of this research and for finding optimal solutions in order to help women entrepreneurs with learning, acquiring knowledge, overcoming barriers and supporting each other. Women entrepreneurs are major contributors to the economies in the UK and across the world. However, little research was developed on women entrepreneurs in the last decades. As a consequence of this research, I shall be able to find new methods of helping women entrepreneurs. I therefore, kindly request your participation in this 10 minutes survey. Should you have any queries and comments regarding this survey, you are welcome to contact me on 01443482321 or by email: Florica.tomos@southwales.ac.uk I will appreciate the help you will give to the successful result of this research. Thank You!

Acknowledgement – This Questionnaire is based on the literature review as well as inspired from the questionnaires by Buckley (2009), Grosch (2011) and Tomos (2011). Florica Tomos PhD Research Student University of South Wales, Faculty of Business & Society Treforest Campus CF37 1DL Email: Florica.tomos@southwales.ac.uk

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Section A – Background Information This section refers to the background and demographic information. The researcher is aware of the confidentiality of the questions and therefore, the information will remain anonymous. The responses to these questions will allow the researcher to compare groups of respondents. Your collaboration will be highly valued. 1.

What is the legal form of your business? (Please place a tick in one box) Public Company 1 Private Company 2 Community Interest Company 3 Family Business 4 Sole Trader 5

Please state the type of ownership for your business: Single owner Partnership – female/male Partnership - female/female Partnership – wife/husband Multi Partners / Others (Please specify)

1 2 3 4 5

Please indicate the firm size: initial size (number of employees at the creation): Business Size Answers (Number of employees) 0–9 1 10 – 49 2 50 - 249 3

Please indicate the firm size: current size (number of employees at present): Business Size Answers (Number of employees) 0–9 1 10 – 49 2 50 - 249 3

What is your current position in the firm? Owner Partner 1 2

Owner/Director 3

Please indicate the year of creation (Please place a tick in one box): Before 1970 1 1971 - 1980 2 1981 - 1990 3 1991 - 2000 4 After 2010 5

What is the firm age? (Number of years of operation) Less than 1 year At least 1 but less than 3 years At least 3 but less than 5 years At least 5 but less than 10 years At least 10 but less than 20 years 20 years or more

1 2 3 4 5 6

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Other 4

Please indicate the sector of your business: Manufacturing Wholesale and Retail Trade Health/Social services Agriculture Services/Accommodation/Cafes/Restaurants Constructions/Transport/Storage IT/Finance/Insurance

1 2 3 4 5 6 7

What type of business do you have (Please place â&#x20AC;&#x2DC;Xâ&#x20AC;&#x2122; in the appropriate box): Manufacturing 1 Retails 2 IT/Property 3 HR/Personnel 4 Promotion/Publicity 5 Consulting 6 Building and Constructions 7 Catering/Hotels 8 Beauty/Hairdressing 9 Health/Nutrition/Physiotherapy/Sport 10 Training/Education 11 Accounting /Finances 12 Arts/Crafts/Fashion Design 13 Charity/Community Services 14 Social care/cleaning 15 Services 16 Food/Hygiene 17 Cosmetics/perfumes 18 Jewellery 19 Others (Please state) 20

10. Where is the geographical location of your business? Wales England 1 2

United Kingdom 3

11. How wide is the market area for your business? Local Regional National Online National 1 2 3 4

International 5

12. Gender of the owner/owners of the business. Female Male & Female Female & Female 1 2 3 13. What is the age of the owner? Age group. 19-25 26-30 31-40 1 2 3

41-50 4

14. What is the nationality of the owner? Welsh English 1 2

British 3

15. What is the ethnicity of the owner? White British/Welsh Black British Indian/Bangladesh/Pakistani Chinese

1 2 3 4

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Online International 6

Others (please state) 4 51-60 5

61 or over 6 Other 4

White European Other(Please state)

5 6

16. How many years have you been the owner of the business? 0-5 6 - 10 10 - 20 1 2 3

More than 20 4

17. Please state the current annual sales/turnover figures of your business (as per financial year). Sales/Turnover (£000) Answers X From 1 to 100 1 From 101 to 500 2 501 – 1,000 3 1,000 – 5,000 4 Over 5,000 5 18. Previous experience as a manager/leader. Experience Yes No Manager Leader Sector Section B – Entrepreneurship Education The section contains a set of closed and open questions regarding entrepreneurship education, general background education, models and types of learning you use and learning preferences and satisfaction. Please provide answers that best represent you. 1. What is your educational background? (Please place a tick in a box) GCSE/High A Level/ Graduate Postgraduate Vocational/ Other School College Professional 1 2 3 4 5 6

Which of the following studies did you undertake? Business/Management 1 Accounting/Finances 2 Marketing 3 Entrepreneurship 4 Technology/IT 5 Others (Please state) 6 None 7

Did you undertake Entrepreneurship training/courses: Before starting the business Yes After starting the business Yes

What entrepreneurship skills/competences do you have? Management Finances (Budgets/Cash Flow) Sales/Negotiating Marketing/Promotion/Advertising Information Communication Technologies Accounting Facebook, Twitter, Blogs, LinkedIn None How would you describe yourself as a learner: Formal learner Informal learner Doing/Asking/Applying learner

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No No 1 2 3 4 5 6 7 8 1 2 3

Experience-based learner Observational and role-model based learner

4 5

Please state what are your business learning needs: ........................................................................................................................................................... .......................................................................................................

How would you describe yourself? Interactive learner Networking learner

Yes Yes

No No

According to your opinion, before starting your current business, did you have experience/knowledge in one of the following: finance, marketing, sales, and management, negotiating, networking? Yes No Some knowledge

After starting the business did you acquire this business knowledge? Yes No Some business knowledge

10. Please state if you use networking: Yes No Note: a) If ‘Yes’, go to Q (11) and Q (12); b) If ‘No’ go to Q(13). 11. If you use networking, what type of knowledge do you need to acquire: Social Professional Business

Other

12. If you use networking, please indicate if you learn from information and communication, participating and sharing: Yes No 13. Please indicate if you use ICT and new emerging technologies when learning (Computer, mobile phones, Twitter, Facebook, Blogs, websites, Blackboards). Yes No 14. Learning Preferences (Please place a tick in the appropriate box): Learning style Strongly Disagree Neither Disagree Flexible formal Flexible with ICTs & informal Experience-based Role model-based

Agree

Strongly Agree

15. What is your satisfaction with learning (Your business/entrepreneurship learning since you started the business)? Attitudes Strongly Disagree Disagree Neither Agree Strongly Disagree Satisfied Unsatisfied 16. How would you define in your own words the following terms: Women Entrepreneurship is............................................................................. .......................................................................................................................... Women Entrepreneurs are................................................................................

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Section C – New Emerging Technologies 1. How often do you do the following? 1.1 Attending courses

Very often

Often

Neither

Not often

Never

Don’t know

1.2 Learning by yourself at home 1.3 Learning in groups (more than two people) 1.4 Learning with others online (via Facebook, Instant Messenger, e-mail) 1.5 Learning using ICTs (laptop, computer, tablets, iPhone, iPad) 1.6 Doing business using ICTs (laptop, computer, tablets, iPhone, iPad) 2. Which of the following are you using for learning?

Answers (Place a tick)

2.1Video sharing website (You Tube) 2.2 Instant messengers (MSN Messenger, Yahoo Messenger, Skype) 2.3 Facebook 2.4 Google+ 2.5 Other social networks (LinkedIn, MySpace) 2.6 Playing computer games 2.7 Mobile phones (iPhone, smartphone) 2.8 Internet connection at home 2.9 Wireless connection 2.10 Twitter 2.11 Virtual lectures (web conferences, real time) 2.12 Virtual class in non-real time 2.13 None 3. Which of the following do you use for business? 3.1 Mobile phones 3.2 Mobile internet connection (via mobile phone, notebook, tablet) 3.3 Facebook 3.4 Google+ 3.5 Other social networks (LinkedIn) 3.6 Google Search 3.7 Mobile apps 3.8 Internet connection at home 3.9 Internet Forums 3.10 Twitter 3.11 YouTube 4. How satisfied are you with the use of the above (Q2) for the study?

Strongly Disagree

Yes

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

No No No No No No No No No No No

Answers Yes Yes

No No

Yes Yes Yes Yes Yes Yes Yes Yes Yes

No No No No No No No No No

Disagree

Neither

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Agree

Strongly Agree

Don’t Know

4.1 Satisfied 4.2 Unsatisfied 5. How satisfied are you with the use of the above (Q3) for business? 5.1 Satisfied

Strongly Disagree

Disagree

Neither

Agree

Strongly Agree

Donâ&#x20AC;&#x2122;t Know

5.2 Unsatisfied

Section D â&#x20AC;&#x201C; Networking/Communities of Practice (CoP) Communities of Practice are types of associations and networking groups who come together to share expertise, knowledge, ideas and who have a passion for a common venture/business. They share, interact, participate, collaborate and learn from each other. Members have personal commitment to the work of the community. They use the same resources and vocabulary and they are devoted to extend their knowledge and expertise in that particular area/field. 1.

Do you belong to a group/network where you share knowledge and experience with others in the same field? CoP Yes No Business Associations Yes No Professional Associations Yes No Networking Groups Yes No Other (Please indicate) Yes No 2. Could you please state the name of that Group/Association? ....................................................................................................................................... 3. What type of participation are you using to communicate with other members (Please mark all applicable): Face-to-face 1 Online 2 Other (please explain) 3 ....................................................................................................................................... 4. Please state your agreement with the following statements: Strongly Disagree Agree Strongly Disagree agree 4.1 By participating in CoP I increase my knowledge 4.2 By participating in CoP I learn from experts 4.3 By participating in CoP I find information to grow my business 4.4 By participating in CoP, I learn from role models, I share knowledge 4.5 By participating in CoP I am encouraged and motivated to succeed 4.6 The participation in the CoP gives me the sense of belonging and identity 4.7 The participation in the CoP is important for my success in business 5.

Please state if the following statement is true or false:

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The new emerging technologies help my participation in CoP The new emerging technologies do not help me with the participation in CoP 6.

False

True

False

True

The following new emerging technologies help me to participate in CoP: Laptop/computer Yes Mobile phone, iPhone, Smartphone Yes iPad, tablet Yes Yahoo Messenger Yes Facebook Yes Twitter Yes Skype Yes Other (please state) Yes None Yes

No No No No No No No No No

Section E â&#x20AC;&#x201C; Women Entrepreneursâ&#x20AC;&#x2122; Success 1. In the last five years did your business registered an increase in sales/turnover? (Even though you just started the business and have an increase in sale, please answer): Yes No 2. In the last five years did your business increase the numbers of employees? Yes No N/A 3. Which of the following financial measures would you describe as measures for business success? Increase in Sales 1 Increase in Profit 2 4. Which of the following non-financial measures would you describe as determinants for business growth and success? 4.1 Enterprise culture 1 4.2 Innovation 2 4.3 Usage of ICT and Globalization 3 4.4 Entrepreneurial Knowledge 4 4.5 New Emerging Technologies (Facebook, Google+, Twitter, LinkedIn) 5 4.6 Entrepreneurship Education 6 4.7 Networking and CoP 7 4.8 Effective website 4.9 Larger product range 4.10 Quality of the product/service 4.11 Customer loyalty/satisfaction 4.12 Brand recognition 4.13 Niche market 4.14 Increase in number of employees 4.15 Social recognition 4.16 Survival

8 9 10 11 12 13 14 15 16

5. On a scale from 1 to 5 please rate your opinion regarding the impact of the following factors for business success: 5.1 Entrepreneurship Education 5.2 New emerging technologies (Facebook, Twitter, LinkedIn, Mobile Phones, Skype) 5.3 Networking and CoP 5.4 Twitter

373

1 (Low)

5 (High)

5.5 Facebook 5.7 Internet 5.8 Laptops/computers 5.9 Mobile phones 5.10 Tablets 6. Do you think Entrepreneurship Education is enhancing business success? Yes No If ‘Yes’, Why? .............................................................................................................. 7.

Please state whether by using the new emerging technologies, you increased the success of your business? Yes No

Please indicate whether by undertaking business and entrepreneurial training you increased the success of your business? Yes No 9. How would you define women entrepreneurs’ success? ...................................................................................................................................... ..................................................................................................................................... 10. Please indicate your recent entrepreneurial learning: 10.1 Management 1 10.2 Leadership 2 10.3 Networking 3 10.4 ICT & Globalization 4 10.5 Entrepreneurial Skills 5 10.6 Economics 6 10.7 Legislation 7 10.8 Finances and Accounting 8 10.9 Interpersonal skills 9 10.10 Human Resources 10 10.11 Marketing, Promotion 11 10.12 Sales, Negotiation 12 1o.13 None 13 11. Which of the following types of learning did you use to enhance the success of your business? Traditional (Class-based) learning 1 Blended (traditional and online) 2 Online learning 3 Distance learning 4 E-learning 5 Networking through Facebook, Twitter, LinkedIn 6 None 7 12. What would you recommend to others to do regarding entrepreneurship education in view to achieve success? (Place a tick) Continue to Learn from Learn from Undertake Adhere to Networking learn the own more professional experience of experience entrepreneurship Bodies others education 1 2 3 4 5 6 13. Do you enjoy being a women entrepreneur? Yes No 14. Please explain why: ................................................................................................

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Thank you very much for the participation in this survey! Without your involvement this research could not take place. We would like to ask you please, be kind and give us the following details about yourself: Name/Surname........................................................................................................... Business Name............................................................................................................ Email address.............................................................................................................. Telephone number/Mobile........................................................................................... These information is strictly confidential and we will only use if we need more information regarding this research. Note: Please state if you would like to be contacted in the future by our university and receive further information about training, business courses, entrepreneurship education, knowledge, collaboration, and networking: Yes No Florica Tomos PhD Research Student University of South Wales, Faculty of Business & Society Treforest Campus CF37 1DL Email: Florica.tomos@southwales.ac.uk

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APPENDIX C: DATA CODING CODEBOOK for entreprsurvey.sav

A. Variable allocation document (Agreed allocation of questions to variables, shortened labelling system)

Background and Demographic Data – Section A (Question 1 – Question 18)

Entrepreneurship Education – Section B (Question 1 – Question 16) EE1 – EE16

New Emerging Technologies – Section C (Question 1 – Question 5) NET1 – NET5

Networking /Communities of Practice (CoP) – Section D (Question 1 – Question 6) NCoP1 – NCoP6

Women Entrepreneurs’ Success and Business Growth – Section E (Question 1 – Question 14) WESG1 – WESG14

List of Variables/Type of Variables ID – Respondent Identification Number /Ordinal BDM1LF – the legal form of the business/Nominal BDM2TO – the type of ownership/Nominal BDM3IS – firm initial size/Ordinal BDM4CS – current firm size/Ordinal BDM5CP – respondent current position/Nominal BDM6YC – the year of creation/Ordinal BDM7FA – the firm age/Ordinal BDM8SB – the sector of the business/Nominal BDM9TB – the type of business/Nominal BDM10GL – the geographical location/Nominal BDM11MA – market area of the business/Nominal BDM12GO – the gender of the owner/Nominal BDM13AO – the age of the owner/Ordinal BMD14NO – the nationality of the owner/Nominal BDM15EO – the ethnicity of the owner/Nominal BDM16BO – years of business ownership/Ordinal BDM17AS – annual sales or turnover/Ordinal BDM18BEm – business experience manager/Nominal BDM18BEl – business experience leader/Nominal BDM18Bes – business experience sector/Nominal

376

BDM1 - BDM18

EE1EB – educational background/Nominal EE2ST – studies/Nominal EEC3b – entrepreneurship courses before business start/Nominal EEC3a – entrepreneurship courses after starting business/Nominal EEC4 – entrepreneurship competences/Nominal EE5TL – type of learner/Nominal EE6LN – learning needs/Nominal EE7I – interactive learner/Nominal EE7N – networking learner/Nominal EE8EE – entrepreneurship experience/Nominal EE9BK – acquired business knowledge/Nominal EE10N – the usage of networking/Nominal EE11K – the type of knowledge acquired/Nominal EE12L – learn from information, communication, participation and sharing/Nominal EE13T – the usage of new emerging technologies and ICT/Nominal EE14Pffl – flexible formal learning/Scale EE14Pfil – flexible informal learning/Scale EE14Pebl – experienced-based learning/Scale EE14Prml – role model-based learning/Scale EE15SEL – satisfied with entrepreneurial learning/Ordinal WW15UEL – unsatisfied with entrepreneurial learning/Ordinal EE16aWE – define women entrepreneurship/Nominal EE16bWE – define women entrepreneurs/Nominal NET1AT – attending courses/Scale NET1LYH – learning yourself at home/Scale NET1LG – learning in groups/Scale NET1LOL – learning online/Scale NET1LICT – learning with ICT/Scale NET1BICT – doing business with ICT/Scale NET2YT – learning with YouTube/Nominal NET2YM – learning with Yahoo Messenger/Nominal NET2FB – learning on Facebook/Nominal NET2G – learning with Google/Nominal NET2OSN – learning with other social networking/Nominal NET2PCG – playing computer games/Nominal NET2LMB – learning with mobile phones/Nominal NET2HIL – home internet connection for learning/Nominal NET2WCL – wireless connection for learning/Nominal NET2TW – Twitter for learning/Nominal NET2VLL – virtual lectures for learning/Nominal

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NET2VNR – virtual class in non real time/Nominal NET2NONE – none/Nominal NET3MPB – mobile phones usage for business/Nominal NET3MIB – mobile internet usage for business/Nominal NET3FBB – Facebook usage for business/Nominal NET3GB – Google usage for business/Nominal NET3OSNB – other social network usage for business/Nominal NET3GSB – Google search for business/Nominal NET3MAB – mobile application usage for business/Nominal NET3IHB – internet at home usage for business/Nominal NET3IF – internet Forums/Nominal NET3TWB – Twitter usage for business/Nominal NET3YTB – You Tube usage for business/Nominal NET4STL – satisfied with ICT and NET for learning/Ordinal NET4UTL - unsatisfied with ICT and NET for learning/Ordinal NET5STB - satisfied with ICT and NET for business/Ordinal NET5UTB - unsatisfied with ICT and NET for business/Ordinal NCoP1CP – Communities of Practice/Nominal NCoP1BA – Business Associations/Nominal NCoP1PA – Professional Associations/Nominal NCoP1NG – networking groups/Nominal NCoP1O – other/Nominal NCoP2GA – groups and associations/Nominal NCoP3TP – type of participation to communicate/Nominal NCoP4PK – participation in CoPs increases knowledge/Scale NCoP4LE – CoPs facilitates learning from experts/Scale NCoP4IGB – in CoPs I find information to grow the business/Scale NCoP4SK – in CoPs I share knowledge/Scale NCoP4ES – through CoPs I am encouraged to succeed/Scale NCoP4SI – CoPs gives me a sense of identity/Scale NCoP4BS – CoPs are important for business success/Scale NCoP5TH – NET help my participation in CoPs/Nominal NCoP5NH – NET do not help my participation in CoPs/Nominal NCoP6L – laptops, computers, help my participation in CoPs/Nominal NCoP6M – mobile phones help my participation in CoPs/Nominal NCoP6T – iPad, tablets help my participation in CoPs/Nominal NCoP6YM – Yahoo Messenger help my participation in CoPs/Nominal NCoP6F – Facebook helps my participation in CoPs/Nominal NCoP6TW – Twitter helps my participation in CoPs/Nominal NCoP6SKY – Skype helps me to participate in CoPs/Nominal

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NCoP6O – other helps me to participate in CoPs/Nominal NCoP6N – None/Nominal WESG1S – increase in Sales/Turnover/Nominal WESG2NE – increase in number of employees/Nominal WESG3FMS – financial measures for business success/Nominal WESG4NFS – non financial measures determine business success/Nominal WESG5EE – entrepreneurship education/Scale WESG5NET – new emerging technologies/Scale WESG5NCP – networking and CoPs/Scale WESG5TW – Twitter/Scale WESG5FB – Facebook/Scale WESG5INT – Internet/Scale WESG5LC – laptops/computers/Scale WESG5MP – mobile phones/Scale WESG5TB – tablets/Scale WESG6ES – entrepreneurship education enhances business success/Nominal WESG6RES – reasons for entrepreneurship education enhancing business success/Nominal WESG7IBS – new emerging technologies increase business success/Nominal WESG8BT – business and entrepreneurial learning increase business success/Nominal WESG9WS – define women entrepreneurs’ success/Nominal WESG10RL – recent entrepreneurial learning/Nominal WESG11TL – types of learning used to enhance success/Nominal WESG12EE – recommendations regarding entrepreneurship education, to achieve success/Nominal WESG13E – I enjoy being a woman entrepreneur/Nominal WESG14RE – the reason of enjoyment/Nominal B. The Coding Frame (for open questions) Question B6): ‘Please state your learning needs’ Categories of answers: 1 Social media and ICT 2 Bookkeeping and Accounting 3 Finance 4 Marketing, Sales, Promotion 5 Legislation 6 Creativeness and Continual Professional Development (CPD) 7 None/NA (Filter question) 9 Miscellaneous 99 Don’t Know 999 No answer

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Question B16 a): ‘How would you define in your own words the following terms: Women Entrepreneurship is......................................................................................’ Categories of answers: 1 independent, creative and innovative process 2 hardworking and multitasking processes 3 passion, satisfaction, enjoyment and financial reward 4 setting, developing business and looking out for opportunities 5 learning, adapting quickly and developing your skills to achieve success 6 determination, motivation and leadership 7 flexible, being able to manage business and family 8 serving others and the community 9 miscellaneous 99 don’ know/ non-gender opinion 999 no answer Question B16 b): ‘How would you define in your own words the following terms: Women Entrepreneurs are........................................................................................’ Categories of answers: 1 positive, passionate, strong, driven, motivated, determined 2 courageous, brave, resilient, powerful, tenacious, confident 3 independent, flexible, creative 4 hard workers, multitaskers 5 sociable, friendly, considered 6 business people, gender immaterial 7 ready to learn all the time 9 miscellaneous 99 none/don’t Know 999 no answer Question D2: ‘Could you please state the name of the Group/Association? Categories of Answers: 1 Market Association 2 Handbags and Briefcases 3 ICAEW, ACCA, CIMA 4 Chamber of Commerce 5 Small Business Federation 6 High Street Traders 7 Facebook, Twitter, Instagram Groups 8 Women in Business Penarth 10 Hairdressing Association 11 British Florist Association 9 Miscellaneous 99 None/N/A

380

999 No answer Question E6 b): ‘Why do you think Entrepreneurship Education is enhancing business success?’ Categories of Answers: 1 It gives confidence, information and knowledge about the business 2 It encourages young business people to succeed 3 It supports ideas sharing and develops skills 4 It helps developing contacts and networks 5 Business is ongoing learning process 9 Miscellaneous 99 None/N/A 999 No answer Question E9: ‘How would you define women entrepreneurs’ success?’ Categories of Answers: 1 being independent and achieving a dream 2 being financially stable 3 making money and having a profitable business 4 work satisfaction and balance 5 survival 6 the ability to manage business and family successfully 7 business growth 8 having happy customers and customers’ satisfaction 9 miscellaneous 999 no answer Question E14: ‘Please explain why do you enjoy being a woman entrepreneur?’ Categories of Answers: 1 having a good relationship with the customers 2 I like meeting people and networking 3 I have a sense of achievement 4 I have freedom, independence and I am my own boss 5 I learned more 6 I am satisfied, with a sense of achievement, happy and content 7 I work flexible, around my family 8 I am equal to men 9 Miscellaneous 99 None/ N/A 999 No answer

381

Codebook for entrprsurvey.sav C. THE CODING BOOK (the text of the original questionnaire together with numerical value allocated to every answer category) Description of variable

SPSS variable name

Coding Instructions

Section A: Background and demographic data Question 1: What is the legal form of your business? The legal form of the business

BDM1LF

1= public company 2= private company 3= community interest company 4= family business 5= sole trader 6= multiple selections

Question 2: Please state the type of ownership for your business: The type of ownership

BDM2TO

1= single owner 2= partnership female/male 3= partnership female/female 4= partnership wife/husband 5= multi partners/others

Question 3: Please indicate the firm size: (initial number of employees at the creation) Firm initial size

BDM3IS

1= ‘0-9 employees’ 2= ’10-49 employees’ 3= ’50-249 employees’

Question 4: Please indicate the firm size: (current number of employees at the creation) Firm current size

BDM4CS

1= ‘0-9 employees’ 2= ’10-49 employees’ 3= ’50-249 employees’

Question 5: What is your current position in the firm? Respondent current position

BDM5CP

1= owner 2= partner 3= owner/director 4= other

Question 6: Please indicate the year of creation The year of creation

BDM6YC

1= before 1970 2= 1971-1980 3= 1981-1990 4= 1991-2000 5= after 2000

382

Question 7: What is the firm age? (Number of years in operation) The firm age

BDM7FA

1= less than 1 year 2= at least 1 but less than 3 3= at least 3 but less than 5 4= at least 5 but less than 10 5= at least 10 but less than 20 6= 20 years or more

Question 8: Please indicate the sector of your business. The sector of the business

BDM8SB

1= Manufacturing 2= Whole Sales and Retails 3= Health/Social Services 4= Agriculture 5= Services/Accommodation/Cafes/Rest 6= Construction/Transport/Storage 7= IT/Finance/Insurance 8= Multiple selections

Question 9: What type of business do you have? The type of business

BDM9TB

1= Manufacturing 2= Retails 3= IT/Property 4= HR/Personnel 5= Promotion/Publicity 6= Consulting 7= Building and Construction 8= Catering/Hotels 9= Beauty/Hairdressing 10= Health/Nutrition/Physiotherapy/Sport 11= Training/Education 12= Accounting/Finances 13= Arts/Craft/Fashion Design 14= Charity/Community Service 15= Social Care/Cleaning 16= Services 17= Food/Hygiene 18= Cosmetics/Perfumes 19= Jewellery 20= Others 21= Multiple selections

383

Question 10: Where is the geographical location of your business? The geographical location

BDM10GL

1= Wales 2= England 3= United Kingdom

Question 11: How wide is the area of your business? Market area of the business

BDM11MA

1= Local 2= Regional 3= National 4= Online National 5= International 6= Online International

Question 12: Gender of the owner/owners of the business: The gender of the owner

BDM12GO

1= Female 2= Male & Female 3= Female & Female 4= Others

Question 13: What is the age of the owner? Age group The age of the owner

BDM13AO

1= 19-25 2= 26-30 3= 31-40 4= 41-50 5= 51-60 6= 61 or over

Question 14: What is the nationality of the owner? The nationality of the owner

BDM14NO

1= Welsh 2= English 3= British 4= Other

Question 15: What is the ethnicity of the owner? The ethnicity of the owner

BDM15EO

1= White British 2= White Welsh/English 3= Indian/Bangladesh/Pakistani/Chinese 4= Black British 5= White European 6= Other

384

Question 16: How many years have you been the owner of the business? Years of business ownership

BDM16BO

1= 0-5 2= 6-10 3= 11-20 4= More than 20

Question 17: Please state the current annual sales/turnover figures of your business (as per financial year) Annual sales/turnover

BDM17AS

1= From 1 to 100,000 2= From 101,000 to 500,000 3= From 501,000 to 1,000,000 4= From 1,001,000 to 5,000,000 5= Over 5,000,000 6= the respondent didnâ&#x20AC;&#x2122;t want to say

Question 18: Previous experience as a manager/leader: Business Experience

BDM18BEm

0= Y (Yes);

1= N (No)

BDM18BEl

0= Y

1= N

BDM18BEs

0= Y

1= N

999= Missing answer

Section B: ENTREPRENEURSHIP EDUCATION Description of variable

SPSS variable name

Coding Instructions

Question 1: What is your educational background? Educational Background

EE1EB

1= GCSE/High School 2= A Level/College 3= Graduate 4= Postgraduate 5= Vocational/Professional 6= Other

Question 2: Which of the following studies did you undertake? Studies

EE2ST

1= Business/Management 2= Accounting/Finances 3= Marketing 4= Entrepreneurship 5= Technology/IT 6= Others 7= None

385

Question 3: Did you undertake Entrepreneurship courses/training? Entrepreneurship Courses (before/after starting business)

EEC3b

0=Yes

1=No

EEC3a

0=Yes

1=No

Question 4: What entrepreneurship skills/competences do you have? Entrepreneurship competences

EEC4

1= Management 2= Finances (Budget/Cash Flow) 3= Sales/Negotiating 4= Marketing/Promotion/Advertising 5= ICT 6= Accounting 7=Facebook, Twitter, Blogs, LinkedIn 8= Multiple selections 10= All

Question 5: How would you describe yourself as a learner? Type of Learner EE5TL

1= Formal learner 2= Informal learner 3= Doing/Asking/Applying learner 4= Experienced-based learner 5= Observational/role-model based learner 6= Multiple answers 7= All

Question 6: Please state what are your business learning needs? Business learning needs

EE6LN

1= Social Media/ICT 2= Bookkeeping/Accounting 3= Finances 4= Marketing, Sales, Promotion 5= Legislation

6= Creativeness, Continuing Professional Development 7= None/ N/A (filter question) 9= Miscellaneous 99= Donâ&#x20AC;&#x2122;t Know 999= No answer Question 7: How would you describe yourself? Learner (Interactive/networking)

EE7I

0=Yes; 1=No; 2= N/A

EE7N

0=Yes; 1=No; 2=N/A

386

Question 8: According to your opinion, before starting your current business, did you have experience/knowledge in one of the following: finance, marketing, sales, management, negotiating and networking? Entrepreneurship experience

EE8EE

0=Yes 1= No 2= Some Knowledge

Question 9: After starting the business did you acquire this business knowledge? Acquire business knowledge

EE9BK

0=Yes 1= No 2= Some Knowledge

Question 10: Please state if you use networking (filter question) Note: a) If ‘Yes’, go to Q11 and Q12. If ‘No’ go to Q13. Use of networking

EE10N

0=Yes; 1=No

Question 11: If you use networking, what type of knowledge do you need to acquire? The type of knowledge acquired

EE11K

1= Social 2= Professional 3= Business 4= Other 5= Social + Business 6= All 7= N/A, filter question

Question 12: If you use networking, please indicate if you learn form information, communication, participation and sharing. Learn from information, communication, participation and sharing EE12L

0=Yes; 1=No; 2=N/A; 999= Missing answer

Question 13: Please indicate if you use ICT and new emerging technologies when learning (computer, mobile phone, Twitter, Blogs, Websites, and Blackboard). Use of new emerging technologies and ICT EE13T

0=Yes; 1=No

Question 14: Learning Preferences Flexible formal learning

EE14Pffl

0= Strongly Disagree 1= Disagree 2= Neither 3= Agree

387

4= Strongly Agree 999=Missing answer Flexible informal learning

EE14Pfil

0= Strongly Disagree 1= Disagree 2= Neither 3= Agree 4= Strongly Agree 999=Missing answer

Experienced-based learning EE14Pebl

0= Strongly Disagree 1= Disagree 2= Neither 3= Agree 4= Strongly Agree 999=Missing answer

Role model-based learning

EE14Prml

0= Strongly Disagree 1= Disagree 2= Neither 3= Agree 4= Strongly Agree 999=Missing answer

Question 15: What is your satisfaction with learning (your business and entrepreneurship learning since you started the business)? Satisfied with entrepreneurial learning EE15SEL

0= Strongly Disagree 1= Disagree 2= Neither 3= Agree 4= Strongly Agree 999=Missing answer

Unsatisfied with entrepreneurial learning

EE15UEL

0= Strongly Disagree 1= Disagree 2= Neither 3= Agree 4= Strongly Agree 999=Missing answer

Question 16a): How would you define in your own words the following terms: Women Entrepreneurship is....................................................................................? Define Women Entrepreneurship

EE16aWE

1= independent, creative, innovative process 2= hardworking, multitasking process

388

3= passion, satisfaction, enjoyment, financial reward 4= setting, developing business and looking out for opportunities 5= learning, adapting quickly and developing your skills to achieve

success

6= determination, motivation and leadership 7= flexible, being able to manage business and family 8= serving others and community 9= Miscellaneous 10= Life style 99= Donâ&#x20AC;&#x2122;t Know/Non-gender opinion 999= No answer Question 16b): How would you define in your own words the following terms: Women Entrepreneurs are.......................................................................................? Define Women Entrepreneurs

EE16bWE

1= positive, passionate, strong, driven, motivated, determined 2= courageous, brave, resilient, powerful, tenacious, confident 3= independent, flexible, creative 4= hard workers, multitaskers 5= sociable, friendly, considered 6= business people, leaders, gender is immaterial 7= ready to learn all the time 8= Networking people 9= Miscellaneous 99= None/Donâ&#x20AC;&#x2122;t Know 999= No answer Section C: NEW EMERGING TECHNOLOGIES Description of variable

SPSS variable name

Coding Instructions

Question 1: How often do you do the following? Attending courses

NET1AT

4= Very often 3= Often 2= Neither 1= Not often 0= Never

Learning yourself at home

NET1LYH

4= Very often 3= Often 2= Neither 1= Not often 0= Never

389

Learning in groups

NET1LG

4= Very often 3= Often 2= Neither 1= Not often 0= Never

Learning online

NET1LOL

4= Very often 3= Often 2= Neither 1= Not often 0= Never

Learning with ICT

NET1LICT

4= Very often 3= Often 2= Neither 1= Not often 0= Never

Doing business with ICT

NET1BICT

4= Very often 3= Often 2= Neither 1= Not often 0= Never

Question 2: Which of the following are you using for learning? Learning with You Tube

NET2YT

0=Yes, 1=No

Learning with Yahoo Messenger

NET2YM

0=Yes, 1=No

Learning on Facebook

NET2FB

0=Yes, 1=No

Learning with Google+

NET3G

0=Yes, 1=No

Learning with other social networking

NET2OSN

0=Yes, 1=No

Playing computer games

NET2PCG

0=Yes, 1=No

Learning with mobile phones

NET2LMB

0=Yes, 1=No

Home Internet connection for learning

NET2HIL

0=Yes, 1=No

Wireless connection for learning

NET2WCL

0=Yes, 1=No

Twitter for learning

NET2TW

0=Yes, 1=No

Virtual lectures for learning

NET2VLL

0=Yes, 1=No

Virtual class in non-real time

NET2VN

0=Yes, 1=No

None

NET2NONE

0=Yes, 1=No

390

Question 3: Which of the following do you use for business? Mobile phones usage for business NET3MPB

0=Yes, 1=No

Mobile internet usage for business NET3MIB

0=Yes, 1=No

Facebook usage for business

NET3FBB

0=Yes, 1=No

Google usage for business

NET3GB

0=Yes, 1=No

Other social network for business

NET3OSNB

0=Yes, 1=No

Google search for business

NET3GSB

0=Yes, 1=No

Mobile applications usage

NET3MAB

0=Yes, 1=No

Internet at home usage for business NET3IHB

0=Yes, 1=No

Internet Forum

NET3IF

0=Yes, 1=No

Twitter usage for business

NET3TWB

0=Yes, 1=No

You Tube usage for business

NET3YTB

0=Yes, 1=No

Question 4: How satisfied are you with the use of the above (Q2) for the studies? Satisfied with ICT and NET for learning

NET4STL

0=Strongly Disagree 1= Disagree 2= Neither 3= Agree 4= Strongly Agree

Unsatisfied with ICT and NET for learning

NET4UTL

0=Strongly Disagree 1= Disagree 2= Neither 3= Agree 4= Strongly Agree

Question 5: How satisfied are you with the use of the above (Q3) for the business? Satisfied with ICT and NET for business NET5STB

0=Strongly Disagree 1= Disagree 2= Neither 3= Agree 4= Strongly Agree

Unsatisfied with ICT and NET for business NET5UTB

0= Strongly Disagree 1= Disagree 2= Neither 3= Agree 4= Strongly Agree

391

Section D: NETWORKING/COMMUNITIES OF PARCTICE (CoPs) Description of variable

SPSS variable name

Coding Instructions

Question 1: Do you belong to a group/network where you share knowledge and experience with others in the same filed? Communities of Practice

NCoP1CP

0=Yes, 1=No, 2=N/A

Business Associations

NCoP1BA

0=Yes, 1=No, 2=N/A

Professional Associations

NCoP1PA

0=Yes, 1=No, 2=N/A

Networking Groups

NCoP1NG

0=Yes, 1=No, 2=N/A

Other

NCoP1O

0=Yes, 1=No, 2=N/A

Question 2: Could you please state the name of that Group/Association? Groups and Associations

NCoP2GA 1= Market Association 2= Handbags and Briefcases 3= ICAEW, ACCA, CIMA 4= Chamber of Commerce 5= Small Business Federation 6= High Street Traders 7= Facebook, Twitter, Instagram Groups 8= Women in Business Penarth 10= Hairdressing Association 11= British Florist Association 9= Miscellaneous 99= None/ N/A 999= No answer

Question 3: What type of participation are you using to communicate with other members? Type of participation to communicate

NCoP3TP 1=Face to face 2=Online 3=Other 4=Face to face and online 5= N/A

Question 4: Please state your agreement with the following statements: Participation in CoPs increases knowledge NCoP4PK

0= Strongly Disagree 1= Disagree 2= Agree 3=Strongly Agree 4= N/A, 999= Missing answer

392

CoPs facilitate learning from experts NCoP4LE

0= Strongly Disagree 1= Disagree 2= Agree 3=Strongly Agree 4= N/A, 999= Missing answer

In CoPs I find information to grow the business NCoP4IGB

0= Strongly Disagree 1= Disagree 2= Agree 3=Strongly Agree 4= N/A, 999= Missing answer

In CoPs I share knowledge NCoP4SK

0= Strongly Disagree 1= Disagree 2= Agree 3=Strongly Agree 4= N/A, 999= Missing answer

Through CoPs I am encouraged to succeed NCoP4ES

0= Strongly Disagree 1= Disagree 2= Agree 3=Strongly Agree 4= N/A 999= Missing answer

CoPs give me a sense of identity NCoP4SI

0= Strongly Disagree 1= Disagree 2= Agree 3=Strongly Agree 4= N/A, 999= Missing answer

CoPs are important for business success NCoP4BS

0= Strongly Disagree 1= Disagree

393

2= Agree 3=Strongly Agree 4= N/A 999= Missing answer Question 5: Please state if the following statement is true or false: NET helps my participation in CoPs

NCoP5TH

NET do not help my participation in CoPs NCoP5TNH

1=False, 2=True, 3=N/A 1=False, 2=True, 3=N/A

Question 6: The following new emerging technologies help me to participate in CoPs: Laptop, computer help participation in CoPs NCoP6L

1=Yes, 2=No, 3=N/A

Mobile phones help my participation in CoPs

1=Yes, 2=No, 3=N/A

iPad, tablet, help my participation in CoPs

NCoP6M

NCoP6T

1=Yes, 2=No, 3=N/A

Yahoo Messenger helps my participation in CoPs, NCoP6YM 1=Yes, 2=No, 3=N/A Facebook helps me to participate in CoPs

NCoP6F

1=Yes, 2=No, 3=N/A

Twitter helps me to participate in CoPs

NCoP6N

1=Yes, 2=No, 3=N/A

Skype helps me to participate in CoPs

NCoP6SKY

1=Yes, 2=No, 3=N/A

Other helps me too participate in CoPs

NCoP6O

1=Yes, 2=No, 3=N/A

None

NCoP6N

1=Yes, 2=No, 3=N/A

Section E: WOMEN ENTREPRENEURSâ&#x20AC;&#x2122; SUCCESS Description of the variable

SPSS variable name

Coding Instructions

Question 1: In the last five years did your business registered an increase in sales/turnover? Increase in Sales/Turnover

WESG1S

1=Yes; 2=No

Question 2: In the last five years did your business increase the numbers of employees? Increase in number of employees

WESG2NE

1=Yes; 2=No; 3= N/A

Question 3: Which of the following financial measures would you describe as measures for business success? Financial measures for business success

WESG3FMS 1= Increasing in Sales 2= Increase in Profit 3= the both of them 999= Missing answer

Question 4: Which of the following non-financial measures would you describe as determinants for business growth and success? Non financial measures determine business success 1=Enterprise culture 2=Innovation

394

WESG4NFS

3=Usage of ICT and Globalization 4=Entrepreneurial Knowledge 5=New Emerging Technologies (Facebook, Twitter, etc) 6=Entrepreneurial Education 7=Networking and CoPs 8=Effective Website 9=Larger product range 10=Quality of product/services 11=Customer loyalty and satisfaction 12=Brand recognition 13=Niche market 14=Increase in number of employees 15=Social recognition 16=Survival 17=Multiple selections 18=All Question 5: On a scale from 1 to 5 please rate your opinion regarding the impact of the following factors for business success: Entrepreneurship Education

WESG5EE

1=’low’, 5=’high’

New Emerging Technologies

WESG5NET

1=’low’, 5=’high’

Networking and CoPs

WESG5NCP

1=’low’, 5=’high’

Twitter

WESG5TW

1=’low’, 5=’high’

Facebook

WESG5FB

1=’low’, 5=’high’

Internet

WESG5INT

1=’low’, 5=’high’

Laptops/computers

WESG5LC

1=’low’, 5=’high’

Mobile Phones

WESH5MP

1=’low’, 5=’high’

Tablets

WESG5TB

1=’low’, 5=’high’ 999=Missing answer

Question 6: Do you think Entrepreneurship Education is enhancing business success? Entrepreneurship Education enhances business success WESG6ES

1=Yes, 2=No, 999= Missing answer

Reasons for Entrepreneurship Education enhancing business success WESG6RES 1=it gives confidence, information, knowledge 2=encourage young people to succeed 3=supports ideas sharing and skills development 4=it helps with contacts and networking development 5=business is ongoing learning process

395

9=Miscellaneous 99=None, N/A 999=No answer Question 7: Please state whether by using new emerging technologies, you increased the success of your business? New Emerging Technologies increase business success WESG7IBS

1=Yes, 2=No

Question 8: Please indicate whether by undertaking business and entrepreneurial training you increased the business success? Business and entrepreneurial training increase business success WESG8BT

1=Yes, 2=No

Question 9: How would you define women entrepreneurs’ success? Define women entrepreneurs’ success WESG9WS 1= being independent, achieving a dream 2= being financially stable and having a profitable business 3= work satisfaction and balance 4= survival 5= ability to manage business and family successfully 6= business growth 7= having happy customers and customers’ satisfaction 10=profit and job satisfaction 11=uniqueness and innovation 12=being role model 9= Miscellaneous 999= No answer 8=No different to that of a man Question 10: Please indicate your recent entrepreneurial learning: Recent entrepreneurial learning WESG10RL 1= Management 2= Leadership 3= Networking 4= ICT & Globalization 5= Entrepreneurial Skills 6= Economics 7= Legislation 8= Finances and Accounting 9= Interpersonal Skills 10= Human Resources 11= Marketing, Promotion

396

12= Sales, Negotiation 13 =Floristry 99= None Question 11: Which of the following types of learning did you use to enhance the success of your learning? Types of learning used to enhance success WESG11TL 1= Traditional (class-based) 2= Blended (traditional and online) 3= Online 4= Distance learning 5= E-learning 6= Networking through facebook, twitter, LinkedIn 7= None 8=More than two types of learning 999=Missing answer Question 12: What would you recommend to others to do regarding the entrepreneurship education in view to achieve success? Recommendations regarding entrepreneurship education to achieve success WESG12EE 1= Continue to learn 2= Learn from the experience of others 3= Learn from own experience 4= Undertake more entrepreneurship education 5= Adhere to professional bodies 6= Networking 7=Multiple selections 10= All Question 13: Do you enjoy being a woman entrepreneur? I enjoy being a woman entrepreneur WESG13E

1=Yes, 2=No

Question 14: Please explain why? The reason of enjoyment WESG14RE 1= having a good relationship with customers 2= I like meeting people and networking 3= I have a sense of achievement 4= I have freedom, independence and I am my own boss 5= I learned more 6= I am satisfied, have achievement, happiness and content

397

7= I work flexible around my family 8= I am equal with men 9= Miscellaneous 99= None/ N/A 999= No answer

398

Selected Answers: Section B, Question 6: Please state your learning needs. Respondent 130: Information Communication Technology, Computers. Respondent 140: Marketing, Bookkeeping, Growing the business. Respondent 110: ICT, Social Media: Facebook, Twitter. Respondent 128: Marketing and Sales. Respondent 122: Legislation and Patents. Respondent 104: Finance Respondent 78: Practical skills specific to ceramic. Respondent 85: Social Media, Instagram Respondent 80: Finances and Management Respondent 79: ICT, Promotion Respondent 92: Creativeness, arts, skills specific to my activity Respondent 93: Beauty and Holistic Respondent 40: Financial Planning Respondent 41: Buying, Event Management Respondent 55: Cooking and baking Respondent 6: Updates on taxes Section B, Question 16a): How would you define in your own words the following term: â&#x20AC;&#x2DC;Women Entrepreneurshipâ&#x20AC;&#x2122;? Respondent 1: Probably more intuitive, possibly less bold. Respondent 3: It is a life style. Respondent 4: The same as male entrepreneur Respondent 5: Is having the courage and commitment to create your own business, your own way Respondent 7: Running her own business and looking out for new opportunities Respondent 19: Learning, adapting quickly to achieve a positive end. Respondent 21: Difficult, having to juggle between family and business Respondent 13: Communication skills Respondent 38: Creating strong working relationship with customers Respondent 34: Innovation Respondent 25: It is run and organised by men. It is a male dominated sector. Respondent 49: Hard work, determination and leadership. Respondent 63: Giving women flexibility to arrange their lives in the way they want Respondent 68: Setting your own business and having your own ideas Respondent 69: Challenging and rewarding Respondent 78: An opportunity, ability of women to compete in the market place Respondent 70: Women leading in business Respondent 82: For me as an artist is a sharing process, to show something, to express and to teach Respondent 83: It is a strong belief in the idea and the conviction and passion to pursue it. Respondent 89: Striving and confirming what we learned.

399

Respondent 104: Creating, designing, managing and providing a service Respondent 109: Leadership and communication Respondents 110: Creativity, satisfaction and balance Respondent 112: It is ‘achieving’, as some people won’t speak to me as a ‘woman’. Respondent 113: It is a passion, knowing to treat people Respondent 118: Chasing the dream. It is a multitasking process, juggling between business and home. Respondent 122: It is a rewarding financial process of helping and giving back to the community Respondent 131: Knitting and selling wool garment Section B, Question 16b): How would you define in your own words the following term: ‘Women Entrepreneurs’? Respondent 1: Possibly more risk averse. Respondent 2: Are determined risk takers. Respondent 5: Hardworking, creative, courageous and resilient Respondent 7: Flexible, ready to learn at all the time Respondent 10: Fantastic role models Respondent 14: Positive, strong, determined Respondent 15: Business people, gender is immaterial Respondent 21: Inspiring, hardworking, showing that if you want to do, you can do it Respondent 28: Incredible creative, practical and resilient Respondent 46: Unique. Not so greedy Respondent 50: Managers and leaders Respondent 55: Sociable, strong and determined Respondent 60: Multitaskers, doers Respondent 119: Flexible, independent, with people skills, interpersonal skills Respondent 131: Artistic and passionate Respondent 140: Innovators Section D, Question 2: Could you please state the name of the Group/Association? Respondent 2: Connect Networking in Bristol Respondent 3: 4 Networking Respondent 10: Women International Business Network (WIBN), Chamber of Commerce, 4 Networking Respondent 14: Dottie Ladies Club Respondent 18: Hair Dressing Association Respondent 22: Community Association with other shops Respondent 38: British Florists Association Respondent 65: British Women Penarth Respondent 49: Interflora Respondent 46: Small Business Federation Respondent 73: National Training Federation for Wales Respondent 78: Ceramic Owners Association Respondent 93: Federation of Holistic Therapist

400

Respondent 114: High Street Traders Respondent 132: Market Federation Committee Respondent 129: The Jewellery Society Respondent 143: Wales Craft Council Respondent 140: Artfinder Respondent 139: Welsh Women Enterprise Group Section E, Question 6b): Why do you think Entrepreneurship Education is enhancing business success? Respondent 1: It gives confidence and financial knowledge Respondent 4: Knowledge is Power Respondent 14: You think outside of the box. Respondent 18: Gaining more knowledge about the business Respondent 20: The more you learn, the more you pass on the profit Respondent 26: It confirms idea and progress the business Respondent 41: To share ideas, develop skills and implement them Respondent 47: You learn all the time [in order to] moving forward Respondent 66: People are more aware of their skills and the areas they need to improve Respondent 79: It gives access to training and information Respondent 103: Knowledge, information and skills Respondent 133: It gives information to compete Respondent 115: It encourages networking and new ideas Respondent 143: Learning is an ongoing process Section E, Question 9: How would you define women entrepreneurs’ success? Respondent 1: It is not different to that of a man Respondent 7: Having a regular flow of customers, having a profitable business that she can run around the family Respondent 2: Increased profit, turnover and job satisfaction Respondent 11: Independent women being the ‘bread winner’ Respondent 12: Satisfaction Respondent 14: To be totally content with all aspects of life and business Respondent 49: Being financially stable, doing something extraordinary and love doing it Respondent 40: Profit, knowledge, social life, wealth Respondent 47: Personal survival for you and family Respondent 53: Achieving sufficient profit to allow you a good income and being respected for what you do Respondent 55: Having money, satisfaction and customers which are happy with the product Respondent 61: Life work balance Respondent 62: Freedom to be my own boss Respondent 68: Income and independence Respondent 75: Surviving Respondent 81: Customer satisfaction and loyalty

401

Respondent 87: Good customer service Respondent 110: Achievement of a dream Respondent 104: Creative fulfilment Respondent 106: Good financial situation Respondent 126: Recognition Respondent 141: Business growth Section E, Question 14: Please explain why do you enjoy being a woman entrepreneur? Respondent 2: I can make my own decisions Respondent 6: It fulfils my needs and wants and makes me feel empowered. Respondent 7: I have learned more than I did in two university degree. I can do all from home and around my childrenâ&#x20AC;&#x2122;s needs Respondent 8: I enjoy leading and expanding the business. The ultimate reward is customer satisfaction. Respondent 12: I like people Respondent 15: I have satisfaction and achievement Respondent 16: I work flexible around my children Respondent 22: I am my own boss Respondent 26: It is rewarding Respondent 28: I have large autonomy and responsibility Respondent 29: I have freedom Respondent 50: The satisfaction of being my own boss Respondent 87: Because we are now equal to men Respondent 90: I enjoy meeting people Respondent 96: I have control of my own working life Respondent 98: I am my own boss and I can help others Respondent 117: It enables me to be independent Respondent 119: I have a flexible life Respondent 138: I have a sense of self achievement Respondent 139: I am working for myself Respondent 140: I create a destiny and an opportunity

402

APPENDIX D: INTERVIEWS’ TRANSCRIPTS INTERVIEW WITH PARTICIPANT FOUR - TRANSCRIPT R: Researcher P4: Participant Four Introduction R: This research is entitled “The Impact of Entrepreneurship Education and New Emerging Technologies on Women Entrepreneurs’ Success”. R: Please speak about yourself; about your business educational background and the type of activities are you doing on a daily basis. P4: My business education was not a great deal, other than in my first job I went to study once per week the HND (High National Diploma) in Business and Finance. That was back in 1995 and then I worked admin for I suppose the next fifteen plus years, until I decided to buy this established business and here I am. So, business is retails, selling fabrics and haberdashery, so, on a daily basis that is basically what I do. It is about managing the shop, selling to the public, buying my stock and starting to get myself up in running online. R: Could you tell me more how did you open your business? P4: I bought it as an established business, for example, it was running for thirty years, before I bought it and I bought the shop from a family member of my ex-husband because she was emigrating. I always wanted to start a business and never got around to find the right thing. So, I bought the business seven years ago, bought it cash, came in and I was behind the counter one week later. I bought a business I didn’t know nothing about sewing, the stock, I knew nothing, so I came in totally fresh, naive and innocent. R: What do you do every day, and how do you start your day? P4: I start my day, I come in and open. Usually I have people waiting for me, and it is just a question of serving, measuring fabrics. We taking sewing, alterations, it is just a matter of dealing with the customers. Sometimes, like now, I have got my phones, so I do my eBay and my Facebook page, whilst I am in the shop, I do that in between serving and that’s it, tiding up, ordering. That is taking most of my time, tiding and serving. R: How do you learn, what is the best method of learning for you, and what are your learning preferences? P4: I suppose I just learn as I go along, as far as this business is concerned, I learned from other people. My customers are a great deal because the nature of the business, also online I suppose I gain most of my knowledge. If it is not from the people that I serve it is from the information that I get online. Also, through Facebook and other people who are doing a similar kind of thing as me on the internet. R: Do you have some learning preferences? P4: Mm... Could you give me some more options, please? R: How would you like to learn and what is your method of learning, to acquire knowledge and information?

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P4: I learn best from watching other people do. I don’t know what kind of learner that makes me, but I learn best by example. Somebody will show me what to do, and gives me an example of what to do it is how I soak in and I learn it. This is my learning preference I suppose. R: Do you use information technology? P4: Yes, actually my abilities are quite limited. I need to get my children to help me, which is the sign of the time. But I do use eBay, Facebook, Twitter, Instagram. I just started my shop on Instagram now.

customer has been showed me setting my shop on Twitter. So I do use the emails obviously, instead, as a basic thing, but I do use Facebook and eBay. R: What is your preference, what is the best mean? P4: A... it is between eBay and Facebook, it has always been eBay. For me, the kind of business I am in, eBay it is a good one. I also tried on Amazon as well. I got some items on Amazon. Mm... , but I think now I am being pushed it into Facebook. Because of the fees it applies when you when you sell on eBay it can be extortionate. So, I am trying to concentrate on the Facebook site of things now. I try to set a shop on there. It is quite complex and you got to put certain links from one place to another, so I am having trouble with it, but I started with this now. So, Facebook is my preference. R: Do you use information technologies [you already answered part of this question] such as: Facebook, Twitter, Google, Smart Phone, Tablets, iPad, for your business or for your learning? P4: Mm... For my business yes, I do sell online, I am in contact with other sellers online. For example, a lot of my customers who come in, they make things, they post things of what they saw onto my page to help me promote what I have. I do all my orders online nowadays, all my suppliers are online, it supposes to go through a catalogues nowadays. They email you and show new staff. It is a big change in the last seven years. When I started nothing was online. Just about e-bay was going in the shop but now, everything is done via the media, on the internet. So, emailing, I don’t use the fax machine anymore, everything is emailed, and suppliers all emailed me everything. Now, selling is the big thing that is happening online. It is about catching up with that too. R: So, do you also use these for learning? (...) P4: Yes, not only for huge degree, but yeah, the only learning that I gain through it is picking up from other people I am friend with and they are doing similar things and from customers. That’s the only way I believe, but I am learning, so, picking up the skills, on selling online, that’s it. R: Are you satisfied with these for business and for learning? P4: Yes. What I am not satisfied with, is that I am not making the most of what is available, that is the annoying thing due to the time restraints I think. I am dissatisfied with myself, because I feel like the ability and the opportunity is there and I am not taking the full advantage of it, but I will. R: Did you say that the most accessed is Facebook or eBay? P4: I think is Facebook now. When I took over seven years ago, it was only eBay, in small amount of Amazon, but eBay. I don’t think Facebook was even known for the selling. Seven years ago, was up in

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running good and proper, but I don’t think that people were caught onto the fact that you could sell and networking via Facebook. But now, obviously the last two years, particular, everybody is catching up with selling on Facebook. I think Facebook it is a sort of overtaking the eBay slightly. It is in my domain anyway. R: What is your opinion regarding the role and the importance of these new emerging technologies for business success? Which of them are most effective? P4: As new technologies? R: Yes, technologies such as Facebook, Google, Yahoo Messenger, Mobile Technologies, Smart Phones, iPhones. P4: Oh my God, Smartphone in itself it is just a revelation, because you can do anything on your phone, right in your shop, in the middle of doing things, so I would even use my smart phone to announce a sale, because I had somebody to ask how to crochet for example. I would get on my phone, and I would show them Youtube, because sometimes some of my older customers, they are not afraid of the internet. So I could show them something on You Tube of how to do something, which would increase their likelihood of purchasing what I want them to purchase. So, for that reason Smart Phone is really, really clever. Similar with ribbon, a lady was in the other day, and she wanted to know to make a bow for a wedding and she wanted a lot of ribbon, but she was concerned because she needed that afternoon. So I got on my Phone, I put onto You Tube ‘How to make large bow tie’, she watched the tutorial on my phone, in my shop while I was cutting the ribbon, so that kind of thing. Also, I answer to my sales very often. I am very grateful because it is getting me a sale. The Smart Phone in itself it is just amazing, but also things like Facebook. Pinctoresc is another one. I don’t go there very often but, if somebody is looking for an idea, I allow the customer and have a look together. Instagram, I use them all, but only to a little degrees. But I would say, to me the Smart Phone is just amazing and Facebook too. R: Could you explain whether Entrepreneurship Education and New Emerging Technologies can help your business to grow, or to help you to succeed? P4: Yeah, (...) I suppose I already touched that, it can help your business to grow, but it also needs the person to take advantage of it. So, I suppose that the very fact that eBay is there and selling online, which is probably the reason for what small shop like this are in decline, because people are going online first informal. Without a doubt it is a huge thing, but it is a double edged sword because it needs the person behind it, to use what is available, I think. And if you do use it, there is a potential which disguise a limit, genuinely I do. R: Please state if you belong to any Group, Association and Network. P4: I don’t! I am not a lover of networking. When I was doing, I started off doing an MA in Female Entrepreneurship at the University, one thing that they did encourage was networking. I just, I am not a lover of networking at all. I am comfortable beyond my counter, I can deal with customers beautifully, but I don’t necessarily like to go outside of my comfort zone. I am not a member of any group and associations. Don’t ask me to network, I don’t like it.

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R: What is business/entrepreneurial success for you? How could you measure the success? What can you use to measure the success? How can you define this? P4: I suppose that can be queried, I suppose that initially, I would say when measuring one’s success, in entrepreneurship, I would sort of think financially, but I don’t think that is necessarily everything, although that’s lovely, and I did not achieve the goal financially, that I was hoping that I would, but you are running a small business and you are quite lucky nowadays make a tick over and pay the bills, never mind make a million. I just think that are other benefits such as the very fact that you are working for one self, you got flexibility. I am able to live by example to my children, as a parent it is very important being my own boss, and showing my children what is out there and what you are capable of doing I suppose. How else do I measure the success? Just being independent, I think, I have anybody to help me with anything. You got a sense of independence; (...) you actually achieve something, even though you don’t achieve full potential and your goals, you are achieving something by you know, by running your own business anyway. Even, if financially you are not exactly where you want to be. R: Can you please define women entrepreneurship? As a process, please. In the context of what you do in your shop, in your business, how would you define this process? P4: I don’t know. My mind is gone blank. I suppose it is a process, isn’t it? It is not a question of coming in and standing beyond the counter, and serving and getting your money back, is more to it, the fact that you are everything, so you are the cleaner, you place the orders, you pay the bills, you take the fluke when you can’t pay the bills, you serve the customers, you solve the problems you have and other responsibilities, and reap the rewards, I guess. Being an entrepreneur, isn’t all about is all about the big mix, is all that goes into it, and is quite confusing even for a small business, has got a lot of aspects to be a female entrepreneur, particularly for the problem we face as opposed to anybody else, as sex, we are also raising a family. I got this to organise and care for and also the family to organise and care, and it is a juggle. I don’t know if that is your question or not (...). R: How would you define women entrepreneurs? P4: As opposed to men? R: Either, or as a characteristic. P4: I would say that she would be independent, brave, flexible, resilient, because it is not as easy as you think, to be quite tough, (...) quite organised, you got to ‘take the rough with the smooth’ (...) you have to have quite a few traits of personality to be a female entrepreneur. R: How would you see business grow, or the process of growing your business? How would you define business growth? P4: I don’t know, because when I first started it was one thing that I was intended in doing, coming into this small shop and growing it, that was the one thing that I had in my mind. I was going then to open another shop, grow this, expand to another shop, take it online, and take it big. So, in my mind that is growth. That is what I yet have to achieve. Do I want now to open another shop? I do not know, I like to keep my growth as limited as I can, to be able to manage it. To me growth is not just standing still, doing

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the same thing day in, day out, it is a kind of branching off, doing different things (...) I think to grow you need to come out of comfort zone and push. Nowadays, in a shop like this, the only way to grow is to expand or go online in a ‘biggesh’ kind way. R: Do you enjoy being a woman entrepreneur? P4: Most days I do, yes, I would say, every January I hate it, I just wished I had a paid job I could have go to a steady salary, because January is really, really quiet. In the time of Christmas I love it, because it is so busy and the till is ringing and this is all about. But generally speaking I do enjoy it, whether I would encourage somebody else to do it in today climate, I don’t know, because it is really tough. But, I do enjoy it and it suits my style and my time of life, my family, it suits where I am at in my life, whether I would like to continue forever, I don’t know. I think there are pros and cons, but yeah, ultimately, if I have to answer I do enjoy it 95 per cent of the time. R: What other factors would affect business growth or success as a woman entrepreneur? P4: I think as a female entrepreneur or as anybody, if you have the mind set, if you have the attitude, to put in hundred per cent in your business, really, really try to make it flourish; I think it would be hard to fail. I think one of the factors is your drive, your determination, and your ambition. I think they are key, but I lack it until now, that’s what I really need to pick up on. Those are the things that are important for growth for any kind of entrepreneur (...) that’s where I see my shortfall, knowing what I need to do to push my business forward. R: How would you see entrepreneurship education, meaning, sales, marketing, management, finances, accounting, and other type of education related to entrepreneurship? Whether you need or lack or whether they are important for the success of your business? P4: They are important, you have to have a bit of knowledge of all these things certainly won’t do you any harm, and I do have a limited knowledge of Marketing and Accounting, Advertising. I have got knowledge since I did the HNC and HND in the 1990s, so I am relatively intelligent, I kind of know the ‘just’ of things, but I would say as a female entrepreneur if you really want to make a go of it, the more knowledge you have the better. I am sure it will benefit me to go on a course where I can learn more about marketing, accounts, advertising, or anything to do with business, it will definitively benefit me, whether I got the time and inclination that is the thing. R: Thank you very much. Interview terminated at (...). INTERVIEW WITH PARTICIPANT TWENTY ONE – TRANSCRIPT R: Researcher P21: Participant Twenty One Introduction R: This research is entitled “The Impact of Entrepreneurship Education and New Emerging Technologies on Women Entrepreneurs’ Success”.

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R: Please speak about yourself, your business educational background, how did you start your business, the type of business you have and what are your main activities on a daily basis? P21: I am forty years of age and I spend most of my career in media. I have been an Editor and an owner and an editor of a local magazine since July 2014. So, is effectively a year old. Since March 2015, I set up a media consultancy to complement the magazine; so also, I am heavily involved with the local community, because I am very passionate about promoting local women in business, to be inspirational to local girls within our educational system, and at the moment I am running a local women in business networking group from eight to eighty five members within a space of six months. R: What about your daily activities? P21: Ok, basically my day starts at six o’clock. I have two children age five and eleven. So, between the hours of six and eight I try to do quite a lot of research for my day a week ahead. From eight o’clock till about nine o’clock I am busy being a mum taking them to school, dropping them there, (...) whether will be school term or not. From nine o’clock to lunch o’clock, I split my time between having one to one meeting, running workshops or doing admin. I try to have a bit of lunch; sometimes (...) because I am so busy, one of my key weaknesses at the moment is time management, for being local business entrepreneur. I then in the afternoon I try to run as much time between one and two p. m. to do as much administration as I can, because at three o’clock is the school run. So, between three and eight p. m. I am busy mum. It depends what the children are alike, whether they are in a good mood, they are happy, to keep them amused, so I can do a bit of email. If not we can go out to the beach and we do some activities. Once they are in bed, nine p. m., I then try and do a little bit more research. While I am on social media, I am doing PR and I am planning my next day. R: Thank you! How do you learn and what is the best method for you? P21: I am self-taught, other than being in cooperation. For the majority of my career I was working with radio and newspapers, and my old MT who is now my business mentor is based in X. We have conference calls, around once to twice a month. This is usually a conference call at around nine o’clock in the night, because he is a busy chief executive on a radio station in X and effectively obviously, I am a busy local woman entrepreneur. I am a keen reader, so I read women in business books, I go on YouTube, social media, yeah, I am effectively, every minute I can adapt and learn more about being a woman in business. R: Do you think that this will impact upon your business success? P21: Yes! Because without this extra learning and nurturing and twinkling, my whole day, my week, my month, of being a woman entrepreneur, I would be as successful as I am. I wouldn’t be able to be the best for my clients. R: What can you tell me about information technology, new emerging technologies such as: facebook, twitter, Google, iPhone, Smart Phone, iPad, tablets and their influence on your learning and on your business success?

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P21: Social media today is not the future, it is happening now, and I am a great believer and it needs to be part of your business day, it is a dynamic and a great marketing tool. I think every female entrepreneur has to adopt a daily routine. R: Which one of these technologies do you use the best? P21: All of them, I think is part of the marketing mix. So, between Twitter, Facebook, Instagram, Pinterest and the LinkedIn, as well as you can fit in some Blogging. You do need to look at the dynamic of these platforms, because effectively is a free resource, other than that it takes a lot of your time. R: Are you satisfied with them? P21: Yeah, I wouldn’t be able to promote my business. R: Can you explain which your best styles of learning are? P21: I learn best as a practical learning, so, I am a very creative thinker, I have to look to diagrams, I have to be able to apply what I am learning, within the workshop, working, talking, sharing the experiences, and I am always looking for other women to inspire as the younger generation.

So, to be in a classroom,

learning theory, doesn’t work for me. R: Do you belong to any group, network and association? P21: Yes, I actually because I got very frustrated about some other local networks, what are around Wales, (1) they are too expensive, (2) they don’t fit in with the busy mums, especially single busy mums, so I started my own local [network]. So, what I do is, we run every consecutive month in the morning, meetings and then in the evenings. So, actually, our audience turn up that they are retailers that can come to the morning meetings, and if they have childcare to think about, perhaps dad or granny, they can look after the children in the evening and they can attend. So, I am very passionate about networking, and also the teaching of how to best get something out of networking, because a lot of women in business at the moment are timid to coming forward, about how they do network. R: Can you please tell me how do you acquire information and knowledge within these networks? P21: Well, what you have to think about is that I am very inquisitive and the role I lead as an editor, a media consultant, I am already, naturally nosy, I want to connect people, naturally I am a good public speaker, although I don’t think, you know is part of my daily routine, genuinely and naturally and hence connect with my business (...) just to see people. I understand business and I think that it is important to speak with each other. R: What is entrepreneurial success for you? P21: It is about being able to be independent, it’s about being proud about what you believe in and you are passionate about, it’s having freedom to actually be a mum, a wife, a single mum, a business woman, to feel what is in fact the success; it is to have disposable income, to be financially independent. I think it is the pathway to women understanding that they can actually do it all. R: Thank you. How would you measure the success?

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P21: I would measure it in happiness, because to be happy, I think you find the balance between life and work. Some people may say that they measure against how much profit you make it, how many sales you take in; although, for me money is irrelevant because you will live to means and if you are happy then you have created and achieved all the success you are after. R: How would you define women entrepreneurs’ success? P21: I think if I meet someone who is a female entrepreneur who is successful, I wouldn’t be able to take my eyes and ears off her. I want to be around her, I want to shadow her, I would learn and take what skills she actually has into my business, because I should be honoured to actually meet someone with such dynamism, direct and focus she should be driven, ambitious, and she would have (...) that she would like to help others. R: How would you define business growth and whether you find a similarity or a difference between women entrepreneurs’ success and business growth? P21: Business growth I would define as repetitiveness, so if you are growing as a business, your customers will keep coming back, because they actually respect what you are all about, the service you are providing, they believe in your brand, and they would be happily relaxed to recommend you to others. They will become effectively your own grand ambassadors. R: How do you acquire knowledge with new emerging technologies? P21: You have to be very selective, because we are bombarding every second with the marketing message, so you have to be selective on what information you first thing want to read, and what you want to believe. Because, everybody has an opinion, everybody believes they are specialists; everybody is trying to sell you something. So, I do believe that if you carry on online, and you are able to search through some quality information then is good for you. R: Thank you! Interview terminated. INTERVIEW WITH PARTICIPANT NINETEEN - TRANSCRIPT R: Researcher P19: Participant Nineteen Introduction R: This research is entitled “The Impact of Entrepreneurship Education and New Emerging Technologies on Women Entrepreneurs’ Success”. R: Please speak about yourself, your business educational background, how did you start your business, the type of business you have and what are your main activities on a daily basis? P19: Ok, I haven’t done anything like this before. I previously used to work in a sort of civil service organisation, and I have leaved that for health reasons, although after twelve months or so, I had the opportunity to buy this business. It came up, and was at the point where my husband and I were able to take advantage of the opportunity to finally do something we wanted to do. I always have been interested

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in baking, so it has been a very steep learning curve, but it has been great actually trying to get the cafe of the ground. R: What is your educational background? P19: Ok, I have degree in Politics and Government. R: What are your daily basis activities? P19: It’s mainly baking and preparing food here for the cafe, but also, deciding if we are going to do any (...), you know how to run things. R: Thank you! How do you learn and what is your best method of learning? P19: It’s probably hands on doing actually, things, rather than you know, a sort like a research or anything like that. R: So, it is experience –based? P19: Yes, experience - based. R: Do you think that the type of learning is affecting your business? P19: No, not at all, no! R: Do you have some entrepreneurial education such as: management, marketing, sales and accounting? P19: I have been a manager, in my previous job and I had management training for that, but not in terms of entrepreneurship, no, marketing or anything like that. R: What about information technologies skills and new emerging technologies such as: Facebook, Twitter? P19: I mean I used those computers as part of my working life. I used them in my personal life as well. Mm... I am very familiar with things like iPad, I am using that and through that I am accessing social media. I also did a baking Blog for quite a while, before leaving my last job, so, I have the experience at least of using the internet and social media to try to publicise my Blog there, having that for the cafe. R: Thank you! Which of the following do you use: Facebook, Twitter, mobile phone, Smart Phone, iPhone, Tablets and Google? P19: All of them! R: Both, for business and for learning? P19: Yes! All of them! R: Do you have some preferences? Which are the best? P19: No, not really! Mm... The applications like Facebook and Google I tend to use them on my tablet, my iPad, but that doesn’t matter which one. R: Do you think that they are important for achieving success in business? P19: I think in these days and age, it is important to know about social media. The best way of accessing I found it is through portable devices like, such as my Smart Phone and iPad. Our till system here and our

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stock system is based on the iPad, and is very, very mobile in that respect, we can take it home and check it wherever we are. So, I think, yeah, it’s very important. R: So, do you use them for information, communication or sharing? P19: For information! R: Which of these information communication technologies and new emerging technologies are you using for obtaining information? P19: Probably all of them. In setting up this business we tried to do a little bit of background research, on things like Health & Safety, the Food Regulations, everything that we needed to know and that’s been quite key. R: Which one do you use for communication? [Smart Phone, Mobile Phone, emails, etc]. P19: Yeah, we use Twitter, we text, we use emails quite a bit as a mode of communication that we use. R: How would you communicate with the customers and with the suppliers? P19: That mainly is face-to-face. Obviously, it is coffee shop business, they come in and our point of sale is immediate, is face-to-face. But, as we sell cakes as we prepare, we do have online ordering on our website. So, that facility is there, although, because we are a new business, nobody has used that yet. R: Would you please be kind and tell me about your talents and skills, capabilities to design these cakes. Is it a kind of craft, if I am not wrong? P19: Yeah! Yes, yes, I suppose it is. I always have been interested in baking ever since I was a child, I used to make cakes with my mum, and it is just something that it was following through adulthood. A few years ago, I had my younger son. I was on maternity leave, and needed something to keep myself occupied. So, I became more interested in baking then, and developed I suppose through practice and self-teaching, you know, my love of baking, making cakes and designing all sort of artistic things. R: (...) How would you communicate with the suppliers? P19: Again, it is also face-to-face, we have people coming in, but also, for example for our coffee suppliers, we will send a text message to him, on a weekly basis, explaining what we need, and he comes in the next day and deliver that. R: Thank you! How would you define women entrepreneurs’ success? P19: How would I define it? For me I don’t think is about a woman, it is just being a successful entrepreneur, trying to sort out the business. I certainly, you know, I don’t see anything in how our business is developed, so, sort that affect my husband or I just because of our gender. R: Mm... That is a good point! Ok. R: What is the success? P19: I think is having happy customers who like our products, who come back, so we can develop a good relationship with them, almost think like friends are coming in. We do need to earn a living from this, so

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at the end of the day. I suppose making enough profit, to be able to allow us to have adequate standard of living. R: How would you describe a woman entrepreneur? P19: I am not sure again that I would differentiate, because so far, I met women who are incredibly driven and ambitious, to the point they would manipulate situations. I met women who were particularly generous and kind and sharing their time with me, almost mentoring me. But, equally, I found that with men as well. R: Yes. Yes, that is true! R: Now, because I observed this particular feature that you have, that you create something, a kind of design on cakes, so, how would you describe yourself as a woman entrepreneur in that context? P19: I am lucky that I am doing something that I enjoy, and that I get a great deal of satisfaction from in it. You know the act of actually making a cake, having, you know, look nice and probably more important tastes nice, and that the customers are happy with. That is like really nice for me. R: What is the business growth for you? How would you define this? P19: Business growth for me is that having more customers come in, looking at how much they are spending and encouraging spending more, so the individual sale increases. So, people they donâ&#x20AC;&#x2122;t just come in for a coffee but they start trying our food and developing what they buy from us, and hopefully we keep growing. R: Do you belong to any network, association or group? P19: No. R: What about on the Facebook? (...) P19: Yes, on Facebook, I am member of different groups. They are all based around the community X, and also set my own personal interest as well. But the community groups I tend to, I donâ&#x20AC;&#x2122;t really participate in, but I like to know whatâ&#x20AC;&#x2122;s going on and see what is being talked about. R: Do you enjoy being a woman entrepreneur? P19: I enjoy having my own business, to be my own boss and that is one of the driving factors, which lead my husband and I to set this business. We reached the point in our life where we have been employed by other organisations twenty five years and we found that it was time to do something for ourselves. That is great. I think is something that is one the best things that we have ever done. It is a lot of stress involved, although, and you know, at the end of the day you have to try and still maintain a family life, and I think that women find that more difficult than men, because is a lot of domestic responsibilities still posed on us. R: How would you promote with the new emerging technologies you beautiful products? P19: Well, we have a website, where we explain a bit about the cafe, like a nice background, (...) the kind of things that are important for us in terms of ethics and values. We also use it as online shop for ordering cakes, and also publicising some of the other things we are doing such as afternoon tea bookings, and so on. That is mainly kind of what we are using for. R: Thank you very much for this privilege. Interview terminated.

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INTERVIEW WITH PARTICIPANT TWELVE - TRANSCRIPT R: Researcher P12: Participant Twelve Introduction R: This research is entitled “The Impact of Entrepreneurship Education and New Emerging Technologies on Women Entrepreneurs’ Success”. R: Please speak about yourself, your business educational background, how did you start your business, the type of business you have and what are your main activities on a daily basis? P12: I was educated to degree level at University of Leeds. I did a Bachelor of Science in Pharmacology. So, I did a science degree and then entered the world of research, and worked in labs for a few years. About five years I worked in labs doing all sorts of testing, but I always wanted to run my own business, instead to work for somebody else. I worked a few years researching my passion: food and science were my two loves, what I spent my life doing, when I came across to liquidizing ice cream. I thought what a nice opportunity, a fantastic concept. I spent two years doing, researching it and gathering information and writing a business plan to be able to open the first Wales Liquidizing Ice-cream Parlour. R: Please develop a little bit more about this type of business. P12: The concept is that we spend time liquidizing fresh (...) ice cream. We freeze the ice - cream in front of the customers’ eyes in a matter of minutes. We are not an ice cream parlour, we manufacture as well as we retail also the ice cream. It is a super-premium product, everything is made from scratch. We use a lot of ... ingredients, fair trade article when we can. It is producing a fantastic show, it is very entertaining for people of all ages, and is producing a superior product. The fact is that is freezing the ice cream so quickly with liquid nitrogen, which is minus 196 degrees. It’s so cold and (...) crystals are forming during the freezing process, so, produces a superior, creamier and smoother and denser ice cream, which is much richer in flavour and it has the texture of velvet, it is really very beautiful. R: What are your daily activities from morning until evening when you finish your duties at the shop? P12: We come in the morning; we just do the first check. Running a food business we just need to know that the food has been stored correctly, (...) everything is at the correct temperature, check food, and then we accept deliveries. That’s often takes a large amount of time. It is not how you want to spend the time but, that’s how the things are. The next thing we do, it depends on the day, we do stock takes, we need to re-order food, we do sales forecast, predicting how much we are using. Because is an ice cream business we are very weather dependent, in different times of the years, like in the summer, we are more busier that in the winter. We also do student school holidays, (...) we just collect a lot of data. Then, we work out our sales. We would like to work with product and seasons as well, so we have to do ordering in advance, menu design. That takes out a huge amount of time, and then obviously is about the basics such as staff rotas, cashing up, banking, (...) all sorts of staff making sure that everyone is doing the job correctly, keeping on top with the food hygiene. Everyday there is some routine, but there are many things. .... I use to serve the customers as well, having a lot of out front shifts, but as we grew our business, there is just no time for

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me to do that. I am running the business and increasing. A large part of my time is increasing the turnover and working towards those goals to make the business more successful. R: What is the best method of learning and how do you learn? P12: Learning by experience from the business. I was very lucky to have two very good mentors. I also come from a family of entrepreneurs, so my parents run their own business for years, and told me I was mad to want to do myself. Just long hours, hard work, high stress, but I just enjoy. I just want to give it a go to see how I did it. But my mum has been a lot of inspiration to me and my private investors are. They were helped when they were younger, so, they did a lot of mentoring to help me. They spent a lot of time to help me, when I have to do things, for example I didnâ&#x20AC;&#x2122;t do a back presentation, a business plan. They help me very much. They put me in contact with legal support, accounting support and things like that. I was very luck, to have people with me to help. R: It appears that you had some entrepreneurship education before you started. P12: Yes. I guess. In my previous job, we did. I started my lab work. I worked up to management; then I went into admin job and learned how to do bookkeeping. The sales are not something that I have a huge amount of experience in doing. But luckily, my mum and my two mentors have a lot of experience in that sense. R: What is your opinion regarding the entrepreneurship education? P12: For me, it is not something that I was aware that I was there. I have an entrepreneur who works in this company and is part of the core team. He uses a lot of these things; he goes to the Welsh Assembly, to the local A. M. and uses a lot of sources that are available to him. But is not something that I have myself using. R: Do you think that the entrepreneurship education is impacting upon your business? P12: Yes. We learned so much. We are in kind of job we depend, and we knew so little. Now, we learned so much, quickly. ... It was nice to have these skills before opened up. I have these skills to a certain degree but, most of them have been learned as I just did it. R: What kind of emerging technologies do you use? Do you use performing laptops, computers, Facebook, Smart phones, iPhones, iPad, etc.? P12: We use, our entire system runs from a Cloud-based platform, and that keeps a track on the stocks, cashing up and help with generating monthly reports. Generally, we use Excel a lot, accounting software and we are developing our own system now, where we are writing our own code for it, which will streamline everything. So, it will do a lot of paperwork for us, health & safety work, sales forecast. The emerging technologies are really important for us. We are also develop a prototype, for delivering liquid nitrogen directly into the ice cream making machine, which will streamline the business and help produce concept technology. We opened up, not using technology and now fourteen months into the business it is something we are really trying to bring into it, to make it more profitable. R: Do you use tablets, iPad, Google, Facebook and Twitter?

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P12: Yes, everything. I use social media platforms, Twitter, Facebook, Instagram, but we are also looking into using Red Scarf, which I believe is used by Chinese students, as a social media. We use Google, as an advertisement. We pay to do it as part of the street food, if you type it on Google. We use Google Analytics as well, so Google is a huge part of this.

We use it as an advertisement, it helps with the opening time,

and direct people to the website, Street View, Analytics, so Google is very good for small businesses. R: In what sense the emerging technologies help the learning? P12: Google Analytics, for instance, breaks down who is visiting the website, what country they are from, how many people in the local area using it, the gender, the percentages of male versus female, the age group they are in. It is giving us a lot of information. Which is equally important to us for where to direct our marketing, perhaps what we are missing out and it is really helping with the picture. R: Is this business local, national or international? P12: It is international. There is a lot of traffic into our website which is coming from America, because the liquid nitrogen ice cream chat is taking up more over there than in Europe. It is very much an emerging market. It is more developed in China, America and Australia. The actual business is sales direct in the shop, but a large part of sales are from visiting tourist. R: What is women entrepreneurs’ success? P12: ... Ninety percent here in the....are women. What we are all having in common is that we come from a very good support network. We are supported by family members, partners, who believe in us and give us the opportunity through that support ... it’s just about having that belief that you can do something different and giving a go. It’s mainly that they are ambitious, hard working ... very long hours and have a talent for hard work and just keep going. Everyone here loves actually, what they are doing. It is very important, it is what it keeps going. R: What is business growth for you? P12: Ultimately, is about increase in turnover, getting us to the point where we franchise the model, getting many more stores. We have a five-year plan to get to that point. Success in the first year it was just survival. Then after that year, we managed to grow, which was fantastic, because we had interesting time and days to get to this point. First of all was building out brand and then the customer base. Now it is about increase in turnover, and franchising. R: What is women entrepreneurial success? P12: ...you come away with many skills which you haven’t got, and put you in a position to make it up the ladder, because of is a lot of disparities at the top, where women aren’t getting at the top as much as the men, in the same percentage. It is getting women to believe in themselves, have the success and then the experience to be able to climb the ladder...and be equal. R: Do you enjoy being a woman entrepreneur? P12: Yes. R: Why?

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P12: ... it feels that is a lot of support out there for each other and you are able to join a group... and everyone helps each other. R: Do you belong to any association, group or network? P12: We belong to lot of street food groups ... where traders look after traders, but not to an official body. INTERVIEW WITH PARTICIPANT THIRTY - TRANSCRIPT R: Researcher P30: Participant Thirty Introduction R: This research is entitled “The Impact of Entrepreneurship Education and New Emerging Technologies on Women Entrepreneurs’ Success”. R: Please speak about yourself, your business educational background, how did you start your business, the type of business you have and what are your main activities on a daily basis? P30: This was an established business, the previous owner of the shop started the shop about fifteen years ago, and I was in another corporate job until recently, but exactly one year ago I decided to buy the business and took over the shop at that point. Well, in fact I made a decision before that, when I took over the business. R: Please speak about the normal activities on a daily basis? P30: On a normal daily basis the activities focus on obviously serving customers, advising them on book purchases, buying the books either from whole sale distributors, or direct from publishers and returning books, which we haven’t sold. It is what are we doing today, and just generally focusing on the marketing and presentation of the books in the shop and some other special events what we have, running on a regular basis. R: How do you learn and what is the best method of learning for you? P30: For me, I didn’t have any formal training in this business, or in retails at all, so, I learned a lot from other people, initially from previous owners of the shop, who were very kind and passed on to me as much knowledge and experience as they could. I also learned now from other book sellers, there is a nice strong network of other independent bookshops in the South Wales. Then we have occasional meetings and we stay in touch through other channels in between, though I can get advice from them and learn from what others are doing, and of course, the main way is learning from experience. By trying things out and if they don’t work, try something else. Things like selecting the books for the stock is very much like trial and errors, but you have to select which books are based on what you thing is going to sell, and I try some research as much as I can, keep close to what is in the news at the moment, in the review press, bur at the end of the day it is trial and error. Sometimes you get right, sometimes you get it wrong. R: Do you use information technology? Do you Google, iPad, Tablets, the laptop, Smart phone, iPhone and computers?

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P30: The business is very dependent on ICT. Yes, we have a stock management system, which we use for tracking all our stock, recording sales, the ordering process, the return process. All of that is on computer, it is in the shop and is basically used continuously, all day. In terms of actually managing the business, I use my personal laptop, where I also track all of the accounts and do all the bookkeeping, and so for prepare PR material, and so on. We do a lot of email communication. We have Facebook page, a website and a Twitter account. I also update all of these on a regular basis and I have a Smart phone, we notify customers, whenever possible, if they have a mobile phone and an iPad they use it, we notify customers when their books arrive, by text. When I am out and about, not physically in the shop, I do use my Smart phone to keep in touch with the emails coming in, Twitter, and Facebook as well. R: With regard to these new emerging technologies, which one do you prefer? Which one is the best for learning and for business? P30: Facebook and Twitter are critical, and the website for business in term off keeping up our profile, and marketing and publicity and so for. In terms of learning, I would say it’s primarily just the internet in generally, Goggling things and researching information, whether is about books or some aspects of business, just general website search really. R: How would you define business growth? P30: Business growth would be increase in sale and revenue obviously, and profits. I keep a very close eye on sales level and also on margin, which is critical because I try to make a profit. In terms of future business growth I would be look into expand because I have very limited physical space. As the opportunity arises I may look to expand, (...) but, I don’t want it to grow beyond the level to I can personally, be involved in everything, in some kind of business empire where I lose touch with the day to day staff. I wanted to be a small personal business. I don’t just look for success in terms of turnover and profits. R: What is women entrepreneurs’ success in your opinion? P30: I think that will be able to achieve both business goals and personal goals. For me, this business is very much something I have chosen to do later in my career, in my life, because I wanted to give myself a challenge and something completely different to do at this stage. I am sure it is different perhaps for younger women entrepreneur starting out, and (...). They will make their all career in that entrepreneurial environment. For me, it’s a matter of being able to balance business goals and personal goals and get satisfaction from both. R: How would you define women entrepreneurs? P30: It is about having great ideas first of all and often when women ideas are informed by personal experience of not finding what they need, or seeing opportunities and gaps in the market based on their personal experiences in some way.

Secondly, it is about having the skills, the persistence and the

determination to really make it happen. R: How do you acquire knowledge and information? P30: Mostly from other people, I could say from my own experience. It’s learning from other people and from their support and experience and then, from my own experience as well. I think every business is

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different, though, it can be difficult to have formal training or education that will suit the particular needs of any particular entrepreneur. I think is about to speak more creative about that, using the sources and opportunities that are around you to shape your own knowledge. R: Do you enjoy being a woman entrepreneur? P30: Very much! R: Why? P30: Itâ&#x20AC;&#x2122;s having the flexibility I guess, to whatever you want, to try whatever you want. I love providing a service. I am pretty satisfied when people appreciate this. I just love having control on my own environment and the way things are done, and being able to try and be creative. Sometimes it works, sometimes not, but is always something new to do. R: Do you network? Do you belong to any association, business association or group? P30: Yes, the Informal Community of Other Book Shops in South Wales, we have regular meeting. That is a subset of the National Federation of Book Seller Association, which is also I suppose a network throughout all of the UK. More locally I am part of the Women Business Networking in X. This is just an opportunity to meet other women in business at local level with support and contacts and to learn from them, and just meet people and have a good social life as well. R: Do you belong also to the Community Association to network with other businesses? P30: Not yet! It was a talk the last year to set up a Business Improvement Association but did not go through in the end. That would have been a sort of a business network community. The alternative to resurrect the local Chamber of Commerce that used to exist, it is being pursued (...). If that happen I shall certainly be interested in that. R: Thank you! Interview terminated.

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APPENDIX E: TRANSCRIPT - FOCUS GROUP WITH FIVE PARTICIPANTS R: Researcher FGP1: Focus Group Participant One; FGP2: Focus Group Participant Two; FGP3: Focus Group Participant Three; FGP4: Focus Group Participant Four; FGP5: Focus Group Participant Five. Introduction R: I would like to express my thanks for accepting to participate within this Focus Group. Let us introduce ourselves. I am a PhD Researcher at University of South Wales and I am conducting a research on women entrepreneurs, entrepreneurship education and new emerging technologies. Would you please be kind and introduce yourselves to the Group. FGP1: I am the owner of X Admin. FGP2: I am a Personal Stylist. FGP3: I am the owner of Y Landscape. FGP4: I am the owner of Z Media Consultancy. FGP5: I am the owner of V Training Limited. R: This research is entitled “The Impact of Entrepreneurship Education and New Emerging Technologies on Women Entrepreneurs’ Success”. Question One: R: Please speak about the type of business you have and your business educational background. What type of daily activities do you have? FGP1: I run an admin business, which is a freelance admin services company. I ask the clients to outsource their admin services to me, so, I handle the things that they cannot manage. My business educational background is ten years experience in arts education and administration. My daily activities are two days per week working and three days per week looking after my boys. R: Thank you! The second participant, please answer the same question. FGP2: I am a personal stylist. My aim is to help women to refine their confidence and personal style, and give them something for themselves back. My background, I have a degree in Fashion Design with Manufacturing, Marketing and Promotion. Before I did my degree, I worked in a design factory, in ‘A’ town, where I am from. My daily activities are at the moment researching, maintaining social media and trying to get the clients coming in. R: Thank You! I address the same question for the third participant, please. FGP3: My background, I studied for a degree in architecture and I have a Master degree in Landscape Architecture. Our business is a comprehensive gardening design, construction and maintaining business, mainly focusing on domestic clients, but we commercial clients too. We primarily design gardens, building

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them and plant and things and so on. My daily activities are very varied: meeting clients, hands on, on site, emailing, marketing, all sorts. R: The fourth participant, please. FGP4: I am a publisher, I run a magazine, which I mean I manage it, edit it and I do the advertising for. Recently, I launched a media consultancy, which includes coaching one-t-one, to group, workshops and anything from on anything from Sales to Marketing, Social Media and Business Mentoring.

educational background is quite random actually. I left high school to work in a bank. I didnâ&#x20AC;&#x2122;t enjoy it, after that I went to University to become a nutritionist and have a health science degree. I did a health promotion postgraduate course and then landed in Radio by default, never left the media for fifteen years. Thatâ&#x20AC;&#x2122;s why now I own a magazine and a media consultancy. My daily activities are very random. I have to sort out my two boys to go to school, by nine oâ&#x20AC;&#x2122;clock, two young boys in different parts of Cardiff. (...) My day starts with anything from talking to my Personal Assistant (PA), which I am very proud of, running the accounts, selling, advertising, writing features, going to do workshops, going to sell, encouraging businesses to join my Forum, running a women in business network. Oh, yes I think I am a superwoman. R: Thank you. The fifth participant, please! FGP5: I like a lot of us, have a lot of aims... I do coaching and I do one-to-one tutoring, I am interested in Dyslexia... I move back from F... three years ago, so, I built up my contacts that I lost. I was a College Manager in Further Education and I have got a degree... I did teaching training, I do coaching, I do NLP. At the moment I do work with home tuition service, hoping that young people get place in (...) with their homework. Also, I do creative writing, in the transition to becoming full time writer, which is my goal. R: Many thanks! Question Two: R: Could you please define the following terms: women entrepreneurs, entrepreneurial success and business growth. How would you see a woman in business? FGP1: For me, I am the definition of that because I am doing what I have chosen to do, which is to balance my work and my family life and also to focus my career on something that I really enjoy doing, meeting amazing female clients who become really good friends. I am doing something what I am really good at, I really excel at. Entrepreneurial success could be about the money, but also I think is about balance and how it makes you feel when you work at your personal success. Business growth it is about how you expand and you grow your business, how you finance, taking on staff, using your finances to expand... R: What are your main features as a woman entrepreneur? FGP1: My personal ability, the way I relate to people, the way I support my clients, I understand their businesses, I know what they need from me, I can identify that quite quickly. I develop trust with the clients, so they learn to use me as a support, not only as someone who does the admin... R: The second participant, please.

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FGP2: It is about a woman coming up with a unique idea, having the courage, and being confident to go with it, on top of everything else that they require to do in daily lives, especially if they are mothers. Entrepreneurial success is about continuing to grow the business. Business growth is just looking for new avenues and keeping abreast of what is out there and always being one-step ahead and being... R: The third participant, please. FGP3: For me women entrepreneurs despite saying: this is what I do, this is what I cannot do, this is what I want to do, how can I turn it into a job, how can I make this sort, you know, who I am. They don’t have to step into a traditional role, or a traditional kind of job, which might be something that you have to do. So, thinking about and outside the box, and saying, this I want to do and do it. I think entrepreneurial success leads straight from that in the sense of how you turn your idea in something that actually works and finally makes money to live and business growth is how you take that further, going from just surviving to how can I throw out, how can I build my business and somebody figures out how to do that cliché... how to sort that out to happen. R: The fourth participant, please. FGP4: A woman entrepreneur to me, is an interesting one, because I am very passionate about, energising women... there is a definitive movement in the UK at the moment about women finding themselves and being able to find inner confidence about ‘yes’ they can do what they love, they can be flexible, they can work around whether they are busy wives, busy girlfriends, busy mums. There are so many elements and dynamics to this. This is what will power through something that will effectively make a better country. Entrepreneurial success it’s all about being confident that you don’t have to conform. Before always have been boundaries and ... that ‘You can’t!’. Now it is a ‘can do’ attitude. Business growth, I don’t think is down to money. I think business growth is personal, mental and physical, is that you have a confidence not only to believe in yourself, but believing in others and taking others along with you. R: The fifth participant, please! FGP5: Woman entrepreneur is a woman who left a safe paid job to take a risk to set up a business whether as a self-employed or limited company. It is leaving a Job College with a monthly paid package and starting on my own. Entrepreneurial success is being in a place where you are comfortable with your income and what the company is providing to other people. Business growth is hopefully a business, which is not where, was a year ago and might go in many directions... Question Three R: How would you evaluate success? FGP1: Positive client feedback and my own personal happiness. R: The second participant, please. FGP2: Reputation from customer feedback, personal achievement and a number of clients. R: The third participant, please.

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FGP3: I think creating something that somebody didn’t have before ... add something positive to somebody’s life. R: The fourth participant, please. FGP4: It would be happiness, contentment and financial stable. R: The fifth participant, please. FGP5: Success is that I am happy with the company and ...I want the clients to be happy with me.... Question Four: R: How would you learn and what are your preferences in the context of new emerging technologies, such as information communication technologies, social media like Facebook and Twitter, Smart Phones, iPhones, iPad, Androids, Tablets and computers. Do you use these technologies for learning? Do you use them for business? FGP1: Yeah, daily life and work life on laptop, iPhone, definitively on social media. It is amazing ... to get free advertising, free messages to your clients and to the world. I use them for learning, research, for looking into things. Yeah, I use the internet every day. I use for both learning and business. R: What are your preferences for these technologies, regarding your learning and their usage for business? What about your style of learning? FGP1: I use the laptop for the business and for the learning. The style of learning: reading, researching and exploring. I use information technology. R: The second participant. FGP2: The way I learn is by using most of these technologies. I find a little worry because I would still like to read a book. I think it is very worry all of these, especially, by having an eight-year-old son who is addicted to most of these technologies. I mean is extremely disturbing because this is his way of learning and books are second grade to him... I use Facebook, Twitter, Google, iPhone, iPad, Mac Book Air. I am equally addicted because they are my main learning facilities. R: The third participant. FGP3: Previously I mentioned that I use all of mentioned technologies, in terms of reaching friends and family and also clients, and not only existing clients but general businesses. A lot of my business comes from Facebook, Twitter, and my website and blogs and all sorts. I use daily the iPad, Smart Phone, that is really important and my laptop as well. R: The fourth participant, please. FGP4: I think Apple sponsors me. I don’t think I can function more than one night without an Apple product. I don’t know whether that’s good or bad, but that is my life, my oxygen. It is my only way of promoting myself other than in a Forum like this, where it is a pleasure to be around human beings, to be emotional to talk about, you know about the highs and lows about running your own business and about

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being a woman entrepreneur. But, yes, everything what you think about, whether is Pinterest, LinkedIn, Twitter, Facebook, I probably start my own platform before long. R: Would you choose only online learning or traditional learning, or blended learning? FGP4: No, not at all, because I use ... I am a book worm. If anything it makes me cross in life is that because I am in publishing world, I don’t have enough time to digest other publications. Why? When I look at it, I am creating ideas, I am thinking like a businesswoman rather than: This is X... a mum, a single mum, who wants to get some luxurious and read a magazine or a book, rather than looking in it as a tool. I am at cross roads at the moment... R: Which one is the best for you? What do you prefer for business and what do you prefer for learning? FGP4: For learning it will always be Google search, I am on Blogger so, I have things regular, every day in the morning. Whose Blog is about some topic I am interested in, that will be a food to me even before I woke up. When I do wake up at four o’clock, because I can’t sleep, because I am so tired, then I will digest myself into something like the career girl Blog. When it comes to learning, I rather learn from inspirational women entrepreneurs, which I am still on a battle to find out, because I am one for younger women. I think is enough there locally to inspire me. R: Thank you. The fifth participant, please! FGP5: Because of my age, probably, I don’t even have an iPad, because I don’t see any value in it. When I did the postgraduate certificate recently at the university in mentoring... I got books and I actually bought books. I still prefer books. Nowadays, you have to use social media to promote your business, but I do it to storm my children actually. I get much more fun out of this than from when I am using technology for something else. In business I use Facebook. I have two Facebook pages. One is my personal one and one is my work one. I use Facebook and Twitter. Question Five: R: How do you acquire knowledge and information, in the context of networking and new emerging technologies in order to achieve success? Do you belong to any group, network or association? FGP1: I belong to Business Women in X, which is a networking group and was probably, one of the main catalysts for me, for leaving my own regular salary, income job and jump off the plank to start my own business. It gave me the confidence and inspiration to feel like I can do it, and to balance all things I need into my life. I do belong and I find it very important and valuable and an important part of my business and personal life. R: The second participant, please! FGP2: I think through people, by talking.

I like people, and I am interested in people, so through

conversation, of course. How do I acquire knowledge? By the previous question, technology: Facebook, Twitter, Google, reading Blogs and so on. Yes, I belong to women in business in X, as it’s now called, which is a networking group and which is another platform for gaining knowledge, very good and very supportive.

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R: Do you think that are important for the success of your business? FGP2: Absolutely! R: The third participant, please! FGP3: I also belong to business women in X, which I only recently joined, but I find really helpful and it is lovely to connect to other people, who are in the same position... In terms of other sort of networks, I take part of Nation Wide, which is (...). I also go to local trade shows. This is how I connect to my networks to reach the whole world... R: The fourth participant, please. FGP4: I am the founder and the chairperson for the Women in Business in X. It is very humbling to hear these comments, and it is set up because I was selfish and I needed other women, to feel how I felt, which was lonely, frustrated, lost, and not sure whether I could be successful. It is great to see that this platform has become not only a great institute for me, but for others as well. Looking elsewhere, I found that this year particularly, it is a time to invest and develop my skills, because I am great in helping others, but I know that to move forward I have to invest in learning and training for me. I am a member of the Public Speaking Association, which is an UK based networking group, which has different forms across the UK, and in Cardiff and I am also attending conferences like L... I am also looking for something new and innovative, to progress women entrepreneurs. R: How important are the new emerging technologies and the networking for business success? FGP4: I find face-to-face more human and personal, that’s where I am like as an individual. Online is a bit more solo, it’s not so transparent. I don’t feel like I connect. I will go there for information, if I needed. But, as an individual, to grow personally and through business I need the one-t-one and group contact. R: Thank you! The fifth participant, please! FGP5: I don’t think that you acquire knowledge for business as much, as you acquire knowledge through others who are around you and what happens locally, which is really important, and a networking group is a great way to do that and make that happen. They could be local or national. I joined many networking groups and all of them are unique, they all offer something more or less and you have to find one that suits you. The new emerging technologies, yes, I heard something new today, that I didn’t know; they keep you update. Question Six: R: What is your opinion regarding the impact of new emerging technologies and entrepreneurship education on women entrepreneurs’ success? FGP5: I just did a postgraduate certificate in women entrepreneurship and what was really interesting was the research that came out, because of growth of women entrepreneurs. In the past traditionally have been male and it’s traditionally promoted as male, but in fact there is a huge movement of women entrepreneurs, and again they haven’t marketed themselves much. Therefore Forum like this is so fantastic, because women can see other women doing and achieving. New emerging technologies, again, Mum’s Network is

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so fantastic because there are entrepreneurs within network and they chose the power of social media for having a voice. I think women entrepreneurship is growing. R: Are women entrepreneurs influenced by entrepreneurship education and new emerging technologies? FGP5: Through technologies they seem to be aware of what happens. This never happened in the past. It is very different. R: The fourth participant, please! FGP4: I just think that is evolving actually. Women in business, entrepreneurs, from the moment the young girl starts school, so, the enterprising curriculum that you find in education starts... Being a mum of boys, then you see how keen they are to learn the skills, because they are natural negotiators already, though, I think that is a key opportunity between parents, teachers, university to embrace the fact that we as parents we are also entrepreneurs, and this resource come to be used as a benefit. The technology is just a matter of time, it’s not tomorrow, it’s happening now, you can’t even breath until you see than something new it’s on your radar. I think it is a benefit, the new technology it’s great. But, the new technology it can overpower you, it can crash you, as a person, because you don’t know which way to turn next. That can take up an enormous amount of time and effort, when back in the day, may be in eighties I would have thought, you know what, I probably I would be more successfully until now because I would have been more straightforward. R: What about your opinion regarding women entrepreneurs’ success and its relationship with these two: entrepreneurship education and new emerging technologies? FGP4: There are people who embraced it and there will be those who won’t embrace it because they haven’t got the make up to embrace it. And it’s not by default it’s just the fact that some are very academic and some are very creative. Either you embrace something like emerging technologies or you can’t. It doesn’t mean that you are any less of the success, and I think that the new platform that allows people that are more creative...they need more contact, more human conversation, fact-to-face, whether that will be in literature, performing arts. It’s just need to have its moment, because the moment and everything revolves around something that’s not very human. R: The third participant, please! FGP3: I think about what the previous participant was saying, that is not just a model that fits everyone. Not everyone would have a Facebook business page. That’s not always how the things work. Some people purely deal face-to-face, for some people online it is everything. It is learning to be flexible with emerging technologies. But, it is also about understanding that you don’t have to be on every platform to be successful. R: The second participant, please! FGP2: I am very new to entrepreneurship education, I never came across before. The first experience is by having the courage to come to e networking group. I have very small start out and I have no experience of education in terms of entrepreneurship, apart from networking, which has been brilliant. In terms of new

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emerging technologies, I totally agree with FGP4, I find it is too much choice, too much to digest, which causes confusion and can be totally overwhelming. R: Thank you! The first participant, please! FGP1: I never came across Entrepreneurship education, because I was always employed by organisations, I never had to immerse myself in that area. However, in an organisation I did work for, we were training musicians, at high education level and to be entrepreneurs in that field, they couldn’t just survive as musicians, they had to be teachers, educators and concert performers. They had to adapt to be entrepreneurs to succeed in that field. I have seen students developing through that course. Regarding the technology, you embrace it or you don’t. ... If you don’t then you have to make your success in other way. If you use technology and social media, then that’s the way of networking and making success. R: Thank you! Question Seven: Is gender an issue, either as a benefit or a barrier for you as a woman entrepreneur, in the business world? FGP1: I don’t think that I even considered it as an issue because I am running a business... R: Do you enjoy being a woman entrepreneur? FGP1: Yeah, definitively. R: Why? FGP1: Because it empowers me. It means I get to meet other women, who are doing amazing things, who are inspirational, and I can balance what I need to balance in my life, on my terms. R: The second participant, please! FGP2: I don’t think that gender is an issue at all! In 2015 I don’t think that women struggle to be recognised today, at all. R: Do you enjoy being a woman entrepreneur? Why? FGP2: Yes, absolutely! Because it is empowering and makes me feel independent, like I always wanted to have a level of independence, regardless the fact that I am married. I always wanted to stand on my own two feet. In terms of financial, professional, in every capacity I want to be independent as a woman. R: The third participant, please! FGP3: For me it’s never been a barrier, but working in constructions I have come across with a lot of barriers in that respect, that I have to overcome. Being a young woman and going to contractors, things like that, maybe I have to project myself as being more confident than I actually am, in order to overcome. I change the way I conduct myself, in certain situation that I may overcome these gender barriers. It has worked...for me, because it made me more distinctive and it’s great. R: Do you enjoy being a woman entrepreneur? Why?

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FGP3: Yes, I do! It’s empowering and it’s fantastic. The thing is that my husband left the job back in March, and he works not for me but with me and we managed to sort that out. R: The fourth participant, please! FGP4: It is not an issue for me. I absolutely love men, I love what they are about and I love the way that women and men can connect, and there are sometimes negative times and positive times. I think this is just the behaviour of being in the relationship with men, whether that’s personally or professionally. I have some of the best tutoring time from men and being a chair person for the women business group. I came across with a lot of challenges and very strong opinions about why can’t men join. What I can do I promised that when we have some guests speakers, they will be men, who are very well educated in the fact that women are not shy coming forward, they have the right equal to their male counterparts to set their own business. We are better as a team as men and female. We try to balance these barriers and glass ceiling, because so much media has been out there, we have to believe locally that we can drive this forwards, nationally will be effective and then internationally will be a voice. R: Do you enjoy being a woman entrepreneur? Why? FGP4: It’s my oxygen; I don’t know why I took so long to become a female entrepreneur... I think I was put on this planet to go and become to go into the corporate sector first, to learn from my mistakes and set my own business and to the point where I set up many businesses and I was.... and I started all over again.... It is tough but you excel in what you believe. When you find your passion in life...It is a lifelong balance. R: The last participant, please! FGP5: I still think that gender it is an issue. It is why the women are still in groups, because I have been in groups where I have been patronized by male.... I have got three girls and...Gender is an issue! Yeah, I love men, but they patronized me. I am in business to make my own business. Do I enjoy being a woman entrepreneur? ...In the past research has never included us as an element, of being entrepreneur. Now it is beginning to be accepted and I realize that you can’t ignore it as a factor of life. It does have an impact on how your business grows and how you manage to achieve what you achieve. Question Eight: R: The last question: What is your opinion regarding the impact of networking and business associations for learning and business success? FGP1: It is crucial, it is how I learn. It’s my clients, how I learn about how other businesses are doing, how I can be involved in that... R: The second participant, please! FGP2: I have not much experience in networking at all, this is the first group I have ever been to, but in terms of learning and success, it is absolutely crucial for me. For example I came to this meeting. I felt low, deflated, lost. I walk here and I am feeling so much better, it is such an amazing platform. It is not only learning and success, but it is also a support network. I am really glad that I found it. R: The third participant, please!

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FGP3: It’s really great to be in a room with a lot of energy and with people who got a kind of similar ideas and trials and tribulations as well. It is a kind of safe environment which gives you the confidence to go out and say ‘I can do this!’ and also a good thing for nurturing. R: The fourth participant, please! FGP4: It is one of my goals in life to try and encourage more female to network. I feel like I am trying to champion something, at the local level, because I can feel the energy, the love, friendship, sisterhood, being alone from North Wales, a single mum and trying my best to create a new business. I have been transparent as much as I can...It is invigorated, passion, creativity...What is beautiful is that you create such a friendship. We are not in business for business, but we are in business for us and for our friends and our family. R: The fifth participant, please! FGP5: I set up my company in 2007 and immediately I had to network, because is a way of promoting myself and do the marketing. There are many types of networking and you find one that suits you. I have been to male dominated networks, which I haven’t enjoy ... I prefer women only, and this is very local, it is wonderful to find out what is happening locally. But I will also join a network when my book is published, the RNA, which is a national association to improve my skills in the field I am working. I think women have to find more than one network and use them in different ways to help the business. R: Thank you! Interview terminated.

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APPENDIX F: FOCUS GROUP - CODING DATA Box 1.1 Developing Emergent Themes â&#x20AC;&#x201C; Focus Group (Five Participants) Question One: Please speak about the type of business you have and your business educational background. What type of daily activities do you have? Exploratory comments, key words, Original Transcript Sub-categories and Emerging comments Themes FGP1: I run an admin business, Type of activity which is a freelance admin services company. I ask the clients to Freelance admin services company Opportunity, gap in the market outsource their admin services to me, so, I handle the things that they Things that they cannot manage cannot manage. My business Experienced-based learning educational background is ten years experience in arts education and Parental duties Looking after my boys administration. My daily activities are two days per week working and three days per week looking after my boys. R: Thank you! The second Entrepreneurial identification My aim is to help women participant, please answer the same Women oriented business question. Helping others FGP2: I am a personal stylist. My Opportunity aim is to help women to refine their confidence and personal style, and Relationship between education, give them something for themselves sector experience and business back. My background, I have a activity Maintaining social media degree in Fashion Design with Manufacturing, Marketing and Promotion. Before I did my degree, Entrepreneurial activities include Clients I worked in a design factory, in â&#x20AC;&#x2DC;Aâ&#x20AC;&#x2122; using and maintaining Social Media town, where I am from. My daily activities are at the moment Client-focused researching, maintaining social media and trying to get the clients coming in. R: Thank You! I address the same Link between studies (degree and question for the third participant, postgrad) and the type of activities Design, construction and please. maintaining FGP3: My background, I studied for a degree in architecture and I have a Type of clients: domestic & Master degree in Landscape commercial Domestic clients Architecture. Our business is a Commercial clients comprehensive gardening design, construction and maintaining Three categories of entrepreneurial Meeting Clients business, mainly focusing on activities: specific, on site and Hands on & On site domestic clients, but we commercial managerial & leadership Admin work clients too. We primarily design gardens, building them and plant and things and so on. My daily activities High publishing skills & Publisher are very varied: meeting clients, management Advertising hands on, on site, emailing, marketing, all sorts. Launched a new education & Launched media consultancy R: The fourth participant, please. training business FGP4: I am a publisher, I run a Coaching & Workshops magazine, which I mean I manage it, Teaching Sales, Marketing, Social Social Media edit it and I do the advertising for. Media Business Mentoring Recently, I launched a media consultancy, which includes coaching one-to-one, to group, workshops and anything from on anything from Sales to Marketing, Highly educated Social Media and Business Mentoring. My educational Experienced based learning

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Own a magazine consultancy

media

Daily activities Talking to her PA

Coaching Tutoring one-to-one Worked in Educational sector Management Building the network Highly qualifies Postgrad Home tuition service Additional passion writings

–

creative

background is quite random actually. I left high school to work in a bank. I didn’t enjoy it, after that I went to University to become a nutritionist and have a health science degree. I did a health promotion postgraduate course and then landed in Radio by default, never left the media for fifteen years. That’s why now I own a magazine and a media consultancy. My daily activities are very random. I have to sort out my two boys to go to school, by nine o’clock, two young boys in different parts of Cardiff. (...) My day starts with anything from talking to my Personal Assistant (PA), which I am very proud of, running the accounts, selling, advertising, writing features, going to do workshops, going to sell, encouraging businesses to join my Forum, running a women in business network. Oh, yes I think I am a superwoman. R: Thank you. The fifth participant, please! FGP5: I like a lot of us, have a lot of aims... I do coaching and I do oneto-one tutoring, I am interested in Dyslexia... I move back from F... three years ago, so, I built up my contacts that I lost. I was a College Manager in Further Education and I have got a degree... I did teaching training, I do coaching, I do NLP. At the moment I do work with home tuition service, hoping that young people get place in (...) with their homework. Also, I do creative writing, in the transition to becoming full time writer, which is my goal. R: Many thanks!

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Activity related to the sector experience Ownership Part time entrepreneur Part-time parental responsibilities Normal secretarial activities Activities related to the type of activity

Extra activities – setting up a networking group & managing this

Business related to sector experience Gap in Market Young people – Customers Home-based tuition

Wishing to become a writer Goals and planning

Box 1.1 Developing Emergent Themes – Focus Group (Five Participants) Question Two: Could you please define the following terms: women entrepreneurs, entrepreneurial success and business growth. How would you see a woman in business? Exploratory comments, key words, Original Transcript Sub-categories and Emerging comments Themes FGP1: For me, I am the definition of Ownership Choice that because I am doing what I have Identity Ownership chosen to do, which is to balance my Life & work balance work and my family life and also to Balance between work & family Enjoy doing focus my career on something that I Enjoyment Career really enjoy doing, meeting amazing female clients who become really Friendship Meeting women customers/clients good friends. I am doing something what I am really good at, I really Money excel at. Entrepreneurial success could be about the money, but also I Balance Balance think is about balance and how it Identity Feeling makes you feel when you work at Personal success your personal success. Business Increase in sales, in number of shops Expand growth it is about how you expand Increase in staff Grow and you grow your business, how Finance you finance, taking on staff, using your finances to expand... R: What are your main features as a woman entrepreneur? Building network, customer-base, Personal ability in dealing with FGP1: My personal ability, the way customer-relationship, identifying clients I relate to people, the way I support with clients my clients, I understand their Trust & help Developing trust and respect businesses, I know what they need Teaching the clients from me, I can identify that quite Expertise quickly. I develop trust with the clients, so they learn to use me as a support, not only as someone who does the admin... Unique idea R: The second participant, please. Innovation and uniqueness Courage FGP2: It is about a woman coming Women entrepreneurs’ Confidence up with a unique idea, having the characteristics courage, and being confident to go Mothers with it, on top of everything else that they require to do in daily lives, Continuing to grow especially if they are mothers. Growing the business Entrepreneurial success is about Setting up other businesses Looking for new venture continuing to grow the business. Being informed Business growth is just looking for Being informed new avenues and keeping abreast of what is out there and always being one-step ahead and being... R: The third participant, please. FGP3: For me women entrepreneurs despite saying: this is what I do, this No traditional role is what I cannot do, this is what I Querying themselves want to do, how can I turn it into a Deciding for themselves job, how can I make this sort, you know, who I am. They don’t have to Non traditional step into a traditional role, or a Thinking outside of the box traditional kind of job, which might Applying things and knowledge be something that you have to do. So, thinking about and outside the box, and saying, this I want to do and How you turn idea into practice do it. I think entrepreneurial success Making enough money to live leads straight from that in the sense Surviving of how you turn your idea in something that actually works and Building finally makes money to live and business growth is how you take that

432

A Movement Inner confidence Flexible

Dynamism Being confident Non conformism Doing attitude

Money Personal grow

Taking the risk of a business Independence

Comfortable with your income Providing for others Business is not where was one year ago Many directions

further, going from just surviving to how can I throw out, how can I build my business and somebody figures out how to do that cliché... how to sort that out to happen. R: The fourth participant, please. FGP4: A woman entrepreneur to me it is an interesting one, because I am very passionate about, energising women... there is a definitive movement in the UK at the moment about women finding themselves and being able to find inner confidence about ‘yes’ they can do what they love, they can be flexible, they can work around whether they are busy wives, busy girlfriends, busy mums. There are so many elements and dynamics to this. This is what will power through something that will effectively make a better country. Entrepreneurial success it’s all about being confident that you don’t have to conform. Before always have been boundaries and ... that ‘You can’t!’. Now it is a ‘can do’ attitude. Business growth, I don’t think is down to money. I think business growth is personal, mental and physical, is that you have a confidence not only to believe in yourself, but believing in others and taking others along with you. R: The fifth participant, please! FGP5: Woman entrepreneur is a woman who left a safe paid job to take a risk to set up a business whether as a self-employed or limited company. It is leaving a Job College with a monthly paid package and starting on my own. Entrepreneurial success is being in a place where you are comfortable with your income and what the company is providing to other people. Business growth is hopefully a business, which is not where, was a year ago and might go in many directions...

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Taking your business further and building: (1) survival; (2) making happen; (3) building the business.

Belonging to a movement Having confidence Being flexible

Being dynamic

A ‘I Can Do’ attitude Non conformism Financial growth Personal growth Believing in you and inspiring & motivating others Taking the risk to set up a business Ownership & Independence

Having a good income Providing wages for others or service to clients Being bigger than the last year Developing in various directions

Box 1.1 Developing Emergent Themes – Focus Group (Five Participants) Question Three: How would you evaluate success? Exploratory comments, key words, comments Client positive feedback Personal happiness Reputation Achievement Number of clients Uniqueness Impact on somebody’s life Happiness Contentment Financial stability Personal happiness happiness

client

Original Transcript R: How would you evaluate success? FGP1: Positive client feedback and my own personal happiness. R: The second participant, please. FGP2: Reputation from customer feedback, personal achievement and a number of clients. R: The third participant, please. FGP3: I think creating something that somebody didn’t have before ... add something positive to somebody’s life. R: The fourth participant, please. FGP4: It would be happiness, contentment and financial stable. R: The fifth participant, please. FGP5: Success is that I am happy with the company and ...I want the clients to be happy with me....

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Sub-categories and Emerging Themes Dual aspect of happiness: personal & customer Reputation to attract clients Dual achievement: self & clients

Innovation Positive impact on others’ life Financial stability Contentment Dual aspect of happiness

Box 1.1 Developing Emergent Themes – Focus Group (Five Participants) Question Four: How would you learn and what are your learning preferences in the context of new emerging technologies, such as ICTs, social media like Facebook and Twitter, Smart Phone, iPhones, iPad, Androids, Tablets and computers? What are your preferences for these technologies regarding your learning and their usage for business? What about your style of learning? Exploratory comments, key words, Original Transcript Sub-categories and Emerging comments Themes Daily life FGP1: Yeah, daily life and work life Promotion and communication with Work life on laptop, iPhone, definitively on New Emerging Technologies (NET) Laptop & iPhone social media. It is amazing ... to get Social Media free advertising, free messages to Advertising your clients and to the world. I use Text communication Internet daily them for learning, research, for Clients & the World looking into things. Yeah, I use the internet every day. I use for both learning and business. R: What are your preferences for these technologies, regarding your learning and their usage for business? What about your style of Laptops for business & learning Laptop for learning & business learning? FGP1: I use the laptop for the Styles of learning: traditional Reading business and for the learning. The reading and using technology Using NET style of learning: reading, researching and exploring. I use Learn by using technologies Using most of technologies information technology. Still traditional by reading a book R: The second participant. Reading a book FGP2: The way I learn is by using most of these technologies. I find a Children addicted to NET little worry because I would still like Reading A book is second rate tool to read a book. I think it is very worry all of these, especially, by NET are my learning facilities having an eight-year-old son who is addicted to most of these technologies. I mean is extremely disturbing because this is his way of learning and books are second grade to him... I use Facebook, Twitter, Google, iPhone, iPad, Mac Book Air. I am equally addicted because Technologies they are my main learning facilities. R: The third participant. Using technologies to communicate FGP3: Previously I mentioned that I with family & friends, also clients Social media use all of mentioned technologies, in terms of reaching friends and family Most of the business comes from iPad and Smart Phone and also clients, and not only Facebook and Twitter Laptops existing clients but general Business dependent on NET businesses. A lot of my business Daily Use of iPad, Smart Phone and comes from Facebook, Twitter, and laptop Massive usage of Apple products my website and blogs and all sorts. I use daily the iPad, Smart Phone, that is really important and my Business dependent of Apple Apple product are ‘my life & laptop as well. products oxygen’ R: The fourth participant, please. For promotion FGP4: I think Apple sponsors me. I Communication don’t think I can function more than one night without an Apple product. Business For the Forum/Network I don’t know whether that’s good or bad, but that is my life, my oxygen. Networking with Apple products A Pleasure to be around other It is my only way of promoting women entrepreneurs, meeting and myself other than in a Forum like Meeting & sharing with women talking to them, sharing information this, where it is a pleasure to be entrepreneurs is central to business around human beings, to be & life emotional to talk about, you know about the highs and lows about

435

Reading books Publishing world Creating ideas as a business woman Single mum

Google for learning Blogs

Blogs Career girl

Age I don’t see a value in having an iPad I still prefer books

Social media business

promote

the

Use Facebook for business Two Facebooks: personal Twitter

business

running your own business and about being a woman entrepreneur. But, yes, everything what you think about, whether is Pinterest, LinkedIn, Twitter, Facebook, I probably start my own platform before long. R: Would you choose only online learning or traditional learning, or blended learning? FGP4: No, not at all, because I use ... I am a bookworm. If anything it makes me cross in life is that because I am in publishing world, I don’t have enough time to digest other publications. Why? When I look at it, I am creating ideas, I am thinking like a businesswoman rather than: This is X... a mum, a single mum, who wants to get some luxurious and read a magazine or a book, rather than looking in it as a tool. I am at cross roads at the moment... R: Which one is the best for you? What do you prefer for business and what do you prefer for learning? FGP4: For learning it will always be Google search, I am on Blogger so, I have things regular, every day in the morning. Whose Blog is about some topic I am interested in, that will be a food to me even before I woke up. When I do wake up at four o’clock, because I can’t sleep, because I am so tired, then I will digest myself into something like the career girl Blog. When it comes to learning, I rather learn from inspirational women entrepreneurs, which I am still on a battle to find out, because I am one for younger women. I think is enough there locally to inspire me. R: Thank you. The fifth participant, please! FGP5: Because of my age, probably, I don’t even have an iPad, because I don’t see any value in it. When I did the postgraduate certificate recently at the university in mentoring..... I got books and I actually bought books. I still prefer books. Nowadays, you have to use social media to promote your business, but I do it to storm my children actually. I get much more fun out of this than from when I am using technology for something else. In business I use Facebook. I have two Facebook pages. One is my personal one and one is my work one. I use Facebook and Twitter.

436

Usage for business of platforms such as: LinkedIn, Pinterest, Twitter and Facebook

Referring traditional books to read and learn Dual aspect: New Emerging technologies and Face-to-Face Meetings and Networking with women entrepreneurs Vision To create own Platform

Learning with Blogs Career girl Blog – Role Model Inspirational

Age Lack of value in using iPad Traditional books for learning Social media usage for business Having two Facebook business and personal Using Twitter

pages:

Box 1.1 Developing Emergent Themes â&#x20AC;&#x201C; Focus Group (Five Participants) Question Five: How do you acquire knowledge and information, in the context of networking and new emerging technologies in order to achieve success? Do you belong to any Group, network or Association? Exploratory comments, key words, Original Transcript Sub-categories and Emerging comments Themes Networking Group FGP1: I belong to Business Women Networking Catalyst in X, which is a networking group and was probably, one of the main Taking the risk to start a business Leaving a regular salary catalysts for me, for leaving my own Leaving comfort and a safe job regular salary, income job and jump Start my own business off the plank to start my own Giving confidence business. It gave me the confidence Being inspirational Confidence & Inspiration and inspiration to feel like I can do To balance things in life it, and to balance all things I need Able to balance things in life into my life. I do belong and I find it very important and valuable and an Dual aspect: (1) part of the personal Part of personal and business life important part of my business and life; (2) part of the business personal life. Acquiring knowledge by meeting R: The second participant, please! and talking to people FGP2: I think through people, by talking. I like people, and I am Acquire knowledge by participating Technology interested in people, so through in networks, meeting and talking to conversation, of course. How do I people Social Media, Google and Blogs acquire knowledge? By the previous question, technology: Facebook, Acquire knowledge through new Twitter, Google, reading Blogs and emerging technologies so on. Yes, I belong to women in business in X, as itâ&#x20AC;&#x2122;s now called, which is a networking group and which is another platform for Supportive gaining knowledge, very good and Good supportive platform very supportive. NET important for business success R: Do you think that are important Technologies very important for for the success of your business? business success FGP2: Absolutely! R: The third participant, please! FGP3: I also belong to Belonging to local business women Belonging to Women in Business businesswomen in X, which I only network Networking Group recently joined, but I find really Lovely to connect to others helpful and it is lovely to connect to Helpful other people, who are in the same Belonging to Nation Wide Network Nation Wide Network position... In terms of other sort of Participating in Local Trade Shows networks, I take part of Nation Wide, Go to local trade shows which is (...). I also go to local trade Networking To reach the whole Reaching the world shows. This is how I connect to my world Founder and Chair of Network networks to reach the whole world... R: The fourth participant, please. FGP4: I am the founder and the I was lonely and not sure if I could chairperson for the Women in be successful Business in X. It is very humbling to hear these comments, and it is set up Gaining confidence, moral support, because I was selfish and I needed and encouragement by creating own Platform other women, to feel how I felt, network with women entrepreneurs which was lonely, frustrated and lost and not sure whether I could be Created a platform successful. It is great to see that this Forum platform has become not only a great Great to help others institute for me, but for others as Helping others well. Looking elsewhere, I found Investing to develop own skills Need to invest and develop skills that this year particularly, it is a time to invest and develop my skills, Learning and self-training because I am great in helping others, but I know that to move forward I have to invest in learning and Belonging to Public Speaking training for me. I am a member of Association

437

Attending conferences

Face-to-face more human Online is more sole Gaining online information Personal and business through networking

growth

Networking great way to acquire knowledge Unique

the Public Speaking Association, which is an UK based networking group, which has different forms across the UK, and in Cardiff and I am also attending conferences like L... I am also looking for something new and innovative, to progress women entrepreneurs. R: How important are the new emerging technologies and the networking for business success? FGP4: I find face-to-face more human and personal, that’s where I am like as an individual. Online is a bit more solo, it’s not so transparent. I don’t feel like I connect. I will go there for information, if I needed. But, as an individual, to grow personally and through business I need the one-to-one and group contact. R: Thank you! The fifth participant, please! FGP5: I don’t think that you acquire knowledge for business as much, as you acquire knowledge through others who are around you and what happens locally, which is really important, and a networking group is a great way to do that and make that happen. They could be local or national. I joined many networking groups and all of them are unique, they all offer something more or less and you have to find one that suits you. The new emerging technologies, yes, I heard something new today, that I didn’t know; they keep you update.

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Attending conferences related to own activity Promoting own women networking group Face-to-face meetings are more human Online networking is not transparent

Face-to-face contact and networking impact positively on personal and business growth

Acquiring knowledge through local and national networking Uniqueness New emerging technologies to keep up to date

Box 1.1 Developing Emergent Themes – Focus Group (Five Participants) Question Six: What is your opinion regarding the impact of new emerging technologies and entrepreneurship education on women entrepreneurs’ success? Exploratory comments, key words, comments

The growth of women entrepreneurs Traditionally promoted as male entrepreneurship There is a huge movement of women entrepreneurs Forum Fantastic to see other women doing and achieving Mum’s Network Having a Voice through social media

Women are aware of what happens

Enterprising Curriculum

Resource to be of benefit

Technology is happening today

Original Transcript FGP5: I just did a postgraduate certificate in women entrepreneurship and what was really interesting was the research that came out, because of growth of women entrepreneurs. In the past traditionally have been male and it’s traditionally promoted as male, but in fact there is a huge movement of women entrepreneurs, and again they haven’t marketed themselves much. Therefore, Forum like this is so fantastic, because women can see other women doing and achieving. New emerging technologies, again, Mum’s Network is so fantastic because there are entrepreneurs within network and they chose the power of social media for having a voice. I think women entrepreneurship is growing. R: Are women entrepreneurs influenced by entrepreneurship education and new emerging technologies? FGP5: Through technologies, they seem to be aware of what happens. This never happened in the past. It is very different. R: The fourth participant, please! FGP4: I just think that is evolving actually. Women in business, entrepreneurs, from the moment the young girl starts school, so, the enterprising curriculum that you find in education starts... Being a mum of boys, then you see how keen they are to learn the skills, because they are natural negotiators already, though, I think that is a key opportunity between parents, teachers, university to embrace the fact that we as parents we are also entrepreneurs, and this resource come to be used as a benefit. The technology is just a matter of time, it’s not tomorrow, it’s happening now, you can’t even breath until you see than something new it’s on your radar. I think it is a benefit, the new technology it’s great. But, the new technology it can overpower you, it can crash you, as a person, because you don’t know which way to turn next. That can take up an enormous amount of time and effort, when back in the day, may be in eighties I would have thought, you know

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Sub-categories and Emerging Themes

Traditionally the entrepreneurship has been male designed for male Promoted as male entrepreneurship The emergence of huge movement of women entrepreneurs Seeing other women doing and achieving Fantastic opportunity for women entrepreneurs to meet in such Forum Mum’s Network using Social Media to have a VOICE

Through the power of spreading the information, NET allow women to be aware of what happens

Entrepreneurship education impacted upon the development of young girls in school Enterprising Curriculum

Technology as a resource

Technology is happening Benefit Dual aspect: positive and negative It can empower you

People who technology

won’t

embrace

Technology is not human People need people

You do not need a platform to be successful

Networking brilliant

NET overwhelming

Entrepreneurial in music

what, I probably I would be more successfully until now because I would have been more straightforward. R: What about your opinion regarding women entrepreneurs’ success and its relationship with these two: entrepreneurship education and new emerging technologies? FGP4: There are people who embraced it and there will be those who won’t embrace it because they haven’t got the make up to embrace it. And it’s not by default it’s just the fact that some are very academic and some are very creative. You either embrace something like emerging technologies or you can’t. It doesn’t mean that you are any less of the success, and I think that the new platform that allows people that are more creative...they need more contact, more human conversation, fact-to-face, whether that will be in literature, performing arts. It’s just need to have its moment, because the moment and everything revolves around something that’s not very human. R: The third participant, please! FGP3: I think about what the previous participant was saying, that is not just a model that fits everyone. Not everyone would have a Facebook business page. That’s not always how the things work. Some people purely deal face-to-face, for some people online it is everything. It is learning to be flexible with emerging technologies. But, it is also about understanding that you don’t have to be on every platform to be successful. R: The second participant, please! FGP2: I am very new to entrepreneurship education, I never came across before. The first experience is by having the courage to come to e networking group. I have very small start out and I have no experience of education in terms of entrepreneurship, apart from networking, which has been brilliant. In terms of new emerging technologies, I totally agree with FGP4, I find it is too much choice, too much to digest, which causes confusion and can be totally overwhelming. R: Thank you! The first participant, please! FGP1: I never came across Entrepreneurship education, because I was always employed by organisations, I never had to immerse myself in that area.

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Dual aspect: people who embrace technology; people who does not

Academics versus creative people who do not need technology for achieve success Creative individuals need more faceto-face contact

Technologies will not suit everyone

Being successful without the need of having or being on a technological platform

Networking is brilliant

Technology can be totally overwhelming

Training musicians to be entrepreneurial in view to succeed

Networking for success

However, in an organisation I did work for, we were training musicians, at high education level and to be entrepreneurs in that field, they couldn’t just survive as musicians, they had to be teachers, educators and concert performers. They had to adapt to be entrepreneurs to succeed in that field. I have seen students developing through that course. Regarding the technology, you embrace it or you don’t. ... If you don’t then you have to make your success in other way. If you use technology and social media, then that’s the way of networking and making success. R: Thank you!

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The possibility to be successful without technology Networking is a way of making success

Box 1.1 Developing Emergent Themes – Focus Group (Five Participants) Question Seven: Is gender an issue, either a benefit or a barrier for you as a woman entrepreneur, in the business world? Exploratory comments, key words, comments Gender is not an issue

Enjoying being entrepreneur

woman

It empowers me I get to meet other women I need a balance in my life

Gender not an issue at all, in 2015 Absolutely It is empowering I like to have independence

level

Financial independence Professional independence

Working in construction I came across with a lot of barriers I have to overcome by projecting more confidence I changed my conduct in order to overcome gender barriers

Empowering Working with her husband now Gender it is not an issue for me I love men

Original Transcript FGP1: I don’t think that I even considered it as an issue because I am running a business... R: Do you enjoy being a woman entrepreneur? FGP1: Yeah, definitively. R: Why? FGP1: Because it empowers me. It means I get to meet other women, who are doing amazing things, who are inspirational, and I can balance what I need to balance in my life, on my terms. R: The second participant, please! FGP2: I don’t think that gender is an issue at all! In 2015 I don’t think that women struggle to be recognised today, at all. R: Do you enjoy being a woman entrepreneur? Why? FGP2: Yes, absolutely! Because it is empowering and makes me feel independent, like I always wanted to have a level of independence, regardless the fact that I am married. I always wanted to stand on my own two feet. In terms of financial, professional, in every capacity I want to be independent as a woman. R: The third participant, please! FGP3: For me it’s never been a barrier, but working in constructions I have come across with a lot of barriers in that respect, that I have to overcome. Being a young woman and going to contractors, things like that, maybe I have to project myself as being more confident than I actually am, in order to overcome. I change the way I conduct myself, in certain situation that I may overcome these gender barriers. It has worked...for me, because it made me more distinctive and it’s great. R: Do you enjoy being a woman entrepreneur? Why? FGP3: Yes, I do! It’s empowering and it’s fantastic. The thing is that my husband left the job back in March, and he works not for me but with me and we managed to sort that out. R: The fourth participant, please! FGP4: It is not an issue for me. I absolutely love men, I love what they are about and I love the way that women and men can connect, and there are sometimes negative times and positive times. I think this is just

442

Sub-categories and Emerging Themes Gender is not an issue

Being a woman entrepreneur it empowers me Meeting with other women

Needed a balance in my life Gender is not an issue

Enjoying being woman entrepreneur It is empowering me Having independence Being financially independent

Gender is a barrier in construction and I needed to change conduct to overcome gender barriers

Needing To show more confidence

Being a woman entrepreneur it is empowering

Gender is not an issue

I have the best tutoring from men

I came across with strong opinions about why men cannot join.

I try to balance the barriers and glass ceiling Drive this forward and be a voice internationally

I enjoy being a woman entrepreneur because it is my oxygen

It is a lifelong balance

Gender it is still an issue Therefore women are still in groups

Men patronized me In the past the research never included us as an element, of being entrepreneurs Gender has an impact upon business growth and what you achieve

the behaviour of being in the relationship with men, whether that’s personally or professionally. I have some of the best tutoring time from men and being a chair person for the women business group. I came across with a lot of challenges and very strong opinions about why can’t men join. What I can do I promised that when we have some guests speakers, they will be men, who are very well educated in the fact that women are not shy coming forward, they have the right equal to their male counterparts to set their own business. We are better as a team as men and female. We try to balance these barriers and glass ceiling, because so much media has been out there, we have to believe locally that we can drive this forwards, nationally will be effective and then internationally will be a voice. R: Do you enjoy being a woman entrepreneur? Why? FGP4: It’s my oxygen; I don’t know why I took so long to become a female entrepreneur... I think I was put on this planet to go and become to go into the corporate sector first, to learn from my mistakes and set my own business and to the point where I set up many businesses and I was.... and I started all over again.... It is tough but you excel in what you believe. When you find your passion in life...It is a lifelong balance. R: The last participant, please! FGP5: I still think that gender it is an issue. It is why the women are still in groups, because I have been in groups where I have been patronized by male....I have got three girls and...Gender is an issue! Yeah, I love men, but they patronized me. I am in business to make my own business. Do I enjoy being a woman entrepreneur? ...In the past research has never included us as an element, of being entrepreneur.Now it is beginning to be accepted and I realize that you can’t ignore it as a factor of life. It does have an impact on how your business grows and how you manage to achieve what you achieve.

443

Came across with challenges when created women only network

Still barriers and glass ceiling

Needed to have an international VOICE Being a woman entrepreneur is like ‘oxygen’

Set my own business

It is a lifelong balance

Gender is an issue Therefore women gather in groups Men patronizing

Past research ignored women entrepreneurship in the past The research began to accept women entrepreneurs Gender has an impact upon business growth and what you achieve

Box 1.1 Developing Emergent Themes – Focus Group (Five Participants) Question Eight: What is your opinion regarding the impact of networking and business associations for learning and business success? Exploratory comments, key words, Original Transcript Sub-categories and Emerging comments Themes Networking is crucial FGP1: It is crucial, it is how I learn. Crucial. Networking is crucial for Learning from other businesses and It’s my clients, how I learn about learning about how other business about other businesses how other businesses are doing, how are doing I can be involved in that... R: The second participant, please! FGP2: I have not much experience in networking at all, this is the first group I have ever been to, but in Crucial in terms of learning terms of learning and success, it is absolutely crucial for me. For Energizing example I came to this meeting. I Amazing platform felt low, deflated, lost. I walk here and I am feeling so much better, it is such an amazing platform. It is not Support only learning and success, but it is Supporting also a support network. I am really A lot of energy glad that I found it. R: The third participant, please! FGP3: It’s really great to be in a Trials and tribulations room with a lot of energy and with Energy people who got a kind of similar ideas and trials and tribulations as Trials and tribulations Confidence well. It is a kind of safe environment which gives you the confidence to go Giving confidence out and say ‘I can do this!’ and also a good thing for nurturing. Encouraging female to network R: The fourth participant, please! FGP4: It is one of my goals in life to Encouraging women entrepreneurs try and encourage more female to to network Energy, love, sisterhood, friendship network. I feel like I am trying to champion something, at the local Finding energy, love, friendship level, because I can feel the energy, Transparent the love, friendship, sisterhood, being alone from North Wales, a Being transparent single mum and trying my best to create a new business. I have been Invigorated transparent as much as I can...It is invigorated, passion, creativity...What is beautiful is that you create such a friendship. We are not in business for business, but we are in business for us and for our friends and our family. I had to network immediately to R: The fifth participant, please! Networking is essential for promote myself FGP5: I set up my company in 2007 promotion and immediately I had to network, because is a way of promoting Various types of network Male dominated networks myself and do the marketing. There are many types of networking and I did not enjoy in male dominated Women only networks you find one that suits you. I have networks been to male dominated networks, which I haven’t enjoy ... I prefer I prefer women only networks women only, and this is very local, it is wonderful to find out what is happening locally. But I will also join a network when my book is published, the RNA, which is a

444

national association to improve my skills in the field I am working. I think women have to find more than one network and use them in different ways to help the business. R: Thank you! Interview terminated.

445

Needing to have more than a network to use them to help the business

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