Ijebea15 437 by iasir journals

International Association of Scientific Innovation and Research (IASIR) (An Association Unifying the Sciences, Engineering, and Applied Research)

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International Journal of Engineering, Business and Enterprise Applications (IJEBEA) www.iasir.net IMPACT OF STRAIN-BASED CONFLICT ON THE WORK-LIFE BALANCE AMONG BANK EMPLOYEES Dr. Anil. K. Bhatt Professor, Pacific Institute of Business Studies, Udaipur, Rajasthan, India. E-mail: anilbhatt_ndhn@yahoo.com & Chandani Goyal Research Scholar, Pacific University, Udaipur, Rajasthan, India. _________________________________________________________________________________________ Abstract: Work-life balance is about creating and maintaining supportive and healthy work environments, which will enable employees to have balance between work and personal responsibilities and thus strengthen employee loyalty and productivity. The work-life, or work-family, balance is a frequently cited phenomenon. The current study assumes that bank workers may be more prone to imbalance effects than other groups of employees as workers frequently face extended work schedules and unrealistic deadlines. Results conclude that bank employee strongly believes that tension and anxiety from work often pinch into their personal and family life and they often feel emotionally drained when get home from work that prevents them from contributing to family life. Keywords: strain, work life conflict, banking sector __________________________________________________________________________________________ I. INTRODUCTION Balance is the key to lead a successful and beautiful life which includes everything but in balance. It is important in everyone’s life be it in the life of an entrepreneur, student or a housewife to maintain a balance between various aspects of their daily routine. A student must know how to balance between his studies and curricular activities; otherwise he will fail in one or the other thing (Global Research Analysis). Our life has so many things to deal with, like our relationships, work, health, entertainment , responsibilities for family and country etc. and to be successful in all these aspects, we must know how maintain balance between all of them. The topic of life balance starts from and has been mostly discussed in applied psychological disciplines such as work or family psychology. Theories and approaches within social psychology and personality psychology (e.g., Personality Systems Interaction Theory, Kuhl, 2001; the Self-Concordance Model within Self-Determination Theory, Sheldon & Elliot, 1999) provide a useful framework to explain several findings of life balance research. As noted above, the approach of life balance was initially conceived in terms of work-family balance (e.g., Hill, Hawkins, Ferris, & Weitzman, 2001) or work-family conflict (Kahn, Wolfe, Quinn, Snoek, & Rosenthal, 1964). Work-family balance was defined as the degree to which an individual is able to simultaneously balance the temporal demands of both paid work and family responsibilities, whereas work-family conflict represented incompatibilities between work and family responsibilities because of limited resources like time and energy. However, the work-life system is multi- and not just two dimensional (Seiwert 2000, 2001). We have to deal with more than two domains when we speak about life balance. Warren (2004), for example, notes that over 170 different life domains have been identified in previous investigations. The major ones include domains of work, financial resources, leisure, dwelling and neighborhood, family, friendships, social participation and health. Seiwert (2000, 2001) distinguishes apart from work and family two other life domains – health and meaningfulness of life – that are important in human life as well. His approach is based on the intercultural research that identified four domains as the most important areas of life. These represent the main factors which reflect the multidimensionality of life. The life areas are: (1) work/achievement, (2) social contact/relationships, (3) health/body, and (4) meaningfulness of life. II. LITERATURE REVIEW Greenhaus and Beutell (1985) describe that strain-based conflict occurs when the strain created in one role makes it difficult to meet the expectations of another role. It can lead to both adverse physical and psychological states that spill over into other areas of an employee’s life (Edwards & Rothbard, 2000). Additionally, Batt and Valcour (2003) found that usage of technology is significantly associated with work-life conflict. This is of IJEBEA 15-437; © 2015, IJEBEA All Rights Reserved

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Anil. K. Bhatt et al., International Journal of Engineering, Business and Enterprise Applications, 14(1), September-November, 2015, pp. 3034

particular concern to IT workers because their jobs may require them to plug into devices more regularly than other. An additional element of conflict is role ambiguity, which happen when an employee is unsure of their job demands and the boundaries for their positions, leading to strain-based conflict (Boyar et al., 2008). Role ambiguity can be particularly problematic for IT personnel because of their boundary-spanning activity. Many IT professionals like system analysts and designers perform in a great deal of boundary spanning, as their positions require them to interact with end users, developers, marketers, vendors and suppliers (Michel et al., 2011; Goswami, 2014). Studies from Baroudi (1985) and Guimaraes (1992) found that higher levels of role ambiguity were associated with turnover intentions, lower levels of job satisfaction and less organizational commitment among IT workers. The role of Work Place support has consistently emerged in literature as an important factor that influences work-family balance in a positive manner. Low levels of leader or supervisor support and interaction facilitation appear to produce work family conflicts (Jones & Butler, 1980, Chouhan et.al, 2013; 2014a; 2014b). Social support from the work domain was measured as organizational support is related in reduction of work-life conflict (Eisenberger et al., 1986; Foley et al., 2005). Moreover, Ezra and Deckman (1996) found that organisational family friendly policies and supervisor understanding of family duties are positively related to Job satisfaction. III. METHODOLOGY To the best of researcher knowledge, there are very few other studies in the context of the Indian banking industry, which attempt to capture the unique dimension on managing life and work responsibilities. The study was based on an employee questionnaire distributed to select public and private banks in Rajasthan state. The respondents were selected using convenience sampling from eight different organisations. The total number of respondents contacted was 175, but due to incomplete responses and other faults, the final responses subjected to data analysis were 160. The high response rate of 94 percent was the effect of the constant direct contact and reminders between employees and researcher. Following hypothesis has been formulated to attain research objectives. H1: Factors identified for work life conflict significantly explain for the imbalance. Statistically tools like Regression analysis is used for determining the major predictors of imbalance and correlation for understanding the type of association between work-life balance and employee’s organization commitment. The present study followed both exploratory and descriptive research approach. Exploratory research is carried out via review of existing literatures in formation of Hypothesis. Further descriptive research approach is used to test the hypotheses and present conclusions from data analysis. The present study uses quantitative approach of problem solving. Data Collection Tool: All selected employees within the eight banks received a survey questionnaire as part of data collection process Data Collection period: Surveys were distributed directly to employees over a three month period during March 2015 to May 2015. Piloting testing: The piloting strategy is used for this survey. Cognitive testing seeks to understand the thought processes that a respondent uses in trying to answer a survey question. The aim is to see whether he/she understands both the question as a whole and any key specific words and phrases it might contain, what sort of information is needed to retrieve in order to answer the question. IV. MEASURES Control variables like age, gender, household status (single or joint family), dependent responsibilities, work experience and management level were measured as either dichotomous or nominal variables. While one of the objectives of this was to understand the sample characteristics and other is to conduct analysis in the demographic context to understand the variation in the behavior manifestation by people with different demographic background. Multiple items were considered to be more reliable measures for the present sample. Dependent variable of organisational commitment was measured using two scale items of Allen and Meyer’s (1990). Independent variables like Work-life boundary flexibility was measured as the supportiveness of the immediate supervisor, time flexibility for personal demands and whether employees were expected to sacrifice non-work commitments for career progression in the company. Majority of scale items for work-to-non-work imbalance is adopted from Greenhaus and Beutell’s (1985) dimensions of strain and time-related worklife spillover. The respondents were asked to rate different items capturing their perception using a 5-point likert type scale where 5 indicated Strongly Agree while 1 represented Strongly Disagree. Major sources and Cronbach alphas values of scale reliability for different scales are presented in Table 1.

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Anil. K. Bhatt et al., International Journal of Engineering, Business and Enterprise Applications, 14(1), September-November, 2015, pp. 3034 Table 1: Construct Table Scale Items (with codes used in SPSS)

Conflict sources Strain conflict



based

   Work Imbalance



Life



When I get home from work I am often feel physically exhausted to participate in family activities. (Strain1) The stress from my job often makes me irritable when I get home. (Strain2) Tension and anxiety from work often pinch into my family life. (Strain3) I often feel emotionally drained when I get home from work that prevents me from contributing to my family. (Strain4) My work often interferes with my family responsibilities. (WLB1) I am not able to maintain an appropriate and healthy balance between my work and personal commitments. (WLB2)

Major Source Stephens and Sommer (1996), Edwards & Rothbard (2000), Greenhaus and Beutell (1985)

Greenhaus and Beutell (1985)

Cronbachs’ Alpha 0.836

0.892

Characteristic wise respondents profile is presented in table below and briefly discussed to better understand the characteristics and other company policies regarding work life balance. Table-2: Sample Demographics Characteristics

Category

Percent

Age

20-25 26-35 >36 Male

23% 52% 25% 50%

Female 1-2 year 2-5 year >5 year Junior Middle

50% 14% 42% 44% 57% 43%

Gender Work Experience

Management Level

Table 3: Regression result

Mean WLB Strain1 Strain2 Strain3 Strain4

Pearson Correlation

WLB Strain1 Strain2 Strain3 Strain4 WLB Strain1 Strain2 Strain3 Strain4 WLB Strain1 Strain2 Strain3 Strain4

Sig. (1-tailed)

Model 1

Variables Entered Strain1

Strain2

Descriptive Statistics Std. Deviation N 2.9313 1.02253 160 3.4250 1.13575 160 2.7063 1.06160 160 2.6938 1.06397 160 2.5563 1.04458 160 Correlations WLB Strain1 Strain2 Strain3 Strain4 1.000 .589 .485 .472 .525 .589 1.000 .402 .488 .579 .485 .402 1.000 .633 .579 .472 .488 .633 1.000 .709 .525 .579 .579 .709 1.000 . .000 .000 .000 .000 .000 . .000 .000 .000 .000 .000 . .000 .000 .000 .000 .000 . .000 .000 .000 .000 .000 . 160 160 160 160 160 160 160 160 160 160 160 160 160 160 160 160 160 160 160 160 160 160 160 160 160 Variables Entered/Removeda Variables Removed Method . Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100). . Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100).

a. Dependent Variable: WLB Model Summary

Model 1

R R Square .589a .346

Adjusted R Std. Error of the Square Estimate .342 .82929

Change Statistics R Square Change F Change df1 df2 Sig. F Change .346 83.729 1 158 .000

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Anil. K. Bhatt et al., International Journal of Engineering, Business and Enterprise Applications, 14(1), September-November, 2015, pp. 3034 2 .648b .420 a. Predictors: (Constant), Strain1 b. Predictors: (Constant), Strain1, Strain2 Model 1

.413

.78346

Sum of Squares 57.583 108.661 166.244 69.875 96.369 166.244

.074

ANOVAc df

Regression Residual Total 2 Regression Residual Total a. Predictors: (Constant), Strain1 b. Predictors: (Constant), Strain1, Strain2 c. Dependent Variable: WLB

20.025

Mean Square 57.583 .688

1 158 159 2 157 159

157

34.937 .614

.000

Sig. 83.729

.000a

56.918

.000b

Coefficientsa

Model 1 (Constant)

Unstandardized Standardized Coefficients Coefficients B Std. Error Beta 1.116 .209

Strain1 .530 (Constant) .710 Strain1 .423 Strain2 .286 a. Dependent Variable: WLB 2

.058 .217 .060 .064

t Sig. 5.345 .000

.589 .469 .297

9.150 3.269 7.074 4.475

Correlations Zero-order Partial

.000 .001 .000 .000

Part

Collinearity Statistics Tolerance VIF

.589

1.000

.589 .485

.492 .336

.430 .272

.839 .839

1.192 1.192

Excluded Variablesc Model 1

Beta In t Strain2 .297a 4.475 Strain3 .242a 3.395 Strain4 .277a 3.644 2 Strain3 .103b 1.238 Strain4 .156b 1.863 a. Predictors in the Model: (Constant), Strain1 b. Predictors in the Model: (Constant), Strain1, Strain2 c. Dependent Variable: WLB

Sig. .000 .001 .000 .217 .064

Partial Correlation .336 .262 .279 .099 .148

Collinearity Statistics Tolerance VIF Minimum Tolerance .839 1.192 .839 .762 1.313 .762 .665 1.504 .665 .534 1.871 .534 .522 1.917 .522

Collinearity Diagnosticsa Model 1

Dimension 1 2 2 1 2 3 a. Dependent Variable: WLB

Eigenvalue 1.949 .051 2.874 .075 .051

Condition Index 1.000 6.211 1.000 6.170 7.543

(Constant)

Variance Proportions Strain1 .03 .03 .97 .97 .01 .01 .16 .20 .83 .79

Strain2

.01 .99 .00

Information in the Model summary Table above (table 3) the last row indicates that the value of R-square for the model is 0.420. This means that 42.0 percent of the variation in the Work Life Balance among the respondents. In general, R square always increases as independent variables are added to a multiple regression model. To avoid overestimating the impact of adding an independent variable to the model, some analysts prefer to use the adjusted R-square value (it recalculates the R-square value based on the number of predictor variables in the model). This makes it easy to compare the explanatory power of regression models with different numbers of independent variables. The adjusted R-square for the model is 0.413, which indicates only a slight overestimate with the model. It has been clear from the ANOVA table that the regression model is statistically significant (F ratio=56.918, probability level 0.000). The probability level 0.000 means that the chances are almost zero that the results of regression model are due to random events instead of a true relationship. Information provided in the coefficients table tells us, which of the independent variables are significant predictors in nourishing the WLB in banking sector. In the significance column, it can be concluded that beta coefficients for Strain 3 and Strain 4 are significant. The sign associated with coefficients shows that the association between independent variable and dependent in Positive (Chandra et.al, 2012). It can be concluded that strain conflict factors are statistically significant to predict the WLB in banking sector. Employee strongly believes that tension and anxiety from work often pinch into their personal and family life (Strain3) and they often feel emotionally drained when get home from work that prevents them from contributing to family life (Strain4). V. CONCLUSION These results are important for practical attempts to retain skilled and experienced employees. A flexible approach towards managing employeesâ&#x20AC;&#x2122; work-life boundary, particularly if it is not at the expense of career progression, may be especially important for high-status workers who value their freedom and continuing IJEBEA 15-437; ÂŠ 2015, IJEBEA All Rights Reserved

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Anil. K. Bhatt et al., International Journal of Engineering, Business and Enterprise Applications, 14(1), September-November, 2015, pp. 3034

employability in the field and who carry substantial power in shaping their terms and conditions in tight labour markets(Chouhan et.al, 2013; 2014). Work-life balance aided by one’s employer may represent an important dimension of perceived fair treatment, similar to perceived fairness with respect to pay or provision of training opportunities. This is consistent with arguments that employer flexibility in HR issues generally can play a role in the formation of the psychological contract between employers and high-status employees. Managerial people should feel that if they support the executives and non executives wholeheartedly the achievement of the mission of the organization be facilitated and compensation should be providing on the basis of team performance. Although the female respondents agreed with banks WLB policies but they disagreed with overall WLB. So the female employees should be given the facilities like flexi time; job sharing; creche facilities, and necessary breaks so that they feel that the organization is helping them in coordinating the family and professional life. REFERENCES [1] [2] [3] [4]

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