The European Journal of Applied Economics - 2022 - Vol 19 No 2

Assessment of the Impact of Circular Economy Competitiveness and Innovation on European Economic Growth pp. 1-14

Rewarding Top Managers in the Banking Sector During the Covid 19 Pandemic pp. 15-27

e Levels of Arti cial Intelligence Application in Human Resource Systems pp. 28-42

e Impact of Covid-19 on Household Consumption Expenditure in South Africa: A Macroeconomic Perspective: Impact of Covid-19 on Households' Consumption in South Africa pp. 43-53

Organizational Culutre in Smes: An Investigation of Managers Vs Employees’ Perceptions pp. 54-70

Prediction of Gold Price Movement Considering the Number of Infected With the Covid 19 pp. 71-83

Online learning during the pandemic of COVID-19: Experiences of students and universities pp. 84-96

Financial analysis of the broadcasting service of digital television, radio programs and data transmission in the Republic of Serbia pp. 97-113

Employees: Case Study in Serbian Hotel Industry pp. 114-128

Using Open Government Data for Economic Development pp. 129-141

Vol. 19 No. 2

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1 - 14

CONTENTS

Assessment of the Impact of Circular Economy Competitiveness and Innovation on European Economic Growth

Andrija Popović, Maja Ivanović-Đukić, Ana Milijić 15 - 27

Rewarding Top Managers in the Banking Sector During the Covid 19 Pandemic

Miloš Ilić, Vinko Lepojević 28 - 42

The Levels of Artificial Intelligence Application in Human Resource Systems Teodora Ćormarković, Lazar Dražeta, Angelina Njeguš 43 - 53

The Impact of Covid-19 on Household Consumption Expenditure in South Africa: A Macroeconomic Perspective: Impact of Covid-19 on Households' Consumption in South Africa

Remembrance Hopeful Chimeri, Isaac Busayo Oluwatayo 54 - 70

Organizational Culutre in Smes: An Investigation of Managers Vs Employees’ Perceptions

Ivona Mileva, Snezhana Hristova

- 83

Prediction of Gold Price Movement Considering the Number of Infected With the Covid 19

Jovana Stokanović Sević, Ana Jovancai Stakić

- 96

Online learning during the pandemic of COVID-19: Experiences of students and universities

Ilija Savić, Slavko Alčaković

- 113

Financial analysis of the broadcasting service of digital television, radio programs and data transmission in the Republic of Serbia

Jelena Cerovina, Ivana Milošević, Milan Simić

- 128

Work-Life Balance and Work-Related Attitudes of Employees: Case Study in Serbian Hotel Industry

Jasmina Ognjanović, Aleksandra Mitrović

Using Open Government Data for Economic Development

- 141

Nevena Petrović, Petar Milić, Bojan Prlinčević

EJAE 2022, 19(2): 1 - 14

ISSN 2406-2588

UDK: 338.12.021(4) 330.341.1

DOI: 10.5937/EJAE19-39057

Original paper/Originalni naučni rad

ASSESSMENT OF THE IMPACT OF CIRCULAR ECONOMY COMPETITIVENESS AND INNOVATION ON EUROPEAN ECONOMIC GROWTH

Andrija Popović*, Maja Ivanović Đukić, Ana Milijić

University of Niš, Innovation Center, Niš, Serbia

Abstract:

The world usage of raw materials is 70% higher than what the Earth can safely renew. Circular Economy represents a new model of economic development relying on the 7Rs (redesign, reduce, reuse, repair, renovate, recycle, and recover) to provide operational and strategic benefits on the micro, meso, and macro levels. This research aims to determine the impact that circular economy competitiveness and innovation have on economic growth within European countries by evaluating the impact of four independent variables selected from the European Commission Circular Economy monitoring framework on the GNI per capita. This paper analyses the competitiveness through Values Added at Factor Cost (VAFC), Gross Investment in Tangible Goods (GITG), and Number of Employees (EMP) in Circular Economy, innovation through the Number of Patents in climate change mitigation technologies related to wastewater treatment or waste management (PAT), while the economic growth was estimated based on the GNI per capita annual growth rate (GNIpc). Correlation and regression methods were applied to the sample of 25 European countries using the log-transformed data. The results show that the correlation between VAFC and GNIpc is moderate and significant but negative, while the correlation between GITG and EMP and GNIpc is not statistically significant.

Article info: Received: Jul 08, 2022

Correction: August 05, 2022

Accepted: August 08, 2022

Keywords: Circular economy, Competitiveness, Economic development, Sustainable development, Europe.

JEL Classification: O440, Q01, Q56

INTRODUCTION

Throughout the last 150 years of industrial evolution, a linear production and consumption model, in which goods are produced from raw materials, sold, exploited, and then discarded or incinerated, has dominated the global economy. Since the global climate change conference in Paris in 2015 and the Glasgow conference in 2021, 70% more raw materials have been extracted than the Earth's capacity to safely renew them (Circle Economy, 2022). A new economic model has become essential as the world faces increasing volatility in the global economy and signs of resource depletion.

*E-mail: andrija.m.popovic@gmail.com

As an alternative model, the Circular Economy offers operational and strategic benefits at both the micro and macroeconomic levels. Driven by the technological advancements in Industry 4.0, this transformation represents an opportunity with enormous potential for innovation, job creation and economic growth (EMF, 2013; WEF et al., 2014; Popović, 2020). The Circular Economy represents a systemic approach to economic development, designed to contribute to all socio-economic subjects. Unlike the linear model, the Circular Economy is meant to be regenerative by design and aims to incrementally decouple growth and development from the consumption of finite resources (EMF, 2022). Circular Economy aims to make the most of the material resources available to us by applying the seven principles ("7Rs"): redesign, reduce, reuse, repair, renovate, recycle, and recover. The idea stems from the imitation of nature, where everything has value, and everything is used, and where waste becomes a new resource. In this way, the product's life cycle is extended, waste is utilised, and, over time, a more efficient and sustainable production model is established. Thus, the balance between progress and sustainability is maintained (REPSOL, 2022).

The European Commission has estimated that the manufacturing sector of the European Union (EU) would gain an additional 600 billion euros annually from the transition to a circular economy (Korhonen et al., 2018). The Circular Economy currently contributes to job creation and economic growth in Europe, and the development of innovative technologies improves product designs for more accessible reuse and promotes innovative industrial processes (EC, 2022). Multiple authors and organisations have tackled the subject of the impact that the Circular Economy has on overall development and growth worldwide or within particular countries, but all have remained theoretical in nature or relied on ad hoc evaluation models (Yuan et al., 2006; Mathews & Tan, 2016; Domenech & BahnWalkowiak, 2019; Chateau & Mavroeidi, 2020; EMF, 2022). Furthermore, the research focused on the effects of competitiveness and innovation in the Circular Economy in Europe is extremely scarce and intertwined with more complex questions. Thus, it is necessary to evaluate the impact of particular elements of the Circular Economy on many aspects of development, particularly on economic growth.

The notion that Circular Economy will provide strong effects on innovation, job creation and growth is widely accepted even though today, data for confirming these effects is scarce and ununiformed. In Europe, it is especially significant to determine the relations between competitiveness and innovation in the Circular Economy, on the one hand, and economic growth, on the other, to provide investments and funds for the most impactful areas of the economy.

This paper aims to improve understanding of the impact the Circular Economy competitiveness and innovation have on economic growth. Relying on the European Commission Circular Economy monitoring framework indicators, this paper will estimate the correlation between competitiveness and innovation in the Circular Economy and the economic growth within European countries (EC, 2022). Additionally, a linear regression model will be developed to estimate the combined impact of the selected independent variables on the economic growth measured by the GNI per capita growth rate within Europe.

EJAE

A.,

M., MILIJIĆ. A.

ASSESSMENT OF THE IMPACT OF CIRCULAR ECONOMY COMPETITIVENESS AND INNOVATION ON EUROPEAN ECONOMIC GROWTH

LITERATURE REVIEW

In the 1970s, the ecological economist Boulding and the political economist Thomas Malthus intro duced the concept of limitations to growth for the first time (Popović & Milijić, 2021). Some authors and influential international institutions introduced growth's social and environmental dimensions based on their fundamental conclusion that limited resources do not provide an endless supply of fuel for growth under the linear production model (Sverko Grdic et al., 2020; Popović, 2020). While circularity was introduced in the 1970s, multiple authors credit Pearce and Turner (1989) with the concept of the linear economy being substituted by the circular system (Ghisellini et al., 2016; Sverko Grdic et al., 2020; Popović & Milijić, 2021). They examined and explained the role of natural resources on both sides of linear production, making it necessary to evaluate and utilise the economy's circular flow of matter. Today, there are over a hundred definitions of the circular economy (Kirchherr et al., 2017). However, the most widely accepted definition is that of the Ellen MacArthur Foundation, which defines a Circular Economy as "an industrial economy that aims to rely on renewable energy; minimises, tracks, and eliminates the use of toxic chemicals; and eliminates waste through careful design" (EMF, 2013, p.22).

Within the last two decades, both theoretical and empirical research focused on Circular Economy provided frameworks, guidance, and models for faster and more effective implementation of the concept. However, the ad hoc implementation and evaluation of its effects on economic growth and development leave much room for research on both micro and macro levels.

Theoretical discussions about the effects, potential, advantages, limitations, and measurement of the Circular Economy comprise the main body of research within the last two decades (Kirchherr et al., 2017; Geissdoerfer et al., 2017; Berg et al., 2018; Esposito et al., 2018; Korhonen et al., 2018; Martinho & Mourao, 2020; Marković et al., 2020). However, starting with China's experiment with a Circular Economy (Yuan et al., 2006; Geng et al., 2013; Chen et al., 2020), empirical research within the last decade is providing a better understanding of how a Circular Economy can benefit national, regional and world economies (Berg et al., 2018; Bogovitz & Sergi, 2019; Domenech & Bahn-Walkowiak, 2019) as well as individual economic subjects such as corporations and SMEs (Leider & Rashid, 2016; Busu & Nedelcu, 2017; Esposito et al., 2019).

Even though there is no consensus regarding the definition and measurements of the Circular Economy, there were several attempts to assess the impact of the Circular Economy based on the available SDG indicators (UN, 2015), EC indicators (EC, 2022), and other regional or national indicators meant for the assessment of the waste management, energy efficiency, production, and consumption. Some authors focused on indicators from separate datasets, such as eco-innovation (Smol et al., 2017). Others focused on indicators representing particular segments of the Circular Economy, such as waste management and energy efficiency, while a small group of authors tried to provide a comprehensive analysis of the impact of the Circular Economy (Hysa et al., 2020). Most recently, Karman and Pawlowski (2021) created the Circular Economy Competitiveness Index as a comprehensive indicator showing the impact of this new concept on the world economy.

Advances in theoretical and empirical research are creating the necessary basis for the fundamental transformation of the world economy. However, the research is still lacking in assessing the impact of particular segments, such as secondary raw materials, competitiveness, and innovation brought by the Circular Economy, on socio-economic development. This paper aims to narrow the gap by evaluating the available indicators and their adequacy for statistical modelling, as well as developing the model for assessing the impact of competitiveness and innovation on economic growth in Europe.

POPOVIĆ. A., ĐUKIĆ. I. M., MILIJIĆ. A.  ASSESSMENT OF THE IMPACT OF CIRCULAR ECONOMY COMPETITIVENESS AND INNOVATION ON EUROPEAN ECONOMIC GROWTH

METHODOLOGY

This paper aims to provide insight into the impact that competitiveness and innovation brought by the Circular Economy have on the economic growth within European countries. For this purpose, the research relies on quantitative and qualitative approaches to analyse the secondary data collected from the EC Circular Economy Monitoring Framework (EC, 2022) and World Bank Database (WB, 2022).

For the purpose of this paper, four indicators related to the Competitiveness and Innovation thematic area will be used treated as independent variables (IV), and Gross National Income growth (Annual %) as an indicator of economic growth will be used as the dependent variable (DV). Keeping in mind the limitations of statistical data for Circular Economy indicators, the paper will use 2016 as the most recent year for which all of the indicators have representative values.

Independent variables (IV) that will be used in the analysis are (EC, 2022):

Value-added at factor cost - thousand euro - (VAFC)

Gross investment in tangible goods - thousand euro - (GITG)

Persons employed – number - (EMP)

◆

Number of Patents in climate change mitigation technologies related to wastewater treatment or waste management - (PAT)

The dependent variable (DV) that will be used for the purpose of the analysis is (WB, 2022):

◆

Gross National Income per capita growth (Annual %) (GNIpc)

The dataset used for the purpose of this analysis is presented in Table 1. Seven countries (Czech Republic, Estonia, Ireland, Luxembourg, Malta, Slovenia, Switzerland, the United Kingdom, North Macedonia, and Turkey) were excluded due to the complete lack of statistical data.

Table 1. Used dataset.

Countries VAFC in 000 € GITG 000 € Employees Patents GNIpc

Austria

3,705,500.00 291,700.00 64,629.00 3.86 0.023

Belgium 2,926,400.00 631,800.00 51,999.00 14.65 0.010 Bosnia and Herzegovina 153,300.00 14,900.00 14,062.00 0.00 0.039 Bulgaria 539,100.00 86,900.00 60,952.00 0.00 0.037 Croatia 568,400.00 51,300.00 35,094.00 1.66 0.018

Cyprus 162,100.00 10,700.00 7,671.00 0.00 0.023

Denmark 2,319,600.00 250,300.00 39,109.00 5.50 0.014

Finland 2,025,600.00 214,100.00 41,794.00 10.50 0.019

France 19,466,300.00 222,800.00 419,989.00 35.53 0.011

Germany 31,246,300.00 2,809,200.00 641,345.00 66.53 0.022 Greece 616,800.00 66,400.00 67,528.00 1.00 -0.001

Hungary 1,040,200.00 194,600.00 85,943.00 3.50 0.051

Iceland 241,100.00 222,800.00 3,883.00 0.00 0.023

OF

OF

AND INNOVATION ON EUROPEAN ECONOMIC GROWTH

Countries VAFC in 000 € GITG 000 € Employees Patents GNIpc

Italy 18,019,700.00 2,201,400.00 510,145.00 14.12 0.033

Latvia 251,400.00 68,000.00 25,614.00 1.00 0.056

Lithuania 406,500.00 53,100.00 36,879.00 0.00 0.051

Netherlands 5,614,400.00 857,700.00 105,763.00 15.69 0.001

Norway 3,720,400.00 390,400.00 52,282.00 0.00 -0.029

Poland 4,830,000.00 716,800.00 355,643.00 45.01 0.029

Portugal 1,413,200.00 222,800.00 84,756.00 0.00 0.033

Romania 1,280,900.00 333,300.00 132,908.00 3.00 0.050

Serbia 267,500.00 117,300.00 26,437.00 0.00 0.029

Slovakia 623,500.00 133,800.00 40,890.00 0.13 0.012

Spain 11,464,300.00 977,500.00 384,753.00 29.09 0.033

Sweden 4,110,300.00 656,100.00 76,485.00 5.01 0.006

Source: EC (2022) and WB (2022).

The essential hypotheses tested through this research can be expressed as follows:

H1. There is a statistically significant correlation between competitiveness in a circular economy and economic growth measured by GNIpc.

H2. There is a statistically significant correlation between innovations in Circular Economy and economic growth measured by GNIpc.

H3. Competitiveness and innovation in the Circular Economy have a significant impact on the economic growth in European countries.

Based on the selected indicators, the research in this paper is structured as follows:

1. Normality assumption evaluation, data selection and transformation

2. Correlation analysis between selected indicators

3. Multiple Linear Regression and Model Development

The first step of the research is the evaluation of the normality assumption necessary for correlation analysis and multiple linear regression. Based on the data provided by the Shapiro-Wilk test (Shapiro & Wilk, 1965), the data for further analysis will be selected and log transformation applied to the indicators that do not meet the assumption in their original form. The indicators which do not meet the assumption, even after transformation, will be eliminated from further analysis. The correlation analysis will provide information about the potential correlation and the intensity of the correlation between Circular Economy competitiveness and innovation indicator, and economic growth. Depending on the results of the correlation analysis, the following regression analysis will be performed to determine the model representing the combined effect of IV on DV. Before model development, a test will be used for the assumptions needed for performing linear regression, including linearity of data, normality of residuals, homoscedasticity, and independence of residuals error terms (Freedman et al., 2003). Only if the assumptions are met the quality of the model can be confirmed. For the analysis, the R software (version 4.2.1) and R Studio (version 2022.02.3) were used.

AND INNOVATION ON EUROPEAN ECONOMIC GROWTH

RESULTS

This section will provide an overview of the collected data and statistical analysis and will be divided into three subsections. The first segment introduces the Shapiro-Wilk test for the evaluation of the normality assumption. It will present the results of the test for the original and transformed values. The second segment will show the correlation results between the IV and DV. The third segment will present the linear regression results and evaluate the quality and fitness of the model.

Normality Assumption Evaluation, Data Selection and Transformation

To determine whether the variables used for the correlation analysis meet the normality assumption, the Shapiro-Wilks test was performed. Based on the Shapiro-Wilk test results presented in Table 2, only one indicator meets the requirement without transformation.

Table 2. Shapiro-Wilk Test Result for Original Variables.

Variable Type of Variable W p-value

VAFC IV .631 9.685e-07

GITG IV .647 1.534e-06

EMP IV .684 4.434e-06

PAT IV .670 2.970e-06

GNIpc DV .957 3.567e-01

Source: Data analysis performed by the author using R

Since it was determined that the GNIpc p-value (.3567) is higher than the significance level of alpha (.05), it can be concluded that it meets the assumption of normality, and it will be used in its original form. The original data for four IVs do not meet the assumption of normality, and thus it will be trans formed using log transformation (MaCurdy & Pencavel, 1986). The new variables which will be used in the analysis are the following:

log.VAFC = log(VAFC)

log.GITG = log(GITG)

log.EMP = log(EMP)

log.PAT = log (EMP – (min (EMP) - 1))

log.GNI = log (GNIpc – (min (GNIpc) - 1))

The transformation of the PAT and GNIpc variables requires the inclusion of the constant to ensure the data adequacy for log transformation.

The Shapiro-Wilk test was applied to the transformed variables to determine whether they meet the assumption of normality in this form. Based on the results of the test, the variables that do not meet the assumption will be eliminated from the model.

POPOVIĆ. A., ĐUKIĆ. I. M., MILIJIĆ. A.

ASSESSMENT OF THE IMPACT OF CIRCULAR ECONOMY COMPETITIVENESS AND INNOVATION ON EUROPEAN ECONOMIC GROWTH

Table 3. Shapiro-Wilk Test Result for Log Transformed Variables. Variable Type of Variable W

p-value log.VAFC IV .960 4.136e-01 log.GITG IV .978 8.321e-01 log.EMP IV .955 3.164e-01 log.PAT IV .878 6.210e-03 log.GNI DV .957 3.506e-01

Source: Data analysis performed by the author using R

Based on the test results provided in Table 3, it can be determined that four out of the five trans formed variables meet the requirements of the test – the p-value is higher than the significance level of alpha (.05). The only value that does not meet the requirement is the log.PAT, thus it can be concluded that the number of patents in climate change mitigation technologies related to wastewater treatment or waste management cannot be used for further analysis.

Correlation Analysis

Spearman correlation analysis was performed between transformed Circular Economy competitiveness and innovation indicators and transformed GNIpc growth rate. The following interpretation will be used - the closer rho is to ±1 stronger the monotonic relationship.

The correlation analysis shows that there is a negative correlation between all IV and DV. The analysis showed that there was a moderate, negative correlation (rho (23) = -0.40, p = .050) between VAFC and GNIpc. Furthermore, there is a weak, negative correlation (rho (23) = -0.26, p = .212) between GITG and GNIpc, and finally there is very weak, negative correlation (rho = -0.09, p = .683) between EMP and GNIpc. The correlation was examined based on the significance level of alpha (.05), and the results are shown in Table 4.

Table 4. Spearman Correlation Results.

IV DV S

Correlation coefficient (rho) p-value log.VAFC log.GNI 3634 - 0.40 .050 log.GITG log.GNI 3273 - 0.26 .212 log.EMP log.GNI 2824 - 0.09 .683

Source: Correlation analysis performed by the author using R * Correlation is effect size, and so the strength of the correlation can be verbally described using the following guide for the absolute value of rho (Cohen et al., 2003) (.00-.19) - "very weak",(.20-.39) - "weak", (.40-.59) - "moderate", (.60-.79) - "strong", (.80-1.0) - "very strong"

Based on the correlation results, the analysis could proceed with the regression analysis and include all three IVs since, although weak, there is a correlation between them and the GNIpc.

OF THE IMPACT OF CIRCULAR ECONOMY COMPETITIVENESS AND INNOVATION ON EUROPEAN ECONOMIC GROWTH

Regression Analysis

Before the regression analysis was performed, the model needed to meet the assumptions of linear relationship, no multicollinearity, independence, homoscedasticity, and multivariate normality (Freedman et al., 2003). Therefore, the data for these assumptions was tested, and the results are shown in Figure 1.

Figure 1. Assumptions for Multiple Linear Regression

Figure 1 provides the necessary information for testing the assumptions that the model needs to meet.

The linear relationship is confirmed through the Linearity graph. It is clear that that the data does not show any visible pattern. Therefore, the linear relationship between the variables can be assumed.

◆ No multicollinearity is confirmed through the Collinearity Graph. It is clear GITG and EMP show low collinearity, while VAFC shows medium collinearity. None of the variables shows high collinearity. Thus, there is no increased uncertainty in the model.

◆ Independence is confirmed through the Durbin-Watson test (Cohen et al., 2014). Residuals appear to be independent and not autocorrelated (p = .562).

Homoscedasticity is confirmed through the Homogeneity of Variance Graph, and residual points are scattered relatively equally along the line. Thus, homoscedasticity can be assumed.

◆

Multivariate normality is confirmed through the Influential Observations Graph and Normality of Residuals. It is clear that there are no influential observations (>|.8|) and that data points follow the projected line, thus confirming that the assumption is met.

Since it can be concluded that the assumptions have been met, following the correlation analysis, the multiple linear regression was calculated to estimate the change in economic growth as a function of the change in Value Added at Factor Cost, Gross Investment in Tangible Goods, and Persons Employed. The results of the Regression Analysis are presented in Table 5.

Table 5. Simple Linear Regression (log.GNI ~ log.VAFC + log.GITG + log.EMP). Variable

Std. Error t-value P (t-test) 0 .0829 .2253 .00297 2.791 .011 log.VAFC - 0.0182 -0.0495 .0056 -3.274 .004 log.GITG .0043 .0117 .0045 0.943 .356 log.EMP 0.0159 .0432 .0050 3.176 .005

Source: Correlation analysis performed by the author using R

The results of the regression indicated that the model explained 31.36% of the variance and that the model was a significant predictor of economic growth, F(3,21) = 4.656, p = .01. While VAFC (B = -0.0182, p<.05) and EMP (B = .0159, P<.05) contributed significantly to the model, GITG did not (B = .0043, p=.356). The final predictive model was: log.GNI = .0829 - (0.0182*log.VAFC) + (.0043*GITG) + (.0043*EMP)

The log-log model after reverse transformation was: GNIpc = .2253 - (0.0495*VAFC) + (.0117*GITG) + (.0432*EMP)

Two out of three analysed variables have a statistically significant impact on economic growth, and it can be interpreted as follows:

◆

Every 1,000 euros increase in VAFC results in a 4.95e-02 decrease in economic growth rate (GNIpc).

◆

Every additional person employed in Circular Economy areas is correlated with a 4.32e-02 increase in economic growth rate (GNIpc).

Even though results indicate a positive impact, EMP did not significantly contribute to the model, and thus the following interpretation can be considered only for the sample presented within this paper.

◆

Every 1,000 euros increase in GITG is correlated with a 1.17e-02 increase in the economic growth rate (GNIpc). However, it is not contributed.

The presented information in this segment provides abundant information for the following discussion of the observed correlation and identified model.

OF THE IMPACT OF CIRCULAR ECONOMY COMPETITIVENESS AND INNOVATION ON EUROPEAN ECONOMIC GROWTH

DISCUSSION

Analysing available data sources and the literature regarding the current state of the Circular Economy, its potential, advantages, limitations, and measurement of its effects and implementation on a national, regional, and global scale (EMF, 2022; Circular Economy, 2022, EC, 2022) it is noticed that even though there are advancements in the evaluation of the effects of a Circular Economy (Smol et al., 2017; Hysa et al., 2020), there is a lack of comprehensive systems and models, which can provide reliable and comprehensive estimates for specific areas of impact.

Through this research, an inquiry was made into the correlation between log-transformed inde pendent variables VAFC, GITG, EMP, and PAT, and the log-transformed dependent variable GNIpc.

The observed correlation coefficients show that there is a statistically significant correlation between competitiveness in a circular economy measured by VAFC, GITG, and EMP, and economic growth measured by GNIpc. The analysis proved that:

◆ There was a moderate, negative correlation between VAFC and GNIpc, which indicates the reverse relationship between Value Added at Factor Cost in Circular Economy and economic growth in Europe.

◆

There is a weak, negative correlation between GITG and GNIpc, which indicates a direct rela tionship between Gross Investments in Tangible Goods related to the Circular Economy and the economic growth in European countries.

◆

There is a very weak, negative correlation between EMP and GNIpc, which indicates the direct, but nearly insignificant, relationship between Employment in the Circular Economy and the economic growth in Europe.

The results of the correlation analysis are consistent with several recent studies (Leider & Rashid, 2016; Busu & Trica, 2019; Karman & Pawlowski, 2021), which developed comprehensive models and frameworks to analyse the economic growth explained by similar variables related to CE for EU member states. Additionally, based on the results of the analysis, it can be concluded that the data support the first hypothesis.

Furthermore, the correlation analysis showed that the observed data regarding innovation in the Circular Economy is not suitable for further analysis and, thus, the effects of innovation on economic growth cannot be evaluated. These results confirm the observations from previously conducted research, which also excluded innovation indicators due to a lack of data (Hysa et al., 2020; Karman & Pawlowski, 2021). Based on these results, it can be concluded that the second hypothesis is not supported.

Finally, a regression analysis was performed to estimate the impact of the transformed independent variables VAFC, GITG, and EMP on the transformed dependent variable GNIpc. The analysis resulted in the regression equation GNIpc = .2253 – (0.0495*VAFC) + (.0117*GITG) + (.0432*EMP), which represents the impact of the Circular Economy competitiveness on the economic growth in European countries. The analysis and constructed model support the third hypothesis. However, the model does not include the innovation segment, thus its predictive capabilities for the whole competitiveness and innovation thematic area are limited. This model, unlike previous research (Leider & Rashid, 2016; Busu & Trica, 2019; Hysa et al., 2020; Karman & Pawlowski, 2021), provides a unique, segmented approach to the evaluation of the competitiveness and innovation in the Circular Economy on economic growth in Europe.

POPOVIĆ. A., ĐUKIĆ. I. M., MILIJIĆ. A.  ASSESSMENT OF THE IMPACT OF CIRCULAR ECONOMY COMPETITIVENESS AND INNOVATION ON EUROPEAN ECONOMIC GROWTH

CONCLUSION

This research aims to prove the existing relationship between competitiveness and innovation in the Circular Economy and economic growth in European countries. For this purpose, the data from the Circular Economy Monitoring Framework provided by the European Commissions (2022) and the data provided by the World Bank (2022) in the Development Indicators segment were utilised. Relying on these macroeconomic variables, a linear regression model was developed to assess the effects that competitiveness and innovations brought about by the Circular Economy have on economic growth measured by Gross National Income per capita annual growth rate.

Available data indicate that European countries widely differ in the quality of the systems and treatment of the competitiveness and innovation directed towards Circular Economy. Based on the original data, it was concluded that, for traditionally competitive and innovative economies, Central and Western European countries are leading in terms of utilisation of these specific segments of the Circular Economy Framework. The correlation analysis and regression model show that increased Values Added at Factor Cost have adverse effects on economic growth, while Gross Investments in Tangible Goods, and Employment in Circular Economy have positive effects on economic growth.

Briefly, it can be concluded that:

◆

Data and scientific framework regarding the implementation and evaluation of the effects of Circular Economy improved daily, but are still lacking.

◆

There is respectively a moderate, weak, and very weak correlation between Value Added at Factor Cost, Gross Investment in Tangible Goods, and Employment in Circular Economy and economic growth measured by Gross National Income per capita annual growth rate.

◆

It is expected that, every 1,000 euros increase in VAFC, GITG and increase in employment by one employee will result in a 4.95e-02 decrease, 1.17e-02 increase, and 4.32e/02 increase in the GNIpc annual growth rate, respectively.

The results of this paper are relevant for academic and business communities, as well as for policy makers. Scientifically, this paper contributes to an attractive and profound research area. The research base so far is primarily focused on the theoretical aspects of the subject, while empirical research is still lacking. This paper aims to narrow the gap between these two aspects of the Circular Economy. Contribution to the business community can be seen through the indication of future development in the European area and the most prolific areas of investment. Thus, business leaders can base their decisions on reliable and scientific data. Finally, perhaps the most significant contribution is to the policymakers. This research is an inquiry into the impact of particular segments of the Circular Economy on economic growth and provides relevant data for directing the development of future policies.

ACKNOWLEDGEMENTS

This research was supported by the Ministry of Education, Science and Technological Development. Contract Number: 451-03-68/2020-14/200371.

AND INNOVATION ON EUROPEAN ECONOMIC GROWTH

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ASSESSMENT OF THE IMPACT OF CIRCULAR ECONOMY COMPETITIVENESS AND INNOVATION ON EUROPEAN ECONOMIC GROWTH

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ASSESSMENT OF THE IMPACT OF CIRCULAR ECONOMY COMPETITIVENESS AND INNOVATION ON EUROPEAN ECONOMIC GROWTH

KORIŠĆEOCENA UTICAJA KONKURENTNOSTI I INOVACIJA U CIRKULARNOJ EKONOMIJI NA PRIVREDNI RAST U EVROPI

Rezime:

Upotreba sirovina u svetu je 70% veća od one koju planeta Zemlja može bezbedno da obnovi. Cirkularna ekonomija predstavlja novi model privrednog razvoja koji se oslanja na „7R“ (redizajniranje, smanjenje, ponovnu upotrebu, popravku, renoviranje, recikliranje i oporavak) kako bi obezbedila operativne i strateške koristi na mikro, mezo i makro nivou. Ovo istraživanje ima za cilj da, kroz procenu uticaja četiri nezavisne varijable iz okvira za praćenje cirkularne ekonomije Evropske Komisije na BND per capita, utvrdi uticaj koji konkurentnost i inovacije u cirku larnoj ekonomiji imaju na privredni rast u evropskim zemljama. U ovom radu analizirana je konkurentnost kroz dodatu vrednost po jediničnoj ceni inputa (VAFC), bruto ulaganje u materijalna dobra (GITG) i broj zaposlenih (EMP) u cirkularnoj ekonomiji, inovacije kroz broj patenata u tehnologijama za ublažavanje klimatskih promena koje se odnose na tretman otpadnih voda ili upravljanje otpadom (PAT), dok je privredni rast procenjen na osnovu godišnje stope rasta BND per capita (GNIpc). Primenjene su metode korelacije i regresije na uzorku od 25 evropskih zemalja koristeći logaritamski prilagođene. Rezultati pokazuju da je korelacija između VAFC i GNIpc umerena i značajna, ali negativna, dok korelacija između GITG i EMP i GNIpc nije statistički značajna.

Ključne reči: Cirkularna ekonomija, Konkurentnost, Privredni razvoj, Održivi razvoj, Evropa.

Klasifikacija JEL: O440, Q01, Q56

OF THE IMPACT OF CIRCULAR ECONOMY COMPETITIVENESS AND INNOVATION ON EUROPEAN ECONOMIC GROWTH

EJAE 2022, 19(2): 15 - 27

ISSN 2406-2588

UDK: 616.98:578.834]:005.334 005.664:336.71(4)"2020/2021" 005.88:005-057.17

DOI: 10.5937/EJAE19-39080

Original paper/Originalni naučni rad

REWARDING TOP MANAGERS IN THE BANKING SECTOR DURING THE COVID - 19 PANDEMIC

Miloš Ilić*, Vinko Lepojević

Faculty of Economics, University of Niš, Niš, Serbia

Abstract:

The paper analyzes the practice of the leading banks in Europe related to the compensation of top managers during the COVID - 19 pandemic and the determination of their relationship with the achieved performance of the banks. The paper aims to examine whether top managers' compensation was related to the bank's performance during the COVID - 19 pandemic as well as give recommendations related to rewarding top managers in crises, based on the good practice of lead ing European banks during the COVID - 19 pandemic. By applying correlation and regression analysis methods, to a sample of leading 50 banks in Europe and 123 top managers, we examined the relationship between the gross profit and compensation of top managers in 2020 and 2021. The results showed that the relationship between bank perfor mance and top managers' compensation (base salary, bonus, and total compensation) was positive even during the COVID - 19 pandemic.

INTRODUCTION

Article info:

Received: Jul 10, 2022

Correction: August 30, 2022

Accepted: September 05, 2022

Keywords: Top management, Basic salary, Bonuses, Total compensation, Bank performance.

The COVID - 19 pandemic has occupied the entire world for the past two years, causing a health and economic crisis (Bapuji et al., 2020). Creating a crisis, reduced the business activities of companies in most sectors and led to a decline in their business performance (McKee & Stuckler, 2020; Bansal, 2020; Ceylan et al., 2020). The pandemic has led to increased business uncertainty and numerous pressures as a result of which crisis management has been introduced in most companies (Bryce et al., 2020; Oehmen et al., 2020; Carnevale & Hatak, 2020).

In response to this crisis, managers have taken a variety of measures depending on the industry and the degree of impact (San et al., 2021; Ardito et al., 2021; Mizrahi et al., 2021). Some things that can be similar to all companies can be collaboration and personnel management, recovery marketing and communication, market segmentation, and the selection and crisis management plan are success factors for recovery (Campiranon & Scott, 2014). Besides this, a lot of companies have implemented remote work in their everyday routine (Van der Kolk & Delfino, 2021).

*E-mail: ilke.ilic@hotmail.com

The scientist also suggests four strategies during the crisis. An exit strategy related to product/market positioning in declining industries, business restructuring, discontinuing business, disinvestment, or portfolio reorganization activities is the first strategy (Wenzel et al., 2020). The strategy of reducing employees, on the other hand, refers to the reduced scope of the company's activities by reducing assets, the number of personnel, product line, costs, and concentrating on basic activities (Schoenberg et al., 2013), as well as a business turnaround as the most frequent strategic response (Miocevic, 2022). The two strategies that remain are the strategy of renewing by innovation, which can be defined as the adaptation of firms to a changing environment and linking this to their ability to use existing competencies and build new capabilities, and the so - called persistence strategy, which aims to "maintaining the business activities of the firm in response to the crisis" (Wenzel et al., 2020). There are some possible strategies, but there is a very big variety of possible actions, which can or cannot be involved in some strategies. On the other side, every crisis can be unique in its way and can reveal some new actions (Bundy et al., 2016; Dobrowolski, 2020).

Crisis management, among other things, meant reducing the number of employees and reducing their salaries. Given the fact that the share of managers' salaries in total salary expenditures in most companies is extremely large, and that on the other hand managers, especially top managers, have the most power and authority, the question arises whether the compensation system of managers has changed in proportion to oscillations in the achieved performance of the company? The examination of the relationship between the compensation package of top managers and the achieved business perfor mance, as well as the analysis of the practice of leading banks in Europe about rewarding top managers during the COVID - 19 pandemic, is precisely the subject of this paper. The aim of the paper is to give recommendations related to the design of a compensation package for top managers in times of crisis.

At the very beginning, the literature on the manager's reward system will be presented, followed by the methodology, then the obtained results and a discussion of the results and recommendations to managers in banks. While concluding considerations are given in the last, final part of the paper.

LITERATURE REVIEW

When we talk about human resources management, it is inevitable to say that the employee reward system is one of the most important systems. The importance of this system stems from the fact that it is a system that can be used to motivate, shape, and correct the behavior of employees following the goals of the company (Dosenovic, 2016). At the same time, it is a very complex system. This system must be designed to reconcile numerous, and often contradictory, demands. Thus, this system is expected to enable a higher degree of motivation for employees and, accordingly, their greater commitment and better results. To this should be added the fact that the reward system is often used as a means of competition in the labor market. However, budgetary constraints appear as a limiting factor in all this because the salaries of employees are, after all, a cost for the company.

The manager's reward system stands out as a special subsystem within the reward system. The creation of a special subsystem for rewarding managers is justified by the fact that managers have a special role and importance in achieving business results. Managers, their assessments, and decisions can have a much greater impact on business results than other employees in the company (Hendriks et al., 2022).

Given that there are three different levels of management in companies (top managers, middle level of management, and operational management), there are also different reward systems for each of these three levels (Loyola & Portilla, 2020). This paper will analyze the system of rewarding top managers.

The compensation package of managers, as with other employees, consists of a basic (guaranteed) salary, incentive / variable part of earnings based on performance, benefits, and equity - based compensation. The manager's compensation package, basically, as with other employees, consists of a basic or guaranteed salary, benefits, an incentive, or a variable part of the salary based on performance and sometimes compensation based on capital. Accordingly, the guaranteed salary represents a fixed monetary reward that the employer pays to the employee for the work performed, and often includes premiums, such as those for night shifts, then differentials, for example, differences in annual leave or differences in shifts and monetary benefits, such as housing allowances and carriage allowances (Kweh, et al, 2022). The basic salary, which is given for the job for which the person is employed to perform, is very often prescribed in its minimum amount by the state, province, or even cities. It is paid on a monthly, semi - monthly, weekly, daily, or even hourly rate, and it is most often determined by a) the performance of the person at work and b) the prevailing level of market wages paid by other employers for that job (Lawrence & Floegel, 2022).

Differentiation of income among employees in the same workplace mainly depends on the achieved results, discretion, or performance. The variable part of the salary is a non - fixed monetary reward that the employer pays to the employee and depends on the achieved results, discretion, or performance. Overtime payment, bonus schemes, or commissions (sales incentives) are just some of the types of variable salaries, and the most common are bonus plans, which have three classic goals (Hendriks et al., 2022):

1. Increase employee performance - the key thing is that an employee will do everything he can to improve his performance if he knows he will get a bonus for it. In this way, workers are encouraged to achieve better results, because they will be paid more (which is defined through the bonus plan).

2. Employee retention - basically, there can be three reasons why bonus plans retain employees, even if that is not their primary goal: 1) employees are less inclined to leave the employer if they are paid better for their work (under other neglected circumstances), 2) a good bonus plan allows good workers to earn more money, which makes it difficult for competitors to make a better offer because top workers are already extremely well paid and 3) in the case of annual bonuses, the probability of employees leaving during the year is reduced, because that way misses out on bonus payments, which gives existing employers more time to better respond to competing offers.

3. Adjusting the price of labor to financial results - the plan is to pay more or to pay a bonus at all when the company is doing well, but not to pay it or reduce it during difficult periods. The operating costs of the company are automatically reduced in bad times, which is the reason for adjusting the bonus plan according to financial indicators and thus updating its increase or decrease.

A wide range of benefits, such as a company car, private health insurance, paid leave, participation in a retirement plan, such as a 401(k) or private pension, and various types of other insurance, such as disability, dental, or life are just some of the supplements and additional compensation for employees employed by employers (Loyola & Portilla, 2020). Many benefits are voluntary by employers to meet the specific needs of a certain population of employees, while on the other hand, some are mandatory following state regulations. Benefit plans are not usually provided in cash but form the basis of an employee salary package along with a basic salary and bonus. Equity - based compensation - action programs or pseudo - actions that an employer uses to secure actual or potential ownership in a company that links employee compensation to the company's long - term success (Boshkoska, 2015).

ILIĆ. M., LEPOJEVIĆ. V.

REWARDING TOP MANAGERS IN THE BANKING SECTOR DURING

The specificity of the compensation package of managers is reflected in the fact that the relationship between the basic salary and salary based on performance (variable part) is different. The organizational unit they manage, i. e. performance at the company level. What many companies offer is the contribution of capital - based compensation to top managers, that is, a significantly larger part of incentive income. Thus, the owners of the company try to motivate the managers to work in their interest and to neutralize the negative effects of the agency problem as much as possible, because in this way the compensation of the manager is tied to the results of the company.

In recent decades, compensations of managers, especially those at the highest level, together with the remuneration of board members have increased significantly (Wang et al., 2021). The gap between the total earnings of top managers and lower - level managers has also increased (Hendriks et al., 2022). What has attracted a greater degree of academic interest, as well as a great deal of public attention, is precisely the topic related to top management compensation due to its specificity. Examining the relationship between a manager's business performance in the US and the manager's salary has been the focus of most papers, but in contrast to the USA, there are much fewer such works in the European context (Carlson & Bussin, 2020). There are papers related to the study of this relationship in the national context of individual European countries, but there are very few papers that cover the whole of Europe or the EU (Hüttenbrink et al., 2014). Therefore, this paper will examine the relationship between the salaries of top managers and bank performance in Europe during the COVID - 19 pandemic. Examining the relationship between top management earnings and firm performance has been the subject of most previous studies (Olaniyi, 2022; Banker et al., 2013). Based on those studies, it was shown that there is a positive correlation between the company's business performance and the total salaries of managers. We assume that the same situation was during the COVID - 19 pandemic. Our first hypothesis is:

H1: The correlation between the total earnings of top managers and the performance of banks in Europe during the COVID - 19 pandemic was positive.

When it comes to the connection between the performance of the company and certain parts of the compensation package of top managers, the results are very different. While most papers have confirmed a positive relationship between base salary and firm performance, research results related to the variable wage - performance relationship are contradictory. Geys, Heggedal, and Sørensen (2017) also observed a positive relationship between variable salaries and company performance, on the other side Worthy (2014) highlighted the positive impact of performance payments and argued that CEO compensation is essential for improving firm performance. They explain that it is not the amount of the variable part of the salary that matters, but how it is determined. They believe that it will not have a positive effect on the company's shareholders if variable compensation is not linked to performance. The relationship between top management bonuses and performance is not statistically significant, but the base salary of top management is therefore significantly positively correlated with performance. This conclusion was reached by the research of Banker, Darrough, Huang, and Plehn-Dujovich (2013).

When discussing the relationship between executive pay and performance during crises, the key thing to do is to separate variable pay for performance and fixed pay, as argued by the authors. A no-bonusperformance relationship has been supported by several other authors in different settings and under different conditions (Basuroy, Gleason & Kannan, 2014). The variable salary of top managers has a negative impact on firm performance as shown by a study conducted by Kweh, Tebourbi, Lo & Huang (2022). We can assume that the relationship between the variable part of earnings and performance was negative since the operations of most banks had negative trends due to the consequences of the COVID - 19 pandemic, which has not bypassed anything, and this is also the case. Our second hypothesis is:

TOP MANAGERS IN THE BANKING SECTOR DURING THE COVID - 19 PANDEMIC

M., LEPOJEVIĆ.

H2: The correlation between the bonuses of top managers and bank performance in Europe was negative during the COVID - 19 pandemic.

METHODOLOGY

Models and variables

Refinitiv workspace data conducted in 2019, 2020, and 2021 are used for the analysis. The sample includes 50 of the largest banks and banking groups in Europe and 136 managers in top - level positions. The list of banks is shown in Table 1.

Table 1. List of banks included in the survey No. Bank

1 BNP Paribas SA (ENXTPA: BNP)

Managers No. Bank Managers

Lemierre, Jean Bonnafe, JeanLaurent Bordenave, Philippe

26 DNB Bank ASA Bech Moen Braathen, Kjerstin Rasmussen Ertizeid, Ottar Fingeschu Rasmus Aaget Grant, Mirella E.

2 HSBC Holdings plc (LSE: HSBA) Quinn, Noel P. Stevenson, Ewen James

3 Crédit Agricole S.A. (ENXTPA: ACA) Lefebvre, Dominique Brassac, Philippe Musca, Xavier

27 Swedbank AB (publ) (OM: SWED A) Henriksson Jens

28 Banco de Sabadell, S.A. (BME: SAB) Oliu Creus, Joser Kigneras David Vegara

4 Barclays PLC (LSE: BARC) Morzaria, Tushar 29 Nykredit A/S Rasusen Michaen Hellemon David Jensen Anders

5 Banco Santander, S.A. (BME: SAN) de Sautuola y O'Shea, Ana Botin-Sanz de Sautuola y O'Shea, Ana Botin-Sanz

6 Société Générale Société anonyme (ENXTPA: GLE)

Bini Smaghi, Lorenzo Oudea, Frederic Aymerich, Philippe Lebot, Diony

30 HSBC Continental Europe,S.A Beunardeau Jean Wild Andrw Davies Christopher

31 Raiffeisen Bank International AG Strobi Johann Lennkh Peter

7 Lloyds Banking Group plc (LSE: LLOY)

Chalmers, William Leon David Calafat, Juan Colombas

8 ING Groep N.V. (ENXTAM: INGA) van Rijswijk, Steven J. A. Phutrakul, Tanate

32 Credit Mutuel Arkea LeMoal Ronan

Bank of Ireland Group plc Mc Donagh Francesa Jane

9 NatWest Group plc (LSE: NWG)

Rose-Slade, Alison Marie Murray, Katie

10 BPCE SA Mignon, Laurent Fabresse, Christine Halberstadt, Catherine Namias, Nicolas

Totalkredit A\S Schmidt Jan Holm Camila

AIB Group plc (ISE: A5G) Hunt S. Colin

11 Credit Suisse AG Gottstein, Thomas P. 36 Caixa Geral de Depositas, S. A Paulo de Jose Jose Antonio Jose Joao

12 Standard Chartered PLC (LSE: STAN)

13 CaixaBank, S.A. (BME: CABK)

14 Banco Bilbao Vizcaya Argentaria, S.A. (BME: BBVA)

15 Coöperatieve Rabobank U.A.

Winters, William Thomas Halford, Andrew Nigel

Gortazar Rotaeche, Gonzalo Maria

Torres Vila, Carlos Genc, Onur

Draijer, Wiebe Brouwers, Bas C. de Groot, Els A. Konst, Kirsten C. M. Leurs, Bart Lichtenberg, Marielle P. J. Marttin, Bernardus Jacobus Sevinga, Ieko Anne Vos, B. Janine

16 Nordea Bank Abp (OM: NDA SE)

17 Danske Bank A/S (CPSE: DANSKE)

Vang-Jensen, Frank Koskinen, Jussi

Egeriis, Carsten Rasch Behring, Berit Irene Vollot, Philippe Soderholm, Glenn Vogelzang, Chris F. H. H.

Virgin Money UK PLC (LSE: VMUK)

Banco Comercial Portugues S.A.

David Joshep

Miguel Maya Dias Miguel de Campos Rui Manuel

Jyske Bank A\S Andres Christian Peter Trier Per Damborg

40 DNB Boligkreditt AS Sagbakkern Per

Converty Building Society Peter Nicholas

42 Bank Polska Kasa Opieki S.A. (WSE: PEO)

Gadomski, Marcin Zmitrowicz, Magdalena

18 ABN AMRO Bank N.V. (ENXTAM: ABN)

Cuppen, Tanja J. A. M. Abrahams, Clif ford James de Kluis, Daphne C. van der Horst, Frans M. R. van Dijkhuizen, Kees C. van Mierlo, Pieter H

43 ING Bank Slaski S.A. (WSE: ING)

Erdman, Joanna Graczyk, Bozena

ILIĆ. M., LEPOJEVIĆ. V.

19 Santander UK Group Holdings plc

Bostock, Nathan Mark Dayal, Madhukar

20 Santander UK plc Bostock, Nathan Mark Dayal, Madhukar Allen, Susan Mary

21 KBC Group NV (ENXTBR: KBC)

Thijs, Johan Popelier, Roger Elie Luts, Erik Marcel Hugo Van Rijsseghem, Christine Hollows, John Arthur Falque, Daniel Scheerlinck, Hendrik

44 mBank S.A. (WSE: MBK) Stypulkowski, Cezary Böger, Andreas Pers, Adam

45 BNP Paribas Bank Polska S.A.

Boulanger, André Furlepa, Przemyslaw Kemblowski, Wojciech

46 SpareBank 1 Sørøst-Norge

Evensen, Marianne Sommerro Hansen, Geir Årstein

22 Svenska Handels banken AB (publ) (OM: SHB A)

Akerstrom, Carina Beckman, Per Moesgaard, Lars Sorensen, Mikael Arkilahti, Nina Tjernsmo, Dag

47 Stafford Railway Building Society Smit, Michael Richard Jones, Steven

23 Skandinaviska Enskilda Banken AB (publ) (OM: SEB A)

Torgeby, Johan 48 The Chorley and District Building Society

24 Nationwide Building Society (LSE: NBS) Garner, Joe D. Rhodes, Chris S.

25 DNB Bank ASA (OB: DNB)

Braathen, Kjerstin Rasmussen Lerner, Ida Loevold, Maria Ervik Grant, Mirella E. Midteide, Thomas Hansen, Hakon Elvekrok Opstad, Morten

Source: Refinitiv workspace

Penlington, Stephen Kos, Angela Roby, Kimberley Emma

49 Newbury Building Society Roland Martin Cardno, Phillippa Bambridge, Lee Frederick

50 Loughborough Building Society

Brebner, Gary Joyce, Caroline

To check the validity of the hypotheses, a correlation analysis was applied. The two models were formed. The first examines the relationship between the business performances of banks and the total compensation of top manager/s. The second examines the relationship between business performances on one side and the fixed and variable part of the compensation package of top managers on the other side. The business performance of banks will be expressed on the bases of Total Revenue - Capital IQ, and Gross Profit - Capital IQ. The average values of the business performances and compensation packages of top managers in banks are given in Table 2.

Table 2. Descriptive statistics

Mean Std. Deviation N

Salary 1045084.79

798394.63

Total compensation 1899577.48

Gross profit* 9837950000

Source: Author’s calculations

Table 2 provides descriptive statistics for the variables used in this study. We note that the oscillations in the salary, bonuses, and total compensation of top managers were very high during the COVID - 19 pandemic. Also, the deviation from the average was great in Gross profit.

The average salary of top managers during the pandemic was 1.045.084, 79 EUR. DNB Bank ASA’s top manager recorded the least salary (42.980 EUR in 2020), while the highest salary had a top manager in Banco Santander, S.A. (BME: SAN) (3.176.000 EUR in both years, during a pandemic).

A correlation analysis was applied to check the relationship between the compensation of top managers and business performance in banks in Europe. The results are shown in Table 3.

Correlation analysis

Salary Bonus

compensation

profit

profit

Correlation is significant at the 0.01 level (2-tailed)

Authors’ calculations

According to Table 3, there was a strong correlation (0,571) between gross profit and total compen sation of top managers in banks during the COVID - 19 pandemic. So, our first hypothesis (H1) that correlation between the total earnings of top managers and the performance of banks in Europe during the COVID - 19 pandemic was positive was confirmed. The correlation between the gross profit of banks and the salary of their top managers was also direct, but weaker compared to the previous correlation.

The weakest correlation was between bonuses of top managers and the gross profit of banks during the pandemic (0,385), but it was also direct and significant at the level of 0.01. We applied regression analysis to check the validity of our second hypothesis. The results are shown in table number 4.

Table 4. Regression analysis

Beta T Sig

Model 1 Dependent Variable: Bonus (Constant) 538883.501

Gross profit 34.752

R .385 3.896

R square .149

Model 2 Dependent Variable: Total compensation (Constant) 843342.328 3.624

Gross profit 107.363 6.843

R .571 R square .326

Source: Authors’ calculations

According to Table 4, the business performance of banks had a direct and significant influence on the compensation of top managers during the pandemic COVID - 19. Model 1 shows that the gross profit of banks had a positive and significant impact on the bonuses of top managers. If Gross profit increases by 1 million EUR, the Bonus grows by close to 35 EUR. The model explained 14.9% of the total variability. Our hypothesis that the correlation between the bonuses of top managers and bank performance in Europe was negative during the COVID - 19 pandemic was wrong.

According to Model 2, the gross profit of banks had a positive and significant impact on the total compensation of top managers. With Gross profit rising by one million EUR, Total compensation rises by 107 EURs. This model explained 32.6% of the total variability of the total compensation.

Discussion and recommendations for managers

The correlation between the overall earnings of top managers and the performance of banks in Europe during the COVID - 19 pandemic was positive. This can be concluded based on the literature review in the field of top managers' compensation and bank performance. Using a sample of 50 banks in Europe and 123 top managers, we conducted research that confirmed these claims. Our results are consistent with most previous research on the relationship between top managers' compensation and firm performance (Olaniyi, 2022; Banker et al., 2013).

However, based on the results of previous research, which are contradictory, and include the relationship between bonuses and company performance, it can be concluded that this relationship was negative during the COVID - 19 pandemic. However, the research we conducted showed that our assumption was wrong. Namely, bonus growth was conditioned by the company's performance even during the pandemic.

LEPOJEVIĆ.

This is in line with the results of research conducted by Basuroy, Gleason & Kannan, 2014, which refers to the relationship between the variable part of top managers' compensation and the firm's performance in periods of a successful business. On the other hand, it is contrary to the research carried out by Kweh, Tebourbi, Lo & Huang (2022) which implies a negative impact of variable salaries of top managers on the performance of firms in crisis.

According to the obtained results, companies can be recommended to pay bonuses to top managers even in periods of crisis, which are directly related to the achieved performance of the company in the previous period, because this can have positive effects on the growth of performance. Frederick Skinner, perhaps the most influential psychologist of the 20th century used the concept of operant conditioning by which he claimed that an organism (animal, human being) shaped its voluntary behavior based on its external consequences from the environment. Also, the concept that bonus plans can improve employee performance was based on his paper.

Most bonus plans are designed following this concept. Unfortunately, the disappointment for many came in the late 1940s due to mounting empirical evidence suggesting that rewards did not work in the diverse environments common to the modern workplace. The disadvantages of a bonus plan often relate to rewarding bad behavior. Managers who can achieve better short - term financial results (and therefore a bonus) and lead to higher profits or who try to innovate and improve their way of working are better, for example, than managers who adhere to the status quo, fire valuable (expensive) employees and participate in immoral business practices. All the above justifies the attitude of poorly formed plans, which can also damage the effects on employees. Despite all the above, employees (and many employers) still believe that the bonus plan is effective and the only possible motivator in the workplace.

CONCLUSION

We investigated the relationship between the compensation of top managers and the firm’s performance. This topic has been widely examined worldwide for decades. However, there is still ambiguity among the different results. Researchers have found negative, positive, and no significant effects over time. Moreover, the importance of this topic has got more relevancy during the COVID - 19 pandemic. For that reason, we analyzed the correlation between the earnings of top managers and the performance of banks in Europe during pandemic COVID - 19. We wanted to answer the following question: ‘To what extent did executive compensation in the leading banks in Europe was influenced by performance of banks during the COVID - 19 pandemic’. To do so, two different hypotheses were formulated. The first hypothesis mentioned that correlation between the gross profit of banks and top managers’ total compensation including, base salary, other benefits, and variable pay was positive; whereas the second hypothesis was that CEO variable pay, in form of bonuses and gross profit was correlated negatively during the COVID - 19 pandemic.

By applying correlation and regression analysis methods to a sample of 50 leading banks in Europe and 123 top managers, we proved that the correlation between the bank's performance and all forms of top manager compensation (base salary, bonuses (variable part, total compensation) was positive even during the pandemic. Given that, it can be concluded that even in periods of crisis, the compensation package of top managers and any form of payment should be linked to the performance achieved by the company.

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EJAE

M., LEPOJEVIĆ. V.

TOP MANAGERS IN THE BANKING SECTOR DURING THE COVID - 19 PANDEMIC

ILIĆ. M., LEPOJEVIĆ. V.

NAGRAĐIVANJE VRHUNSKIH MENADŽERA U BANKARSKOM SEKTORU TOKOM PANDEMIJE COVID-19

Rezime:

U radu se analizira praksa vodećih banaka u Evropi koja se odnosi na naknade top menadžera tokom pandemije COVID-19 i utvrđivanje njihovog odnosa sa ostvarenim učinkom banaka. Rad ima za cilj da ispita da li je naknada za top menadžere bila povezana sa radom banke tokom pandemije COVID-19, kao i da da preporuke u vezi sa nagrađivanjem top menadžera u kriznim situacijama, na osnovu dobre prakse vodećih evropskih banaka tokom pandemije COVID-19. Primenom metoda korelacione i regresione analize, na uzorku od 50 vodećih banaka u Evropi i 123 top menadžera, ispitali smo vezu između bruto dobiti i naknada top menadžera u 2020. i 2021. godini. Rezultati su pokazali da je odnos između performansi banke i naknade top menadžera (osnovna plata, bonus i ukupna naknada) bile pozitivne čak i tokom pandemije COVID-19.

Ključne reči: Top menadžment, Osnovna plata, Bonusi, Ukupna naknada, Učinak banke.

EJAE 2022, 19(2): 28 - 42

ISSN 2406-2588

UDK: 005.53:004.89]:005.96 005.961:005.81

DOI: 10.5937/EJAE19-39535

Original paper/Originalni naučni rad

THE LEVELS OF ARTIFICIAL INTELLIGENCE APPLICATION IN HUMAN RESOURCE SYSTEMS 1

Teodora Ćormarković, Lazar Dražeta*, Angelina Njeguš

Singidunum University, Belgrade, Serbia

Abstract:

As human capital has become a vital asset in contemporary businesses, utilizing human resources exceeds HRM function towards strategic business partnership within organizations. The key enabling factor was global ICT development that changed functional roles and responsibilities within operating business models and introduced machine intelligence that increased organizational capabilities while reducing human involve ment. The paper discusses the current state of AI applications in HRM systems. Emphasis is placed on clarifying technological features and goals, as well as the evolution of existing HRM systems. Furthermore, the paper provides the framework of AI application levels that serve as a foundation for understanding the current operational potential and provides useful evidence for the future development of HRM systems.

INTRODUCTION

Article info:

Received: August 08, 2022

Correction: September 12, 2022

Accepted: September 14, 2022

Keywords: Artificial Intelligence, Machine Learning, Human Resource Management, Information Systems, Levels of AI Applications.

Human capital has become the most critical organizational asset (Đorđević-Boljanović et al., 2019), especially in the era of the gig economy, cognitive computing and the appearance of the fifth industrial revolution (5IR), fueled by the development of blockchain technologies. Furthermore, with the emergence of the COVID-19 virus pandemic, which forcibly led to the change of previous work patterns, workforce demographics, business models and other socioeconomic circumstances, it is clear that human capital has never been more in the focus of contemporary „knowledge economy“.

Large-scale development of artificial intelligence (AI) applications, brought a new dimension to human resource management (HRM), where the traditional approach has gradually been overcome and moved towards an intelligent (cognitive) approach within HRM (Ćormarković & Dražeta, 2022). Existing processes are becoming more agile, and some new ones are also appearing (Edlich et al., 2019). In the near future, administrative, routine and repetitive jobs will be replaced by artificial intelligence applications/robots that are much more precise in performing certain operations (Smith & Anderson, 2014). 1

1 This paper is an extended manuscript of a paper that was awarded at the 9th International Scientific Conference Sinteza 2022 (https://sinteza.singidunum.ac.rs/)

*E-mail: ldrazeta@singidunum.ac.rs

However, analysis of existing research in the field of AI application in HRM showed a slight fear, as well as lack of understanding and clarity to what extent AI can be applied among existing business functions that employees use every day. In contrast, Jatobá et al. (2019) suggested a need for multidis ciplinary working teams of technical engineers and HRM specialists, while Conchúir & Dražeta (2016) showed effective data leveraging process using cloud-based workflows shared between virtual teams due to contemporary technological advances. Hence, this paper attempts to review the existing state of the implemented AI applications and propose a framework for the levels of AI application in HRM systems.

AI: CONCEPT, SUBFIELDS AND TYPES

AI is a field of computing dealing with the development of a machine intelligence that mimic human cognitive functions such as understanding language, learning, reasoning, problem solving, planning, identifying patterns, and all the abilities that a human possesses (Das et al., 2015).

In the past, AI developed through a number of subfields, such as robotics (intelligent control, autonomous exploration), computer vision (object recognition, image understanding), speech processing (speech recognition and production), Natural Language Processing (machine translation), neural networks (brain modelling), evolutionary computation (genetic algorithms, genetic programming), expert systems (decision support systems, teaching systems), planning (scheduling, game playing), machine learning (decision tree learning), etc. Today, we can use the generic term „artificial intelligence system“, because contemporary robots combine all these subfields into one common system.

AI applications are currently used in a number of business domains, depending on the type of application software as well as the type of AI. There are several types of application softwares, namely interactive transaction-based applications, information systems, big data analytics systems (real-time or batch processing), sensor-based data collection systems (IoT applications), intelligent conversational systems (chatbots, personal assistant), embedded control systems, entertainment systems, stand-alone applications, etc. (Sommerville, 2016). In all of them, some sort of AI has been already implemented (e.g. machine learning algorithms, natural language processing).

Accordingly, AI can be also categorized into three distinct types (Wang & Siau, 2019; Stahl, 2021):

◆

Artificial Narrow Intelligence (ANI) or Weak AI. It is a goal-oriented type, designed to perform a singular task in order to solve a specific problem in a certain context. Today, ANI can outper form humans in some tasks, for example in analyzing substantial amounts of data. However, it cannot solve problems beyond the scope of its focus.

◆

Artificial General Intelligence (AGI) or Strong/Deep AI. The advent of deep learning (development of artificial neural network algorithms), which created a machine intelligence capable of performing general human intelligent actions with a full range of human cognitive abilities (e.g., humanoid robot Sophia).

◆

Artificial Superintelligence (ASI) or Machine consciousness. It can exceed general human intel ligence across any task. However, there is a natural fear among the experts worldwide that such a type of superintelligence may represent a threat to humanity (Musikanski et al., 2020).

T., DRAŽETA. L., NJEGUŠ. A.  THE LEVELS OF ARTIFICIAL INTELLIGENCE APPLICATION IN HUMAN RESOURCE SYSTEMS

HUMAN RESOURCES MANAGEMENT SYSTEMS

To grasp the level of AI applications implemented in HRM, at first, HR processes should be clearly established. Some processes are task- or transactional-oriented, but some are analytical, i.e. requires data analysis in order to make proper business decisions. In both cases, AI can be implemented, but in different ways. Hence, the goals and levels of AI implementations within existing HRM systems (i.e. information systems, web applications, big data systems), will be considered separately.

The overall purpose of HRM is to ensure the utilization of organizational human resources by creating, implementing and monitoring policies that govern employee relations within the organization. Hence, the objectives of HRM when developing AI applications can be divided into following four categories (Raymond et al., 2021):

◆

Social goals: measures that correspond to ethical and social needs, including legal issues such as equal opportunities, equal wages, etc.

◆

Organizational goals: actions that ensure business efficiency, including training, equal distribution of jobs, retention of employees, etc.

◆

Functional objectives: guidelines used to maintain the proper functioning of human resources within the organization.

◆ Personal goals: resources used to support each employee's career, including personal development, maintaining employee engagement, etc.

Human Resource Management systems: from traditional to intelligent

Generally, the first type of HRM system that had been widely used within companies was the information system (IS). Database, processes, interfaces, networks, technologies and people who develop and maintain them are the core components that distinguish IS from other applications (Njeguš, 2021). Traditional information systems, that support an organisation’s day-to-day business activities, were usually built on top of a relational database (DB).

This type of HRM system is often a module of larger information systems, called Enterprise Resource Planning (ERP) systems. ERP is a holistic IS that integrates key business processes within the company, such as finance, marketing, human resources, manufacturing, and warehouse management. Some of the leading information systems on the market are SAP ERP, Microsoft Dynamics 365, Oracle ERP, Sage and others (Gartner, 2022).

In contrast, most of the HRM processes are incorporated into the HRM module of ERP systems. For example, SAP HCM (Human Capital Management) covers number of submodules such as Organiza tional management, Personnel management, Time management, Payroll Accounting, Travel management, etc. Today SAP boosts its core processes with AI, especially with machine learning algorithms.

With the development of the analytical type of information systems, called Business Intelligence (BI) systems, the HRM is expanded with human resource analytics (Margherita, 2022; McCartney & Fu, 2021). Human resource analytics systems are built on top of a data warehouse (DW), which is a distinct type of database (Njeguš, 2021). DW are designed to perform multidimensional queries (i.e. OLAP cubes) and analysis of large amounts of historical data (Figure 1).

ĆORMARKOVIĆ. T., DRAŽETA. L., NJEGUŠ. A.  THE LEVELS OF ARTIFICIAL INTELLIGENCE APPLICATION IN HUMAN RESOURCE SYSTEMS

The advent of IoT and Big data devised a new type of application software able to process a lot of data presented in different formats (image, video, voice, text), and in real-time. Namely, data generated today on the Web and IoT devices, require new technologies to process such sizable volumes (e.g. Hadoop ecosystem). Type of application that processes data for HRM, is named HR Big Data systems with a database called a Data lake (Holwerda, 2021). The power of Big Data is used by applying some machine learning algorithms to the data extracted in real-time from various sources and placed on computer clusters to be visually displayed to the end user. Consequently, the whole process of extraction, cleaning and normalization of data, reduction of data dimensionality, and application of machine learning algorithms is known as Data Science. In contrast, HR web and smart applications based on machine learning algorithms have appeared on the market, and usually cover only one specific HRM process (García-Arroyo & Segovia, 2019).

With recent development of blockchain algorithms and newer generations of machine learning algorithms, the so-called deep learning (set of artificial neural networks), in 2021 new type of database known as Data fabric, was created, where all data can be processed, managed, and stored as it moves (i.e. when there is a need). As presented in Figure 1, Data fabric continuously identifies and connects data from disparate applications, therefore connecting multiple locations, types, and data sources (Gupta, 2021).

Figure 1. Comparison of different types of databases for HRM systems (modified from Kyslyi, 2022).

ĆORMARKOVIĆ. T., DRAŽETA. L., NJEGUŠ. A.  THE LEVELS OF ARTIFICIAL INTELLIGENCE APPLICATION IN HUMAN RESOURCE SYSTEMS

LITERATURE REVIEW

Analysis of publications in the field of AI applications in HRM showed two distinct paths of research. One path is dealing with the implementation of machine learning in a specific HRM domain, by showing what algorithms give the best results for a certain HRM process. The other path analyses the level of AI applications in HRM functions within companies, which corresponds to the objective of our paper. Table 1 shows most recent preview of the second path of research.

Table 1. Review of the latest scientific research papers in the field of AI applications in HRM

Authors Title of paper Research description Research results

Cappelli et al. (2018)

Artificial intelligence in HRM: Challenges and a path forward

The gap between the promise and reality of AI in HRM is analysed. Specifically, ML algorithms were taken into the analysis.

Four challenges are identified: the complexity of HR, small data sets, ethical questions associated with fairness and legal constraints and employee reactions to AI management.

Jatobá et al. (2019)

Evolution of Artificial Intelligence Research in Human Resources

Analysis of existing research in the area of ANNs application in HRM topics, for the period 2000-2018.

There are just a few types of research on AI applied to HRM, there is a need for multidiscipli nary teams, i.e. technical engineers and HRM specialists.

Niehueser & Boak (2020)

Introducing Artificial Intelligence into a Human Resources Function

Empirical research on factors affecting the introduction of AI on the talent acquisition function.

Three main factors emerged: increase in efficiency, better performance and quality of the AI applications, and easy to use.

FraiJ & László (2021)

A Literature Review: Artificial Intelligence Impact on the Recruitment Process

Analysis of AI implementation in the HRM recruitment processes.

AI can boost the process of identifying talents, facilitate dealing with a huge number of applicants, eliminate any bias attempts, etc.

Vrontis et al. (2021)

Artificial Intelligence, Robotics, Advanced Technologies and Human Resource Management: a Systematic Review

Understanding the impact of intelligent automation technologies utilization in HRM, both at organizational and employees level.

The impact of these technologies c oncentrates on HRM strategies, namely, job replacement, human-robot/AI collaboration, decision-making and learning opportunities, as well as HRM activities, namely, recruiting, training and job performance.

Garg et al. (2021)

A Review of Machine Learning Applications in Human Resource Management

Identify the degree, scope and purposes of machine learning (ML) adoption in the core functions of HRM.

ML applications are strongest in the areas of recruitment and performance management, while the use of decision trees and text-mining algorithms for classification dominate all functions of HRM.

THE LEVELS OF ARTIFICIAL INTELLIGENCE APPLICATION IN HUMAN RESOURCE SYSTEMS

Authors Title of paper Research description Research results

Jaiswal et al. (2021)

Rebooting Employees: Upskilling for Artificial Intelligence in Multina tional Corporations

Taking into account the dynamic skill, neo-human capital and AI job replace ment theories, based upon interviews of 20 profession als in IT companies.

Research revealed five critical skills for employee upskilling: data analysis skills, digital skills, complex cognitive skills, decision-making skills and continuous learning skills.

Hemalatha et al. (2021)

Impact of Artificial Intelligence on Recruitment and Selection of Information Technology Companies

Analyze the impact that AI is having on recruitment and selection. An online survey of 141 IT employees was conducted.

AI technologies capabilities such as NLP, Machine Vision, Automation, and Augmentation have positive outcomes on time & cost-saving, accuracy, removing bias, reducing workload, increasing efficiency, and candidate experience.

Chowdhury et al. (2022)

Unlocking the Value of Artificial Intelligence in Human Resource Management through AI Capability Framework

A systematic review of the literature in order to provide an objective understanding of the organisational resources required to develop AI capability in HRM.

To benefit from AI adoption, the authors proposed an AI capability framework for the managers to objectively self-assess organi sational readiness and develop strategies to adopt and imple ment AI-enabled practices and processes in HRM. They suggest that organisations need to look beyond technical resources and emphasise on human skills and competencies, leadership, team coordination, organisational culture and innovation mindset, governance strategy, and AIemployee integration strategies.

Bärmann, (2022) Trust in Artificial Intelligence in Human Resources Development

AI processed data in an organizational context leaves employees vulnerable. Besides their dependence on trusting the managers with their competences and intentions, they also depend on AI to produce credible and meaningful data.

Research identifies the critical variables of trust in the rela tionship among an employee, the AI used and the manager. The result is a new integrative model of trust in AI, based upon organizational trust extended by aspects of initial trust and FEAS (fairness, explainability, audit ability, and safety) elements of AI trustworthy. In the future, employees’ perspectives should be more considered.

ĆORMARKOVIĆ. T., DRAŽETA. L., NJEGUŠ. A.  THE LEVELS OF ARTIFICIAL INTELLIGENCE APPLICATION IN HUMAN RESOURCE SYSTEMS

THE LEVELS OF AI APPLICATIONS IN HRM SYSTEMS

In general, the level of modern technology applications in companies primarily depends on the real needs of employees, the issues and challenges they face, the readiness and feasibility of new technologies introduction and the requirements aimed at achieving better performance and competitiveness (Njeguš, 2021). An interesting fact is that professionals often blame IT experts for the rapid development of information technologies, but this responsibility lies upon end-users. The development (IT) team is only dealing with the growing number of end-user requests while trying to find a long-term sustaining solution. However, responsibility for creation of innovative solutions to address end-user problems, is primarily on IT team.

According to the literature reviewed, HRM does not fully use the power of AI, but still relies on already proven information systems within the company. In order to grasp the current state of existing HRM systems, possibilities of technical upgrade, and type of missing AI applications relevant for business, the framework of AI applications levels in HRM systems is proposed (Table 2).

Not every part of HRM process is critical for the business, strategy, and profitability of the company, so the first step is to analyze core HRM processes. For example, balanced scorecard (BSC) can serve as a metric for defining key HRM indicators that support the company’s strategic business goals. According to data on HRM processes, the strategic HRM information system should be acquired. This is quite important since employees are using only 20% of software functionalities, while 50% are hardly ever or never used, and about 30% are used sometimes or rather infrequently (Njeguš, 2021).

The levels of current AI applications in HRM systems are explained in more detail below.

First level: Intelligent Automation

Nowadays, almost every company is using some sort of application software. The core business is usually covered by some ERP business solutions. However, companies also have deployed other types of applications, such as CRM (Customer Relationship Management), web/mobile applications, and others. All these systems should work together in an interoperable way i.e., to exchange and process data in coordinated fashion. The HRM department uses either an HR module within an ERP solution, certain Human Resource Information System (HRIS) or some other HRM applications (Njeguš, 2021). When using these traditional systems, tasks are usually repetitive, tedious, predictable, and labor-intensive.

EJAE

ĆORMARKOVIĆ. T., DRAŽETA. L., NJEGUŠ. A.  THE LEVELS OF ARTIFICIAL INTELLIGENCE APPLICATION IN HUMAN RESOURCE SYSTEMS

Table 2. The framework of AI application levels in HRM systems

AI type

INTELLIGENCE

ARTIFICAL NARROW

Levels of AI Traditional systems Focus on With embedded AI

ARTIFICIAL GENERAL INTELLIGENCE

1. Intelligent automation

System types: ERP HR Module, HR information system (HRIS), HR web applications, HR legacy system or other. Processes

DB type: Relational database

Transactions processed: online

Analytics type: Reports

System types: HR Business Intelligence (BI) system, HR Analytics Information System, HR OLAP System, HR Data Mart or other.

2. Smart Analytics Systems

DB type: Data Warehouse

Transactions processed: batch

Analytics type: OLAP cubes, data mining algorithms, visualization of KPI

System types: Big Data Analytics systems, Big Data Conversational Systems.

Decision making

Implementation of RPA and AI into traditional systems in order to achieve HRM intelligent automation systems.

3. Big Data AI Systems

DB type: Data Lake

Transactions processed: real - time

Analytics type: ML algoriths

System types: Chatbots, Personal Assistant, Robots

Real-time

Implementation of ML algorithms for advanced HR Analytics.

4. Intelligent systems (applications or robots) with human capabilities

DB type: Data Fabric

Transactions processed: streamline

Analytics type: ML with a focus on Deep Learning algorithms

Complete (general) AI system

Implementation of computer vision, NLP, processing and pattern recognition in speech, image, video, text, deep learning algorithms and other AI fields.

Implementation of affective computing and advanced robotics.

RPA (Robotic Process Automation) bots can tackle data entries, generate reports, alert, and do other rule-based tasks (Asatiani et al., 2022). Pure RPA (without AI) is a rule-based, process-driven software application that processes structured data with deterministic outcomes with no elements of intelligence (e.g., automated form filling). Therefore, RPA is not considered a part of AI (Herm et al., 2022). However, RPA bots may combine RPA core functions with AI elements and are primarily designed to emulate human actions and judgment, more quickly and with fewer errors (Mohamed et al., 2022). In general, there are three types of RPA bots: Programmable, Self-learning and Cognitive (intelligent) automation bots (Houy et al., 2019). Intelligent automation is a fusion of different technologies including RPA

ĆORMARKOVIĆ.

T., DRAŽETA. L., NJEGUŠ. A.  THE LEVELS OF ARTIFICIAL INTELLIGENCE APPLICATION IN

RESOURCE

and AI where RPA automate tasks and processes, and intelligent automation creates smarter business processes and workflows, identifies patterns, and learns from previous actions in order to improve processes, provides analytics and decision-making, adapts to their own and self-manages (Figure 2) (Madakam et al., 2022; Chugh et al., 2022).

Some HRM processes, such as recruitment and onboarding, contain numerous repetitive and rulesbased tasks that RPA can assist with. RPA bot can source applicants with more accuracy and no bias, screen CVs and handle much of the paperwork that HRM staff is responsible for. Hence, RPA in HRM function can be applied to CV screening and shortlisting candidates, background verification for new hires, onboarding new hires, employee induction and training, employee data management, payroll processing, expense management, maintaining compliance, employee exit management, performance management, calculation of shift allowance, tracking attendance, etc. (Dilmegani, 2022). Available intelligent automation platforms are IBM Cloud Pak, Automation Anywhere, BluePrism, UiPath, CAI, NexBotix, CGI and other.

Second level: Smart Analytics Systems for Decision Makers

The first level of AI applications supports and improves day-to-day business operations and are used by each employee. The second level of AI applications is intended for decision-makers, regardless of their level of hierarchy in business (i.e., operational, tactical, or strategic). These traditional systems are known by different names, such as Business Intelligence systems, Analytical information systems or just OLAP (On-Line Analytical Processing) systems. They are developed on top of the Data Warehouse, to which either OLAP cubes (multidimensional queries) or data mining models were originally applied. Today these systems are extended with other ML algorithms and have become an integral part of Big Data Analytics systems (e.g. Hadoop ecosystem) (Kakulapati, 2020).

The advantage of these systems is the visualization of Key Performance Indicators (KPIs) that focus on the most important performance measures that quantify objectives and enable the measurement of strategic performance (Huselid, 2018). HRM KPIs are typically stored in the HR Data Mart, which is

Figure 2. Intelligent Automation Components (modified from Reply, 2022)

ĆORMARKOVIĆ. T., DRAŽETA. L., NJEGUŠ. A.  THE LEVELS OF ARTIFICIAL INTELLIGENCE APPLICATION IN HUMAN RESOURCE SYSTEMS

a partitioned segment of an enterprise data warehouse aligned with the HRM department. Therefore, HRM professionals are using HR data mart for querying, reporting, visualizing, as well as running advanced analytical techniques for clustering, classification, segmentation, and prediction to make better decisions (Hamoud et al., 2020).

Some key features of the human resource analytics systems are workforce analytics, employee turnover forecasting, recruitment analytics etc. For example, if the objective is to reduce turnover costs, the key performance measures may include cost-per-hire, turnover rates and costs, time-to-fill, new-hire satisfaction with orientation, supervisor satisfaction with orientation (learning and growth) and others. The aforementioned traditional systems, where data mining algorithms were applied for data analysis, have been recently upgraded with modern ML algorithms that enable more advanced analytics with greater precision in providing proper knowledge to decision makers (Ćormarković & Dražeta, 2022). Therefore, this level of AI applications is mostly based on ML algorithms implementation. Available HR Analytics solutions today are SageHR, IBM Cognos Analytics, BambooHR, IntelliHR, etc.

Third level: Big Data AI Systems

The key characteristics of Big Data Analytics systems, as compared with the traditional structured systems, are that they can process different data formats (image, voice, video, text, etc.), in real-time, while generated at high velocity on different platforms (IoT, Web, browsers, etc.). Traditional technologies are not able to cope with big data, because they are primarily intended for processing structured data. Furthermore, due to the physical limits of data storage, they are unable to process a huge amount of data in real-time. Therefore, newer technologies appeared, such as NoSQL database systems, the Hadoop ecosystem, and others.

Analytical Information Systems or Business Intelligence (BI), have their data extracted, refined (transformed into a consistent, highly structured format), and then loaded into the data warehouse. In contrast Big Data systems, also have their data extracted but immediately loaded into the Data Lake. After that, if necessary, data get transformed while ML algorithms and other relevant AI fields are applied.

Today, big data systems have surpassed traditional systems and companies often acquire them in the form of smaller web applications that manage some of the key HRM processes currently available on the market. More companies are developing these systems from scratch for their specific needs. Today, these systems are upgraded by incorporating missing HRM processes, newer indicators for business monitoring and analysis, and in support they get expanded with other ML algorithms.

Some of the advantages of Big Data systems over the traditional structured systems is that infor mation placed anywhere in any data format is immediately visible to interested parties, analytics are updated in real-time, and decision-makers are warned about opportunities or threats so they can react promptly. For example, the Big Data system can analyze big unstructured data from annual surveys, web profiles, social media chatters, and other data sources on the internet.

An increasing number of evidence shows big data use in HRM processes such as recruiting the best talent, prioritizing recruitment channels, streamlining the hiring process, improving employees’ motivation and engagement, resource utilization and employee retention, enhancing learning and development, detecting employees’ health and injuries, future forecasting for HRM strategy improvement and avoiding subsequent issues in hiring, retention, and performance. Currently available web appli cations that use the power of ML and analysis of big data extracted from various sources (most often from social media) are: Peoplise solution for applicant tracking and assessment; PhenomPeople solution,

ĆORMARKOVIĆ. T., DRAŽETA. L., NJEGUŠ. A.  THE LEVELS OF ARTIFICIAL INTELLIGENCE APPLICATION IN HUMAN RESOURCE SYSTEMS

LinkedIn and Glassdoor for attracting talent; Glint Employee Engagement platform for attrition detection; Workday solutions for individual skills management, personalized training recommendations according to company's needs, market trends, and employee specifics, and performance development.

Fourth Level: Intelligent Systems (applications or robots) with human capabilities

This type of AI system, known as Strong/Deep AI, is still under the development. This system can apply its intelligence in solving complex problems almost as humans do, such as recognizing emotions, beliefs, and mental processes and utterly understand all human aspects, rather than only replicating or simulating the human mind. The first attempt of such intelligent system is the robot, Sophia. However, Sophia's mindset is still in infancy, and far from being AGI type (Lopes & Alexandre, 2018; Acharjee, 2022). When this type of AI system gets developed, robots may appear in the business environment, working side by side with humans (Johnson, 2019). The role of employees may get changed, for example, training machines to perform certain tasks, explaining the outcomes and sustaining the further responsible use of machines (Wilson & Daugherty, 2018).

In addition to robotics, the accelerated development of intelligent applications should not be neglected, namely towards AGI-type AI. Today, these applications are mostly in the form of conver sational AI systems, such as chatbots and personal assistants (Gao et al., 2018). Current examples of these applications are Microsoft Azure Bot Services and Cognitive Services, SAP Conversational AI, IBM Watson, Dialog Flow by Google, Amazon Lex, Rasa, etc.

CONCLUSIONS

The implementation of AI in nowadays HRM systems is more than just an advanced technology employment. The advents of machine intelligence that mimic human cognitive functions and all the abilities that humans possess, necessitate a shift from traditional to intelligent approach in HRM services. It provided numerous advantages for human resource professionals, evolving from ERP systems to Deep Learning that enable greater focus on a number of HRM processes such as employee relations, personal growth, career development, etc., in ever growing business environment.

This paper presents the latest scientific research in the field of AI applications in HRM. The concept, subfields and types of AI were explained in order to clarify critical HRM goals when developing AI applications. The body of presented evidence revealed “state of the art” in the field of AI applications in HRM and the genesis of contemporary HRM information systems worldwide. Consequently, the framework of proposed AI application levels in HRM provides both human resource professionals and IT developers with a foundation for operational utilization of current systems (tailored to business needs and environment) and remarks for further development of intelligent information systems.

T., DRAŽETA. L., NJEGUŠ. A.  THE LEVELS OF ARTIFICIAL INTELLIGENCE APPLICATION IN HUMAN RESOURCE SYSTEMS

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ĆORMARKOVIĆ. T., DRAŽETA. L., NJEGUŠ. A.  THE LEVELS OF ARTIFICIAL INTELLIGENCE APPLICATION IN HUMAN RESOURCE SYSTEMS

NIVOI PRIMENE VEŠTAČKE INTELIGENCIJE U SISTEMIMA LJUDSKIH RESURSA

Rezime:

Kako je ljudski kapital postao dragocena prednost u savremenom poslovanju, korišćenje ljudskih resursa prevazilazi funkciju upravljanja ljudskim resursima u okviru strateškog poslovnog partnerstva unutar organizacija. Ključni faktor koji je to omogućio je globalni razvoj IKT-a koji je promenio funkcionalne uloge i odgovornosti u okviru operativnih poslovnih modela i uveo mašinsku inteligenciju koja je povećala organizacione sposobnosti uz smanjenje ljudskog učešća. U ovom radu se razmatra trenutno stanje aplikacija koje koriste veštačku inteligenciju u sistemima za upravljanje ljudskim resursima. Akcenat je stavljen na objašnjenje tehnoloških karakteristika i ciljeva, kao i na razvoj postojećih sistema upravljanja ljudskim resursima. Štaviše, rad daje okvir različitih nivoa primene veštačke inteligencije koji služi kao osnova za razumevanje trenutnog operativnog potencijala i pruža korisne informacije za budući razvoj sistema upravljanja ljudskim resursima.

Ključne reči: Veštačka inteligencija, Mašinsko učenje, Upravljanje ljudskim resursima, Informacioni sistemi, Nivoi aplikacija koje koriste veštačku inteligenciju.

ĆORMARKOVIĆ. T., DRAŽETA. L., NJEGUŠ. A.  THE LEVELS OF ARTIFICIAL INTELLIGENCE APPLICATION IN HUMAN RESOURCE SYSTEMS

EJAE 2022, 19(2): 43 - 53

ISSN 2406-2588

UDK: 616.98:578.834]:330.526.32 31:330.567.2(680) DOI: 10.5937/EJAE19-39745

Original paper/Originalni naučni rad

THE IMPACT OF COVID-19 ON HOUSEHOLD CONSUMPTION EXPENDITURE IN SOUTH AFRICA: A MACROECONOMIC PERSPECTIVE

Remembrance Hopeful Chimeri*, Isaac Busayo Oluwatayo

Department of Agricultural Economics and Agribusiness, University of Venda, South Africa

Abstract:

The study was motivated by how the Coronavirus (Covid-19), potentially, affected household spending in South Africa. This is because, firstly, final consumption expenditure by households accounts for the largest share of Gross Domestic Product (GDP) in South Africa, and therefore is a significant driver for economic growth. Secondly, expenditure by households is often used as a proxy of ascertaining the standard of living. The analysis drew data from the Household and Income and Expenditure Survey (HEIS), focussing on the period between 2010 and 2020. The results show that the Covid-19 pandemic had a negative impact on disposable income growth and spending of households at a macro-level. Coupled with other triggers, the contraction of the local economy resulted in job losses, with the unemployment level rising above 30% since the third quarter of 2020.

INTRODUCTION

Article info:

Received: August 22, 2022

Correction: September 15, 2022

Accepted: September 26, 2022

Keywords: Consumption expenditure, Covid-19, Economic growth, Households, South Africa.

Households and individuals alike spend on goods and services to fulfil their basic needs (such as food, clothing, energy, communication, shelter) and wants (entertainment for example). The level of household spending and affordability is mainly affected by disposable income, access to credit, interest rates, level of education and household size, and access to unemployment benefits, among other factors (Ganong & Noel, 2019; Aladangady, 2017; Varlamova & Larionova, 2015). Notwithstanding the importance of saving, expenditure by households is one of the indicators used to measure well-being and wealth of households (Aitken, 2020; Nad'a, Jana, & Veronika, 2015; Herciu & Ogrean, 2015). In other words, households with sustainable livelihoods and better income opportunities are more likely to be food secure, have access to clean water and better sanitation, and afford specialised health services (Russell, Lechner, Hanich, Delisle, & Karen, 2018).

*E-mail: rhchimeri@gmail.com

Economic theory suggests complementary and divergent views on how income affects decision making on spending (Juhro & Iyke, 2020; Muellbauer, 2016) . The Absolute income hypothesis (AIH), also known as the Keynesian consumption function, asserts that consumption spending by house holds is determined by current income (Bokana & Kabongo, 2018). This view was later modified by the Permanent income hypothesis (PIH). The PIH stipulates that it is more practical for households to consider future expectations of income and risk when making consumption and saving decisions (Friedman, 1957). Friedman (1957) argued that household income can be split into two components: permanent (past and future income) and transitory, which is unexpected additional income (Jorgensen & Druedahl, 2020; Zheng, Xia, Hui, & Zheng, 2018; Ezeji & Ajudua, 2015). It follows that household spending would also depend on the two income components (Fernandez-Corugedo, 2004), though permanent income is a major determinant to consumptions decisions (Fama, 2021; Friedman, 1957).

The third theory, termed the life-cycle hypothesis (LCH) holds the view that individuals consume a consistent percentage of the present value of their income, influenced by earnings and preferences (Chimeri, 2015). The LCH further asserts that consumption (relative to saving) is comparably higher in households that are dominated by young and elderly persons – due to either borrowing against future income or spending savings accumulated overtime, respectively (Rancan, 2019; Ando & Modigliani, 1963; Modigliani & Ando, 1957).

Apart from being a yardstick of a decent standard living and wealth accumulation, expenditure by households is a component of aggregate demand in economy (Dynana & Sheiner, 2018). According to Keynesian economics, increased aggregate demand is likely to increase output (goods and services and products): converting to more income in the economy (Chimeri & Oluwatayo, 2020). The Keynesian view is more relevant in the South African economy since the local economy has not reached full employment (Chimeri & Oluwatayo, 2020; Mohr & Fourie, 2015).

Growth in income, increased profitability for suppliers of goods and services, and increased consumption consequently enhances the tax base from which the government can collect more revenue (Alvarez-Martinez, et al., 2021). In turn, improved profitability by businesses is likely to create more employment opportunities and therefore somewhat extend the personal income tax base (Rezai, Taylor, & Foley, 2018). The conceptual framework below illustrates how consumption expenditure positively contributes to the growth of the local economy. Again, it should be noted that while acknowledging the positive effect of consumption by households on the economy, saving is still an important practice that should be fostered among South Africans (Stanlib, 2020).

IMPACT OF COVID-19 ON HOUSEHOLD CONSUMPTION EXPENDITURE IN SOUTH AFRICA:

Conceptual

for

MACROECONOMIC

of consumption expenditure to the

for

tability

Source: Own illustration adapted from Chimeri and Oluwatayo (2020)

Table 1 shows the biggest contributors to aggregate demand in the South African economy.

1. Expenditure by households and general government in recent years

Total Gross Domestic Product (GDP)

R million, current prices

Final expenditure by households (R million, current prices

Expenditure by general government (R million, current prices

Own illustration from Quantec EasyData (2021a)

The gross domestic product (GDP) of South Africa was valued at R5.5 trillion in 2020 (at current prices), lower than the GDP in 2019 (valued at R5.6 trillion, in current prices). Final consumption expenditure by households accounted for 64% of the GDP in 2019 and 62% of the GDP in 2020. Expenditure by general government was about 20% of GDP in the last two years, with the residual share of GDP attributable to investment expenditure and net exports. The figure below shows the structure of South African GDP using the expenditure since 1993.

Figure 2. Structure of GDP in South Africa using the expenditure approach.

Composition of GDP in South Africa

R6.000.000

R5.000.000

R4.000.000

R3.000.000

R2.000.000

R1.000.000

R million (current prices) R-

Total GDP/Expenditure Expenditure by households Expenditure by governments

Source: Own illustration from Quantec EasyData (2021a)

Figure 2 shows the values of household expenditure, government expenditure and total GDP at current prices. Final consumption expenditure by households has been the largest contributor to aggregate demand, accounting for more than 60% of the total GDP since the data was recorded and published by Statistics South Africa (Stats SA).

The outbreak of Coronavirus (Covid-19) resulted in the declaration of a national state of disaster by the national government in March 2020, after the first confirmed case was reported on March 5 (IMF, 2021). Despite a number of containment measures introduced with the purpose of slowing down the spread of the virus – encouraging social distancing and school closures etc., the government eventually enacted a nationwide lockdown, effected from midnight March 2020. The lockdown allowed for persons in ‘key’ sectors and industries (such as health workers, transporters, bankers, food and medicine manufacturers, and retailers) to continue operating in a business-as-usual environment (IMF, 2021). Although a phased lifting of the lockdown began in May 2020, to allow some sectors to operate, the government had employed several mechanisms to limit the spread of different and newly discovered Covid-19 variants (IMF, 2021). It is also important to mention that the government implemented a number of fiscal interventions to lessen the burden of the pandemic on citizens:1

Using of the Unemployment Insurance Fund (UIF) to assist distressed employees

Implementing special programmes with the Industrial Development Corporation (IDC) to assist affected workers

Small tax subsidies for workers that earned income below a determined threshold

Higher social grants provided to the most vulnerable families

A new Covid-19 temporary grant, offered to unemployed persons who did not receive UIF benefit

Distributing food parcels

Funding provided to distressed Small, Medium and Micro Enterprises (SMMEs)

Government guaranteed loans provided to eligible businesses to assist with operational expenses

IMF (2021).

Supporting the provision of emergency water supply, sanitation used in public transport, and food and shelter for homeless persons through a special purpose vehicle, known as the solidarity fund, where the private sector and other non-governmental organisations were contributing to

Fast-tracking reimbursements and tax credits, allowing SMEs to defer some tax liabilities

Issuing a list of goods deemed essential, for a full rebate of customs duty and import Value Added Tax (VAT) exemption, and

A four-month skills development levy tax holiday implemented.

According to the IMF (2021), the government, through the Department of Trade, Industry and Corporation (the dtic), also prohibited unfair pricing and limited export control measures of essential goods. In addition, the South African Reserve Bank (SARB) implemented several monetary and macrofinancial measures to stimulate economic activity (IMF, 2021). For instance, progressively reducing the repo rate to ensure there is enough (and not too much) liquidity in the economy. Despite the efforts made by government and other role players, the pandemic hugely affected livelihoods of households and businesses that rely on the openness of the economy, due to the lockdown that limited quantum of economic activity (Ataguba, 2020). The pandemic has also put a strain on the ability of South Africa and other developing countries in attaining their Sustainable Development Goals (SDGs) by 2030 (Dong & Truong, 2022; Erokhin & Gao, 2020; Barber, 2020). According to the 2020 Social Progress Index estimates, it is likely that South Africa will achieve its SDG targets until at least 2092 (Trialogue, 2020). However, the lag can be reduced if there is increased effort in the collective impact, requiring at least double the effort from major key stakeholders (the private sector, civil society, not-for-profit organisations, among others).

DATA

The study used data from the Household Income and Expenditure Survey (HIES), extracted from Quantec EasyData (2021b). The analysis was based on real values in order to make a more meaningful assessment.2 However, the HEIS data from 1993 to 2020 still uses 2010 as the base year.3 The approach involved analysing growth trends in income, spending and saving of households from 2010, until earliest date where such data is available (2020). The start year, 2010, was chosen because it is the earliest year after South Africa (and the rest of the world) had recovered from one of the most severe and well-known recessions, known as the global financial crisis.4

2 It is always advisable to use real (and not nominal) economic values of time series data for better analysis when determining growth trends, since real values are adjusted for inflation.

3 During 2021, Statistics South Africa changed the base year from 2010 to 2015 in measuring national accounts (Stats SA, 2021a).

4 The idea here is to avoid any major structural breaks and give a better reflection of the trends in economic variables under analysis.

CHIMERI. H. R., OLUWATAYO.

CONSUMPTION EXPENDITURE IN SOUTH AFRICA: A MACROECONOMIC PERSPECTIVE

RESULTS AND DISCUSSION

The time period was split into two-time intervals: from 2010 until 2019 (a ten year-period before Covid-19) and from 2019 and 2020 (during Covid-19). In calculating the compounded annual growth rates (CAGRs), the pre-Covid-19 period yields nine intervals, with the latter having one. The following table shows the summary calculations for the CAGRs of the variables of interest.

Table 2. Growth trends in income, consumption and saving by households

Time period Household disposable income Consumption expenditure by households Saving by households

Before Covid-19 (2010 to 2019) 2.14% 2.11% 2.13%

During Covid-19 (2019 to 2020) -3.64% -5.43% 52.24%

Source: Own calculations from Quantec EasyData (2021b)

Table 2 shows that, on average, disposable income of households has grown at a CAGR of about 2%, during the ten-year period before Covid-19. Growth in household spending and savings was similar to the trend of household income growth (2.1%). However, the trend changed between 2019 and 2020. While disposable income contracted by 3.6% at the end of 2020, consumption expenditure also decreased by 5.4%, slightly more than the contraction in disposable income. Interestingly, saving by households grew by more than 50% between 2019 and 2020.

Intuitively, increased saving rates were achievable as a result of either an increase in income (without a proportionate increment in spending), or when a decrease in income is less than the corresponding decrease in spending. As a result, an individual/household will have more money to save. While it is not part of the aims of this paper to investigate the impact on savings by households, it is likely that the commendable growth rate in the savings rate was a result of several factors: such as subsidies and tax reductions and/or holidays, resulting in some individuals/households having more disposable income and possibly channelling part of it into savings.

Further analysis (Table 3) was done to ascertain which types of expenditure groups were most affected during the 2019 to 2020 period. Thus, the table below firstly defines/describes the main expenditure groups in accordance with the Classification of Individual Consumption According to Purpose (COICOP), which is an international system of classifying goods and services based on individual consumption by purpose (Stats SA, 2015).

Table 3. Description of expenditure groups

Expenditure groups

Durable goods

Semi-durable goods

Non-durable goods

Definition Source

“Household items that last for a long time, such as kitchen appliances, computers, radios, televisions, cars and furniture, usually acquired once in several years.”

“Items that last longer than non-durable goods but still need replacing more often than durable goods, for example clothing, shoes and material for clothing.”

“Household items that do not last long, for example food and personal care items. Households usually acquire these items on a daily, weekly or monthly basis.”

Stats SA (2015, p. 66)

Stats SA (2015, p. 67)

Stats SA (2015, p. 67)

H.

While Figure 3 shows the patterns of the main expenditure groups and their respective contribution to final household expenditure, Table 4 shows the individual trends in the expenditure classes.

Figure 3. Trends in final consumption expenditure during the 2010 to 2020 period

R million (2010prices)

R2.500.000

R2.000.000

R1.500.000

R1.000.000

R500.000

Final consumption expenditure by households R-

Source: Own illustration from Quantec EasyData (2021b)

Final_consumption

Durable_goods

Semi-durable_goods

Non-durable_goods Services

As indicated in Figure 3, consumer spending has been on the rise from 2010 until 2019. Between 2010 and 2019, on average, 44% of consumer spending was allocated towards services. Expenditure on non-durable items was the second-largest contributor to consumer spending (37%), while there was a fairly even split between durable (10%) and semi-durable goods (9%). Despite consumption spending declining in 2020, the composition of consumption spending remained unchanged (in 2020).

Table 4 depicts the sparklines that demonstrate trends for the individual expenditure items between 2010 and 2020. This is to show how spending in each expenditure class grew over the years. Although spending on durable goods was more volatile compared to the other categories, consumption spending in all segments reached its highest level in 2019 before dropping in 2020 – similar to the finding shown in Figure 3, at aggregate level.

Table 4. Individual expenditure group trends during the ten-year period

Expenditure group Trend*

Durable_goods

Semi-durable_goods

Non-durable_goods Services

Source: Own illustration from Quantec EasyData (2021b)

*Note: The black marker denotes the highest point (maximum value) in each trend/ sparkline.

According to the conceptual framework, it is possible that suppliers of goods and services at an aggregate (industry) level faced a negative demand shock. Further, it is plausible to suggest that the (negative) demand shock was the major contributor to reduced income growth for businesses and households and consequently a reduction in the tax base. As a result, coupled with other multiplier effects, this led to reduced profitability, salary cuts, and job losses in cases where jobs could not be retained by salary cuts only (Ranchhod & Daniels, 2021). Unemployment, poverty, and inequality are some of the key concerns that the democratic government is striving to address (NPC, 2012). The official unemployment rate has been at least 24% and below 30% since 2010 and at the last quarter of 2019 (Stats SA, 2021b). However, the unemployment rate has consistently stayed above 30% since the third quarter of 2020, reaching 34.4% at the second quarter of 2021 (Stats SA, 2021b) – showing higher levels of unemployment in the history of South Africa.

Apart from the direct negative effects, the recent pandemic has also worsened socio-economic statuses of poor and marginalised people in South Africa. For instance, females employed in informal and labour-intensive sectors are more likely to work fewer hours and are paid less compared to their male counterparts – implying vulnerability and less job security for women (Chitiga, Hensler, Mabungu, & Maisonnnave, 2021; Kikuchi, Kitao, & Mikoshiba, 2021). The welfare and livelihoods of women with no job security were more likely to be harshly impacted due to disruptions in the sectors that employ/ empower them, notwithstanding worsening the gender inequality gap that already existed before the pandemic (Chitiga, Hensler, Mabungu, & Maisonnnave, 2021). Poverty and inequality are expected to increase in female-headed households, at least in the short-term, with the possibly of worsening for households that are not supported by the safety net.

CONCLUSION AND RECOMMENDATIONS

This paper investigates the impact of Covid-19 on household consumption in South Africa, by analysing and comparing consumption patterns of households in two periods: before the emergence of the pandemic (from 2010 to 2019) and in 2020 when South Africa and the rest of the world were exposed to Covid-19. The interest on consumption expenditure is as a result of households’ spending being a major contributor to the GDP of South Africa’s economy, and thus being a key determinant of economic growth of the local economy.

The analysis shows that real disposable income and spending by households declined in 2020, where the decline was more than the average growth in income (and spending) between 2010 and 2019. Despite the government and other key players (such as the SARB) providing safety nets and easing liquidity, respectively, the GDP declined in 2020. The decline in economic activity coupled with other triggers have driven the official unemployment rate above 30% since the third quarter of 2020. Considering the slowdown in economic activity, salary cuts, rising unemployment and contraction of the tax base, challenges of poverty and inequality are likely to worsen, at least in the short-term, making it impractical to achieve some of the SDGs by 2030 – unless efforts are at least doubled to offset to negative outcomes that have been realised.

While the South African government has a budget for the safety net as part of its national priorities, a clear thought process should be followed on how the government can continue to fund its projects without increasing the tax burden on its citizens, as this may further worsen the inequality situation. It is interesting to see how households will adjust spending and saving decisions in the medium to long-term, considering the effect of the pandemic on current income, future expectations and stock of wealth held by households.

OLUWATAYO.

I.

THE IMPACT OF COVID-19 ON HOUSEHOLD CONSUMPTION EXPENDITURE IN SOUTH AFRICA:

MACROECONOMIC PERSPECTIVE

Lastly, the paper recommends at least two areas for further research. Firstly, since the paper was based on highly aggregated data, we suggest a similar study to be undertaken by comparing spending by households according to their living standards – perhaps using the widely used ten Living Standard Measure (LSM) groups, or across different age groups or races. Secondly, it is worthwhile analysing the impact of Covid-19 on household saving, and further explore other aspects such as wealth accumulation.

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CHIMERI. H. R., OLUWATAYO. B. I.

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EJAE

CHIMERI. H.

OLUWATAYO. B. I.

THE IMPACT OF COVID-19 ON HOUSEHOLD CONSUMPTION EXPENDITURE IN SOUTH AFRICA: A MACROECONOMIC PERSPECTIVE

UTICAJ COVID-19 NA POTROŠNJU DOMAĆINSTAVA U JUŽNOJ AFRICI: MAKROEKONOMSKA PERSPEKTIVA

Rezime:

Studija je motivisana time kako je korona virus (Covid-19), potenci jalno, uticao na potrošnju domaćinstava u Južnoj Africi. To je zato što, prvo, izdaci za finalnu potrošnju domaćinstava čine najveći udeo u bruto domaćem proizvodu (BDP) u Južnoj Africi, i stoga su značajan pokretač ekonomskog rasta. Drugo, rashodi domaćinstava se često koriste kao zamena za utvrđivanje životnog standarda. Analiza je iz vedena iz Ankete o domaćinstvima i prihodima i rashodima (HEIS), sa fokusom na period između 2010. i 2020. Rezultati pokazuju da je pandemija Covid-19 imala negativan uticaj na rast raspoloživog prihoda i potrošnju domaćinstava na makro nivo. Zajedno sa drugim okidačima, kontrakcija lokalne ekonomije rezultirala je gubitkom radnih mesta, pri čemu je nivo nezaposlenosti porastao iznad 30% od trećeg kvartala 2020.

Ključne reči: Potrošački izdaci, Covid-19, Ekonomski rast, Domaćinstva, Južna Afrika.

CHIMERI.

OLUWATAYO.

IMPACT OF COVID-19 ON HOUSEHOLD CONSUMPTION EXPENDITURE IN SOUTH AFRICA: A MACROECONOMIC PERSPECTIVE

EJAE 2022, 19(2): 54 - 70

ISSN 2406-2588

UDK: 334.7:005.73 005.32:331.101.32 005.96

DOI: 10.5937/EJAE19-39110

Original paper/Originalni naučni rad

ORGANIZATIONAL CULTURE IN SMES: AN INVESTIGATION OF MANAGERS’ VS EMPLOYEES’ PERCEPTIONS

Ivona Mileva*, Snezhana Hristova

University American College Skopje, Skopje, North Macedonia

Abstract:

Purpose. This paper aims to assess the organizational culture exposed by small and medium-sized companies (SMEs). In other words, we examine the relationship between leadership styles, organizational culture and organizational performance. In order to investigate the role of organizational culture, it is fundamental to analyze the leadership styles in relation to the types of culture, to identify how these are related and well aligned so that they can help the SMEs to be more effective, favoring their innovativeness. Therefore, we like to address the issue of organizational alignment as well, which occurs when employees and leadership are on the same page regarding an organization’s purposes and core values.

Methodology. Based on a sample of 408 Macedonian managers and employees and using the organizational culture assessment instrument VOX, the key findings show that the dominant culture in Macedonian small and medium-sized businesses is Entrepreneurial Democracy and that all employees share similar perceptions about organizational culture.

Contribution/Value. It contributes to the scientific body of knowledge in the context of organizational culture and alignment. The implications of this study will be especially important for the Macedonian SMEs managers and owners in order to gain access to important knowledge of its organizational culture or they need to make improvements to stimulate the innovativeness of their employees to participate in the improvement of company’s performance on the one hand and satisfied employees on the other hand. It also provides the readers with an understanding of how to measure organizational culture and its alignment by introducing up-to-date scientific research in the same field.

Article info:

Received: Jul 12, 2022

Correction: August 08, 2022

Accepted: August 25, 2022

Keywords:

Organizational culture, Leadership, SMEs, Innovativeness.

*E-mail: ivona.mileva@uacs.edu.mk

INTRODUCTION

The most recent business experience appears to show that organizational culture is significant for the exceptional functioning of SMEs. It is so imperative that when not adjusted with organizational structure, business techniques and leader values, it speaks to the company’s most biting adversary on the market. Due to its complexity, the organizational culture is troublesome to be perceived and measured in a genuine environment, which extends the issue of advancement of its impact on the performance and execution of the companies. It is obvious that well-adjusted companies perform more successfully. However, over time, the method of alignment gets to be more complicated due to globalization, different client requests and innovative development.

For this reason, the academic community has begun to explore the concept of organizational culture to help leaders and managers better understand the characteristics of organizations, which in turn can help improve organizational effectiveness and performance.

This study seeks to evaluate organizational culture that Macedonian small and medium-sized businesses have revealed. In order to investigate the function of organizational culture, it is essential to examine the leadership philosophies in relation to the various types of culture. This will help us understand how these are connected and well-aligned, and how they can improve the efficiency and support the innovativeness of SMEs. As a result, the authors talk about organizational alignment, which happens when a company's management and employees are in agreement on its goals and basic principles.

In addition, the paper shed light on organizational culture and leadership in Macedonian SMEs, therefore assisting the practitioners while making improvements to stimulate innovativeness which impacts the company's performance. It also gives its readers a comprehension of how to measure organizational culture and its alignment through the introduction of recent scientific research.

LITERATURE REVIEW

In general, SMEs often struggle in surviving and exceeding the market. Therefore, due to limited data available regarding SME evaluation, the topic has become highly controversial in academia. According to Fourie (2015), the success of SMEs is a result of satisfied customer needs by providing good services and offering good prices. Although it is not clearly defined, it was considered that management success is important for the life of the business. Moving on, many scholars have highlighted the important roles of managers (owners) as well as their impact on a company’s performance. (Beliaeva, Shirokova, Wales, & Gafforova, 2020; Petzold, Barbat, Pons, & Zins, 2019). In the same perspective, there is evidence that SMEs nurture a more organic culture than large organizations. Generally, the owner of the company is the most influential factor over the values and beliefs within the organization. Since a smaller number of people (organizational members of SMEs) are gathered together and cultivate common beliefs and values, it is much easier for them when it comes to changing the organizational culture (Tidor, & Morar 2022).

In the study conducted by Denison and Mishra (1995), based on a sample of 764 SMEs, the CEO perceptions regarding the most important traits of organizational culture and concerning SMEs' effectiveness were examined. The results have shown the support for involvement and adaptability, as indicators of flexibility, openness, and responsiveness, and also were seen as strong predictors of growth.

CULTURE IN SMES: AN INVESTIGATION OF MANAGERS’ VS EMPLOYEES’ PERCEPTIONS

Other traits, consistency and mission, are indicators of integration, direction and vision, and are better predictors of profitability. Each of the four traits was also a significant predictor of other effectiveness criteria such as quality, employee satisfaction and overall performance.

Another significant implication to note is that small and medium-sized companies are particularly vulnerable to economic downturns. Consequently, in times of downturns, not only is it imperative to acknowledge which organizational factors actually stimulate firm performance but it is also urgent to identify the factors that impact these strategic orientations, especially as SMEs struggle to survive. All this turns the focus on the manager, the key player of SMEs. According to the study of Rauch and Frese (2007), it is very important to put the individual back in the entrepreneurial and business research in order to closely examine his/her impact on entrepreneurial success.

Most recently, the activities of SMEs have been ruthlessly disrupted by the COVID-19 pandemic. It calls for expertise, resilience, and perseverance at the managerial level to boost flexibility. Having considered that the Covid-19 pandemic has deeply challenged SMEs to continue to innovate, develop and maintain sustainability, SME managers must focus on the efforts which will be able to support performance and competitiveness. SMEs’ production processes have been also pressurized due to the lack of human resources and the rise in the rate of human cost caused due to the low employee turnout (Bartik, 2020). According to Kottika et al, (2020), in times of any crisis, the organizational culture must be built upon how well the SMEs are going to be agile and resilient to turbulence so that they can carry out risk mapping, take important lessons and build relevant strategies.

In general, there are ‘soft’ and ‘hard’ factors that influence SMEs’ success. Therefore, one can consider customer satisfaction and their acceptance, management capability, entrepreneurial innovativeness, adequate access to financing and information systems, partnerships and governance (Rodrigues, Franco, Silva & Oliveira, 2021). All these characteristics promote a favorable organizational culture.

Concentrating on the empirical evidence of some studies, it is evidenced that the right answer to the survival of the SMEs rests upon: (a) the entrepreneurs' personality traits and skills that affect the market and entrepreneurial orientations of SMEs, (b) the adoption of such orientations that keep impacting the firms' performance, and finally (c) the implementation of strategy relevant to reaching higher quality standards for products and services, combined with tactics relevant to downsizing, marketing actions, extroversion, and financial management. (Kottika et al, 2020 Beliaeva, T., Shirokova, G., Wales, W. et al. 2020 S; Petzold, V. Barbat, F. Pons, M. Zins, 2019).

According to Zutshi et al, 2021, SMEs need to adopt a resilient approach comprising unorthodox thinking and mindful execution. Although this needs to be established first at the individual level, it also needs to be transferred to all departmental levels and the entire organization. In their study, they mention the spectrum of initiatives that might help, such as the SWOT of the owner/manager/decision maker. An objective SWOT process will especially contribute in the long term with enhanced relationships as the decision maker is likely to better understand other employees’ perspectives, making them overall competitive. This process will also assist in the identification of transferable skills, which can be deployed at a time of need. The second focus should be given to the balance in life dimensions. Without good and stable health, one cannot commit to the hard work required for the survival and subsequent success of a business. The authors posit that ‘self-care’ should be the utmost priority for employees and managers need to rethink their roles and responsibilities.

CULTURE IN SMES: AN INVESTIGATION OF MANAGERS’ VS EMPLOYEES’ PERCEPTIONS

Overall, the culture of innovation has a significant influence on the performance of SMEs, which proves that innovation is a trend in absorbing market share, especially in creating superior products, is difficult to emulate and has added value for customers. SME innovation is influenced by leadership and change management within the organization. It fosters a stable culture, spreads trust among the organizational members and encourages innovation and change (Wilderom, Van den Berg & Wiersma, 2012). For that reason, organizational culture is an important element in defining the success or failure of SMEs. In the study done by Arsawan (2020), the results have shown that knowledge-sharing culture significantly influenced innovation culture, business performance and sustainable competitive advantage. The study's findings should further motivate managers and practitioners to emphasize knowledge sharing and innovation culture in the SME sector.

Empirical studies have found different perceptions toward SMEs’ success. Romanian SMEs consider their success to be the result of the degree to which they are friendly to the customers, the degree to which they are known for their honest approach and reputation and offering satisfying customer service. On the other hand, Vietnamese SMEs consider the degree to which they are friendly to their customers and they offer good quality products at a reasonable price, to be the key requirements for their success (Benzing, Chu, & Bove, 2005). In the United States of America, success is based on education and training of entrepreneurs and social competence, which include honesty, and good social skills (Elmuti, Khoury & Omran, 2012). Lately, a large portion of the studies has been focused on managerial skills, entrepreneurial training, personality and psychological aspects of managers and the external environment (Benzing, Chu, & Kara, 2009).

Although organizational culture is more spread in business practice and it is one of the main focuses in the managerial field, there is still a lack of research conducted in the Republic of North Macedonia. One of the few studies dedicated to organizational culture shows evidence that the dominant culture in Macedonian enterprises is the mercenary culture which is characterized by a low score on socializing and a high score on solidarity. They are focused on innovation, prefer to be team-oriented and pay attention to detail, yet do not have a strong impact as national culture has influenced the employees’ behavior (Magdinceva-Sopova, 2012). On the other hand, recent research conducted by Mileva, Bojadjiev, Stefanovska-Petkovska & Tomovska Misoska (2020), suggests that Macedonian SMEs nurture entrepreneurial democracy culture.

Another research shows that SME managers in the country do not possess skills that will result in a detailed understanding of the whole business, and they are focused on building competitive advantage by authorizing employees in the decision-making process. Still, the companies use the outdated way of “doing things” which is not practiced anymore by other companies in today’s business world (Macedonia 2025, 2014). The bottom-up flow of information practice is positively linked to the efficiency and effectiveness of Macedonian SMEs as well as matching the right people with the right position is a practice for differentiating one organization from another (Abduli, 2013).

Speaking of leadership, due to the daily involvement in organizational operations, the behavior of managers/leaders has an impact on organizational members ((Rodrigues, Franco, Silva & Oliveira, 2021). In other words, it is associated with the ability of one or more individuals at the organizational top, which is linked to the owner's historic role within the organization. (Franco & Matos, 2013) suggested that characteristics of the leader, their actions and attitudes are likely to influence the leaders’ work as a component used to encourage management and performance in SMEs.

MILEVA. I., HRISTOVA. S.  ORGANIZATIONAL CULTURE IN SMES: AN INVESTIGATION OF MANAGERS’ VS EMPLOYEES’ PERCEPTIONS

Successful SMEs require good leadership. In other words, the lack of leadership skills in SMEs can lead the company to failure (Breckova & Havlicek, 2013). For this reason, a company should practice the right leadership behavior, linked with organizational performance and success. Moreover, according to Kocherbaeva, Samaibekova & Isabaeva (2019), leadership style is considered to be an important factor in the process of improving and maintaining SME competitiveness. There is a competition for “hunting” talented employees to which both SMEs and large companies are exposed, and their retention depends on the level of quality of the work life. The work autonomy, good corporation and other work conditions cherished by employees are influenced by the leader in the organization (Nanjundeswaraswamy & Swamy, 2015). Due to the small structure of SMEs, leadership styles practiced by the management define their performance. In other words, leadership is a crucial factor in companies’ strategy of maximizing profits and smooth operational flow, although usually, the leaders’ personal goals affect the strategies of the business (Kimberlee, 2019). Moreover, besides the responsibility for financial control and accounting, leaders are in charge of all the relationships with the employees, suppliers and customers and therefore are the key provider of organizational success.

In one of the few studies dedicated to leadership styles in Macedonian companies, Kostovski, Bojadjiev & Budlioska (2015) considered leaders as more autocratically oriented. They explain that the autocratic style is a dominant preferred leadership style despite being unsuitable for new industries and the world today. On the other hand, according to the study of Bojadjiev, Hristova & Mileva (2019), the leaders in Macedonian SMEs prefer a democratic leadership style, which means that they encourage the employees to be involved in the decision-making process and therefore motivate them to accomplish the specific objectives. They explained this change as potential evidence that some changes are happening at the managerial level within the business environment, through which new methods arise in the leadership styles in Macedonian SMEs.

METHODOLOGY

In this study, the VOX Organizationis model was implemented as a principal methodology, a model proposed by Bojadjiev, Tomovska Misoska, Stefanovska & Nikolovska (2011) for measuring organiza tional alignment. The fundamental postulates of this 5-Likert-scale instrument are designed in a way that the dimensions are developed to reflect the broader cultural environments and the specifics of organizations in Macedonia and the rest of South-Eastern European countries. It is focused on meas uring two dimensions and two sub-dimensions of organizational culture: 1) the decision-making and behavior related to the decision-making and behavior policies of the company and 2) innovativeness and risk-taking measuring the tendency toward risk-taking by the company and its employees. The two sub-dimensions are part of the “Democratic VS Autocratic Organization” dimension and those are: 1) People VS Task-orientation which is related to the social care or the human relations within the company and 2) Open VS Closed system which is related to the collaboration of the members of the organization and cooperation between the organization and its environment (Bojadjiev, Tomovska Misoska, Stefanovska & Nikolovska, 2011).

The questionnaire consists of 21 questions and it is distributed to employees and leaders. The ques tionnaire for employees measures organizational culture on “how things are” while the same question naire distributed among leaders answers the question “what the organizational culture should be like”.

CULTURE IN SMES: AN INVESTIGATION OF MANAGERS’ VS EMPLOYEES’ PERCEPTIONS

IN SMES: AN INVESTIGATION OF MANAGERS’

EMPLOYEES’ PERCEPTIONS

The questions from both questionnaires are focused on measuring the two dimensions and two subdimensions:

Questions 1 – 7 are focused on decision-making and behavior. A higher score on this dimension means that an organization supports a Democratic and Participative approach.

Questions 8 – 12 are focused on People versus Task-Oriented. The higher the score the organization gets, the more people-focused they are.

Questions 13 – 15 measure Innovativeness and Risk-taking. A higher score on this dimension shows a higher entrepreneurial spirit.

Questions 16 – 21 – measure Open versus Closed organization. Through these questions, information regarding the type of organization is provided. A higher score on this dimension means that the organization is more open and transparent.

There are four possible outcomes provided from the VOX model, where each of the four cultural types corresponds to the four leadership types.

Managerial Autocracy-company/leader that scores low on both dimensions;

Managerial Democracy-company/leader that scores high on democracy but low on innovativeness and risk-taking;

Entrepreneurial Autocracy-company/leader that scores low on democracy, but high on innova tiveness and risk-taking;

Entrepreneurial Democracy-company/leader that scores high on both dimensions.

Figure 1. Cultural and Leader types regarding dimensions

High High

Entrepreneurial orientation

Entrepreneurial Autocracy Entrepreneurial Democracy Conservative Autocracy Conservative Democracy

“Steve Jobs” like “Jack Welch” like “Army O cer” like “The Banker”

Entrepreneurial orientation Participative management Participative management

HighHigh Low Low Low Low

Source: Bojadjiev (2019)

The research was conducted in 30 small and medium-sized enterprises in the Republic of North Macedonia. The data were collected from 408 respondents among which 378 employees and 30 managers/leaders.

EMPLOYEES’

RESEARCH FINDINGS

In order to examine organizational culture and leadership of the small and medium-sized companies in the Republic of North Macedonia, firstly, we investigate and analyze the companies that took part in the research. For this purpose, the mean and standard deviation was initiated for the two organizational dimensions based on the perception of organizational members or employees on organizational culture and the perception of organizational leader and their style of leading or leadership values.

The mean and the standard deviation for each dimension were calculated and are given in Table 1 and Table 2. The calculation was based on all the 408 respondents’ answers belonging to these 30 companies separately.

According to the findings, all employees in the 30 investigated companies have a tendency to perceive their organizations as more democratically oriented. This means that the employees of each company, separately, see their companies as practicing openness in decision-making, discussions and consultations with employees, free flow of information and shared awareness of proper behavior. However, the employees show a difference in the dimensional score, which means that although all the employees perceive their companies as democratic; some of the employees perceive their organizations as more democratic than other employees in other organizations. The lowest score for “Democratic VS Auto cratic Organization” dimension was evidenced in Company B with a mean of 2.70 (M=2.70), while the highest score was evidenced by Company C with a mean of 4.28 (M=4.28). This can also lead to the idea that employees in Company B (M=2.70) and Company O (M=2.89) are undecided regarding the “Democratic VS Autocratic Organization” dimension since their scores are very close to the cut-off point. For this reason, the results suggest that the employees in these companies are undecided whether the organizational culture allows and encourages them to be part of the decision-making process, or whether the leader and the top management have the last word in making decisions. Moreover, the result can be also prescribed to the lower scores of subdimensions; they equally contribute to “Democratic VS Autocratic Organization” dimension. As a part of the “Democratic vs.Autocratic Organization” dimension, the lower scores in 1) People VS Task-orientation and 2) Open VS Closed system contributes to a lower score in the same dimension (Bojadjiev, Tomovska Misoska, Stefanovska & Nikolovska, 2011). In terms of “People VS Task” sub-dimension, companies in Macedonian the wood furniture industry nurture a more “task-oriented” culture, while companies in the electrical engineering industry nurture culture that is moderate towards high internal and external openness (Mileva, Bojadjiev, StefanovskaPetkovska & Tomovska Misoska, 2020).

Regarding the second organizational dimension, “Innovativeness and Risk-Taking”, which measures the entrepreneurial orientation, all employees from all companies show that they work in companies that are characterized by entrepreneurial orientation, rather than stability focus. This means that the companies which are a part of the research encourage and stimulate the employees to do experimentations, develop new products/services and ideas and take reasonable risks.

However, for this dimension, there is a difference in organizational scores, which makes some of the companies more entrepreneurially oriented and risk-averse than others in the eyes of the company’s employees. The lowest score for “Innovativeness and Risk Taking” dimension was evidenced in Company B with a mean of 2.83 (M=2.83), while the highest score was evidenced by Company E with a mean of 4.00 (M=4.00). This can also lead to the idea that employees in Company B (M=2.83), Company R (M=2.98) and Company Z (2.98) are indecisive regarding the “Innovativeness and Risk Taking” dimension since their scores are very close to the cut-off point.

MANAGERS’

CULTURE IN SMES: AN INVESTIGATION OF MANAGERS’ VS EMPLOYEES’ PERCEPTIONS

The results suggest that the employees in these companies are indecisive about whether the organizational cultures of those companies allow and encourage them to do experimentation, develop new products/services and ideas or whether the companies are more focused on stability.

Table 1. Mean and Standard Deviation for the dimensions of VOX Organizationis

Company Industry

Mean SD D1: Democratic VS Autocratic Organization

D2: Innovative ness and RiskTaking Orientation

D1: Democratic VS Autocratic Organization

D2: Innovative ness and RiskTaking Orientation

Company A Construction Industry 4.12 3.13 0.09 0.31

Company B Construction Industry 2.71 2.83 0.08 0.38

Company C Construction Industry 4,29 3.39 0,11 0.52

Company D IT Industry 3.58 3.20 0.18 0.31

Company E Wine Industry 4,00 4.00 0.25 0.32

Company F PVC Manufacturing Industry 4.00 3.54 0.14 0.10

Company G Food Manufacturing Industry 4.03 3.03 0.06 0.24

Company H Cloth Manufacturing Industry 4.06 3.11 0.35 0.40

Company I Wine Industry 3.49 3.53 0.20 0.22

Company J IT Industry 4.19 3.56 0.52 0.26

Company K IT Industry 3.70 3.26 0.07 0.22

Company L Food Manufacturing 3.83 3.02 0.38 0.27

Company M Construction 4.04 3.74 0.22 0.10

Company N Finance Industry 3.31 3.03 0.14 0.12

Company O IT Industry 2.89 3.43 0.22 0.46

Company P Finance Industry 3.86 3.54 0.29 0.26

Company Q Cloth Manufacturing Industry 3.77 3.31 0.21 0.30

Company R Paper Products Manufacturing Industry 3.53 2.98 0.19 0.17

Company S Wine Industry 3.85 3.78 0.23 0.30

Company T Construction Industry 4.19 3.23 0.09 0.33

Company U Cloth Manufacturing Industry 3.72 3.26 0.21 0.34

Company V Food Manufacturing Industry 3.90 3.54 0.19 0.12

Company W

EMPLOYEES’ PERCEPTIONS

Cloth Manufacturing Industry 3.70 3.27 0.10 0.10

Company X Rubber Manufacturing Industry 4.07 3.42 0.28 0.26

Company Y

Crystal and Glassware Manufacturers and Retail Industry 3.83 3.28 0.30 0.24

Company Z Cloth Manufacturing Industry 3.60 2.98 0.12 0.25

Company AB Food Retailer Industry 3.90 3.46 0.30 0.41

Company AC Food Manufacturing Industry 4.08 3.43 0.43 0.38

Company AD Cloth Manufacturing Industry 3.79 3.28 0.16 0.11

Company AE Finance Industry 3.63 3.30 0.17 0.07

According to the findings in terms of the leadership style practiced by leaders, it could be noticed that all of the organizational leaders believe they nurture participative management or democratic style. This means that the leaders in all investigated organizations believe they encourage employees to be involved in decision-making and they are free to express their ideas and suggestions.

While studying the score on this dimension, one can conclude that all companies scored high (more than 3.50) on the “Democratic vs Autocratic “dimension except for the lowest-scored Company B with a mean of 3.39 (M=3.39).

In terms of “Innovativeness and Risk Taking” dimension, which measures the entrepreneurial orientation of the organization, all leaders from all companies show that they encourage innovativeness and creativity, therefore nurturing entrepreneurial orientation rather than stability focused. This leads to the idea that leaders are also willing to take reasonable risks for organizational success. However, for this dimension, the difference in organizational culture perceived by the leaders’ score is evident; there is a difference in leadership scores for less than half of the companies. The lowest score for “Innovativeness and Risk Taking” dimension was evidenced in Company R with a mean of 2.50 (M=2.50), followed by Company N with a mean of 2.83 (M=2.83), while the highest score was evidenced by Company M with a mean of 4.33 (M=4.33). This can also lead to the idea that leaders in Company R (M=2.50) and Company N (M=2.83) are on the border between being entrepreneurially oriented and stability focused, because of their scores which are very close to the cut-off point.

OF MANAGERS’

IN SMES: AN INVESTIGATION OF MANAGERS’ VS EMPLOYEES’ PERCEPTIONS

Table 2. Mean and Standard Deviation for the dimensions of VOX Organizationis: Leadership Style practiced by the Leaders

Mean SD

Company Industry

D1: Democratic VS Autocratic Organization

D2: Innovative ness and RiskTaking Orientation

D1: Democratic VS Autocratic Organization

D2: Innovative ness and RiskTaking Orientation

Company A Construction Industry 4.14 3.82 1.48 1.60

Company B Construction Industry 3.38 3.19 1.55 1.33

Company C Construction Industry 4.74 3.85 0.71 1.83

Company D IT Industry 4.05 3.83 1.28 1.33

Company E Wine Industry 4.41 4.17 1.09 0.89

Company F PVC Manufacturing Industry 4.20 3.80 0.96 1.17

Company G Food Manufacturing Industry 4.12 3.01 1.24 0.90

Company H Cloth Manufacturing Industry 3.79 3.17 1.50 1.17

Company I Wine Industry 3.68 3.33 1.29 1.03

Company J IT Industry 3.82 3.33 1.19 0.52

Company K IT Industry 3.71 3.50 1.28 0.55

Company L Food Manufacturing 3.51 3.33 0.82 0.91

Company M Construction 4.47 4.33 1.40 1.63

Company N Finance Industry 3.80 2.83 0.94 1.33

Company O IT Industry 3.67 3.83 1.45 0.75 Company P Finance Industry 3.67 3.67 0.62 0.52

Company Q Cloth Manufacturing Industry 3.90 3.50 1.50 1.05

Company R Paper Products Manufacturing Industry 3.73 2.50 0.96 0.55

Company S Wine Industry 4.03 3.83 0.83 0.75

Company T Construction Industry 4.47 3.83 1.41 1.83

Company U Cloth Manufacturing Industry 3.83 3.33 1.11 0.82

Company V Food Manufacturing Industry 3.92 3.67 1.33 0.82

Company W Cloth Manufacturing Industry 3.81 3.33 1.18 0.82

Company X Rubber Manufacturing Industry 4.14 3.83 1.28 0.98

Company Y

VS EMPLOYEES’ PERCEPTIONS

Crystal and Glassware Manufacturers and Retail Industry 3.73 4.00 1.10 0.63

Company Z Cloth Manufacturing Industry 3.73 3.00 0.96 0.63

Company AB Food Retailer Industry 4.07 4.00 1.33 1.26

Company AC Food Manufacturing Industry 4.00 3.50 0.92 0.55

Company AD Cloth Manufacturing Industry 3.93 3.33 1.33 0.52

Company AE Finance Industry 3.93 3.50 1.22 0.84

In order to have a precise and overall picture of the perception of organizational members and leaders as a whole, the results were summarized in general. In this part, the mean, standard deviation and T-tests of the two dimensions as well as the subjective determinants of organizational effectiveness, among the two hierarchical levels (employees and leaders) within the organizations were studied.

The results presented in Table 3 show that there are statistically significant differences, on a level p<0.05, in the opinions about the organizational culture between the two groups. In terms of “Democratic VS Autocratic” dimension, there is no statistically significant difference between the two groups, while there is a statistically significant difference concerning “Innovativeness and Risk Taking” dimension. Employees consider the companies as less entrepreneurially oriented (M=3.33), in comparison with the leaders whose perception regarding innovativeness and risk-taking within the companies is higher (M=3.54).

This means that both leaders and employees think that organizational culture of the companies is entrepreneurially-oriented, although the level of entrepreneurial intention is different and lower in the eyes of the organizational employees. In other words, it can be concluded that both the leaders and the employees place organizational culture on Entrepreneurial Democracy, although there are significant differences in the level of entrepreneurial orientation; organizational members consider the organizations are less entrepreneurially oriented and more risk averse or stability focused.

The case of different perceptions on entrepreneurial orientation between different groups based on position is evidenced in the Macedonian higher education sector where the administrative staff perceives the organizations as more risk-averse in comparison with the faculty staff, and in the food sector where the employees could not confirm the leader’s entrepreneurial perception (Krleska, 2015; Limani, Tomovska-Misoska & Bojadziev, 2015).

CULTURE IN SMES: AN INVESTIGATION OF MANAGERS’

Table 3. General T-test Results for perception on Cultural Dimension of Leaders and Employees

Position Mean SD Sig (2tailed) VOX Cultural Dimensions

D1: Democratic vs. Autocratic Organization

D2: Innovativeness and Risk-Taking Orientation

DISCUSSION AND CONCLUSION

Employee 3.79 0.36 0.07 Leader 3.94 0.30

Employee 3.33 0.26 0.02 Leader 3.54 0.41

The findings suggested that the participants in the survey perceive their company as democratically oriented. In other words, the results indicated that the organizational members feel that companies stimulate openness in decision-making, dialogue and consultations with employees, information free flow and there is a shared awareness of the appropriate behaviors, respect for the employees, work-life balance opportunities, prompt feedback and care for the physical workplace conditions. The organi zational culture was described as open and initiating collaboration within and outside the company, innovation-focused and risk-ready taker. The overall culture was described as Entrepreneurial Democracy.

Several studies have analyzed the culture within SMEs using VOX (Kraleska, 2015; Bojadziev, Tomovska Misoska, Pesev & Stefanovska Petkovska, 2016; Bojadjiev, Kostovski, Handjiski Krliu, & Shindilovski, 2017).According to the proposed methodological and theoretical framework of this instrument, the majority of the studies agreed that organizational culture in SMEs within different industries in the Republic of North Macedonia is described as Entrepreneurial Democracy. According to the literature, smaller businesses are more associated with an autocratic style, rather than a democratic one. This is an unwanted situation because intellectual stimulation is crucial in SMEs, where employees and leaders have close contact, so leaders can effectively encourage employees to think creatively and implement innovative ideas. Moreover, in comparison with large organizations, SMEs are not burdened with strict and formalized structures and procedures. This means that they can focus on not standardized solutions thus offering better modifications to the business environmental changes (Dyczkowska & Dyczkowski,2018). Since SMEs have flexible structures, they may display more entrepreneurial instincts, which provide them more liberty to execute and implement good business practices. When working in small groups, individual members become closer to one another thus they feel committed to performing tasks because their efforts and performance may be noted and cherished more easily. The democratic style is recommended when the organizations are innovative and require collaboration among different units within the organization. For this reason, it should be considered in startups and intensive companies (Mohiuddin, 2017, pp. 26-27). Through the democratic approach, adaptability, innovativeness and knowledge sharing within the company can be increased.

The results from this study are in line with the existing academic literature (Kraleska, 2015; Bojadziev, Tomovska Misoska, Pesev & Stefanovska Petkovska, 2016; Bojadjiev, Kostovski, Handjiski Krliu, & Shindilovski, 2017). However, they are different from the existing literature on organizational culture in Macedonian SMEs, stating that Macedonian companies nurture mercenary culture, meaning that organizational members are not friendly to one another (Magdinceva-Sopova, 2012). Though, the results provide a confirmation that Macedonian companies are focused on innovation, and they

prefer to be team, attention and detail-oriented. This is an important aspect that should be taken into consideration once a practitioners’ community intends to launch a new business; it assists not only in the proper way of structuring the organization but also in the whole way of organizational functioning.

In addition, both employees and leaders describe their companies as focused on participative management and innovation; therefore, both employees and leaders point out the culture as Entrepre neurial Democracy, although the scores from the employees’ perception are considered to be a bit lower than those of the leaders. Though, the analyses of the difference in the perceptions between respondents on leadership positions and those that do not have such positions, suggested that there is a significant small difference in scores in perception regarding innovativeness and risk-taking orientation and there are no statistically significant differences in the opinions about the democratic VS autocratic dimension between the two groups. This means that, although the employees consider working in less innovative focused and risk-taking companies, both the leaders and the employees think that the organizational culture of the companies is Entrepreneurial Democracy.

In link with the academic literature, the same does not contain many studies on the perception of organizational culture and positional differences. A study conducted on a sample of 40.000 nonmanagerial employees, managers and executives in six countries around the globe, that executives within their respective companies had the most favorable appraisal of ethical corporate culture, while the employees’ assessments were less positive, and mid-level managers’ assessments fell in the middle (Ardichvili, Jondle & Kowske, 2012). Besides that, a study dedicated to leaders’ personal values was conducted, confirming the existing link between the leader’s personal and cultural values. This means that organizations need to “fit” between the leader’s characteristics and desired organizational culture.

Last but not the least, the research has some limitations. The possibility of social desirability bias is one of the major restrictions. The degree of honesty should not be taken for granted even though the respondents are anonymous. Uncertainty over the respondents' representation of the industry's overall population is another limitation The respondents' demographic location is the final restriction. Since just the Republic of North Macedonia was studied in this research, subsequent studies should offer a clearer analysis of these characteristics.

RECOMMENDATIONS AND PRACTICAL IMPLICATIONS

The literature review on the organizational culture in the companies from South-East Europe with a focus on the Republic of North Macedonia and the research findings suggest that some of the cultural values from pre-transition have been changed in most of the countries as they face socio-economic instabilities and changes while “going” in the transitional period. The previous system’s remains will no longer function in contemporary management, as the SMEs focus on improvement of their efficiency and effectiveness. The research conducted as a part of this study and the differences in scores of the participants with different organizational positions indicates that different groups experience similar yet different perceptions of organizational culture. Therefore, it is important for organizations to invest in employee well-being through different forms of training and workshops. These forms will raise awareness of what kind of practices should be taken so that both leaders and organizational members feel more comfortable, valuable, and protected in the workplace. These activities should be initiated by the organizational leaders by encouraging active participation in all organizational processes, introducing greater transparency and excluding organizational unfounded opinions and stereotypes concerning employees’ age or gender.

MANAGERS’ VS EMPLOYEES’ PERCEPTIONS

OF MANAGERS’ VS EMPLOYEES’ PERCEPTIONS

Leaders should work on building self-confidence, fostering competition among employees, encouraging relationships with the external world, and sharing expertise and knowledge among the organizational members. In order to listen to “the voice of organization”, leaders should constantly ask employees for feedback on the reflection on the organizational culture, practices and experiences, thus will learn more about the employee’s needs and issues.

Ultimately, organizations should measure their organizational cultures through already established models by recognized authors or adopt internal methods to provide understandable parameters to estimate their organizational culture. A solid organizational culture should be accompanied by a high level of organizational alignment. The process of evaluating the alignment within the organization should not be considered once during the organizational life, but rather should be focused on constant efforts for improvements of the organization’s efficiency and long-term sustainability.

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CULTURE IN SMES: AN INVESTIGATION OF MANAGERS’ VS EMPLOYEES’ PERCEPTIONS

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ORGANIZACIONA KULTURA U MSP: ISTRAŽIVANJE MENADŽERA U ODNOSU NA PERCEPCIJE ZAPOSLENIH

Rezime:

Svrha. Ovaj rad ima za cilj da proceni organizacionu kulturu koju su izložena mala i srednja preduzeća (MSP). Drugim rečima, ispitujemo odnos između stilova rukovođenja, organizacione kulture i organi zacionog učinka. Da bi se istražila uloga organizacione kulture, od suštinske je važnosti da se analiziraju stilovi rukovođenja u odnosu na tipove kulture, da se identifikuje kako su oni povezani i dobro usklađeni kako bi pomogli malim i srednjim preduzećima da budu efikasniji, favorizujući njihovu inovativnost. Zbog toga volimo da se pozabavimo i pitanjem organizacionog usklađivanja, koje se dešava kada su zaposleni i rukovodstvo na istoj strani u vezi sa svrhama organizacije i osnovnim vrednostima.

Metodologija. Na osnovu uzorka od 408 makedonskih menadžera i zaposlenih i korišćenjem instrumenta za procenu organizacione kulture – VOX, rezultati pokazuju da je dominantna kultura u make donskim malim i srednjim preduzećima preduzetnička demokratija i da svi zaposleni dele slične percepcije o organizacionoj kulturi. Doprinos/vrednost. Doprinosi naučnom korpusu znanja u kontekstu organizacione kulture i usklađenosti. Implikacije ove studije će biti posebno važne za makedonske menadžere i vlasnike MSP-a kako bi dobili pristup važnim znanjima o organizacionoj kulturi ili će morati da izvrše poboljšanja kako bi stimulisali inovativnost svojih zaposlenih da učestvuju u poboljšanju performansi kompanije s jedne strane i zadovoljnih zaposlenih s druge strane. Rad takođe omogućava čitaocima da shvate kako da ocene organizacionu kulturu i njenu usklađenost uvođenjem savremenih naučnih istraživanja u istoj oblasti.

Ključne reči: Organizaciona kultura, Liderstvo, MSP, Inovativnost.

CULTURE IN SMES: AN INVESTIGATION OF MANAGERS’ VS EMPLOYEES’ PERCEPTIONS

EJAE 2022, 19(2): 71 - 83

ISSN 2406-2588

UDK: 338.57:549.283]:339.13 616.98:578.834]:339.13

DOI: DOI 10.5937/EJAE19-39258

Original paper/Originalni naučni rad

PREDICTION OF GOLD PRICE MOVEMENT CONSIDERING THE NUMBER OF INFECTED WITH THE COVID 191

Jovana Stokanović Sević*, Ana Jovancai Stakić

Singidunum University, Belgrade, Serbia

Abstract:

This paper aims to test several models and select the best one for predicting the price of gold on the world market for the next day, in five and ten days, taking into account the number of cases and deaths from the Covid-19 virus. These predictions can help decision-makers whether, at what point, and in what amount, it is best to invest in gold and gold-related financial instruments, relative to the projected price of gold from the model. The paper tests models called Decision tree, K-nearest neighbors, Linear regression model, and Support vector machines based on the information on gold prices and the number of cases and deaths from the Covid-19 virus. It will be seen in the paper that even models with only information on the price of gold give quite reliable predictions, but in unstable times like this, models that take into account the instability factor give more accurate predictions. The research aims to determine the optimal amount of information based on which the models will "learn" to give the most accurate possible result. This work’s data processing and models are done in Python.

INTRODUCTION

Article info:

Received: Jul 22, 2022

Correction: September 19, 2022

Accepted: September 23, 2022

Keywords: Gold price, COVID-19, Decision tree, K-nearest neighbors, Linear regression model, Support vector machine..

Throughout the history and development of economic systems, various goods and materials have played the role of money. At the time of barter, goods were exchanged for goods, whereas later it was possible to exchange goods of greater value for more goods of lesser value. Eventually, a system was established where one type of goods became the general equivalent of payment, accepted by all participants. For a large part of history, the function of money was performed by gold. That gold was in the form of coins of precisely determined quality, shape and weight, and in return, it was assigned a value. Naturally, bigger, heavier coins with higher purity had a higher value. Thus, one was able to get larger quantities of goods and services in return.

1 This paper is an extended manuscript of a paper that was awarded at the 9th International Scientific Conference Sinteza 2022 (https://sinteza.singidunum.ac.rs/)

*E-mail: stokanovic.jovana@gmail.com

Gold has always been considered a custodian of value and its basic function is to preserve purchasing power in times of great uncertainty. In the last few years, we have witnessed a period of great uncertainty in the health domain, which further led to uncertainty in the financial, market of goods and services, as well as in all other fields. A new virus called SARS-CoV-2 appeared in 2019 in China as an infectious disease that causes the severe acute respiratory syndrome. The World Health Organization (WHO) declared the Coronavirus outbreak of 2019/20 a pandemic and public health threat of international importance. Evidence of local disease transmission was found in several countries, i.e. in all six WHO regions.

Although the death rate from the virus was quite low at the very beginning, it increased over time, and the number of cases continued to grow. The pandemic was soon declared by WHO, which led to instability in the financial, but also in all other markets. This is best seen through the significant jump in the price of gold. Yousef and Shehadeh (2020) explain this situation quite well. Namely, they prove that there is a correlation between the number of patients and the jump in the value of the price of gold. That is why the research problem in this paper is the prediction of the price of gold in conditions of uncertainty, such as the outbreak of COVID-19.

There are many methods in the literature that make predictions of the price of gold based on historical data. These methods, although effective, lose precision when major market disruptions occur. Therefore, the topic of this paper is to prove that such models have less accuracy than models that include historical data on the cause of market disruptions, which in this case is the COVID-19 pandemic. This paper starts from the assumption that investors need to be able to follow the trend of gold prices, and this paper relatively accurately (over 90% accuracy) follows models that make predictions for tomorrow, the next five or ten days. In this way, investors can determine at what point and how much they can invest and thus get the most value. In addition, this kind of research helps those who operate in shortterm markets, like the Forex market, where things change quickly. Such analyses can help them make the greatest possible profit in the shortest possible period of time. Predictions are of great importance for financial decision-makers. The data contained in the models this paper uses can easily be replaced by data on any other financial instrument in the event of a similar crisis that will almost certainly arise in the future. We believe this to be the greatest contribution of the paper.

BACKGROUND AND LITERATURE REVIEW

Concerning the importance of the gold price in the overall economic environment, predicting the price of gold is very significant. Different studies and models have been used for this purpose. In some eminent research, classical econometric methods were used for this prediction (Shafiee&Topal, 2010; Aye et.al.,2015). Different techniques for the gold price prediction, were used and although various models give very good results, the ARIMA (autoregressive integrated moving average) model is the most precise of all traditional statistical models (Yang 2019; Makala & Li, 2021). In addition, it is good to use a sliding dataset for the prediction (Brownlee, 2020). By comparing the models on the same data set for profit prediction it can be concluded that the choice of the dataset is very important and that parameters unrelated to gold can help make a better prediction (Riazuddin, 2020).

In some prominent research, the artificial neural network model was used for modeling the gold price and compared with the traditional statistical model of ARIMA. The three performance measures, the coefficient of determination (R2), root mean squared error (RMSE), and mean absolute error (MAE), are utilized to evaluate the performances of different models developed. The results show that the ANN

model outperforms the ARIMA model, in terms of different performance criteria during the training and validation phases (Mombeini & Chamzini, 2015; Hong&Majid, 2021).

Machine learning has often been applied to the prediction of financial variables, but usually with a focus on stock prediction rather than commodities (Megan, 2022; Chen et al. 2021). It has also been used for COVID 19 cases (Zivkovic et al. 2021) The application of machine learning in trading with financial instruments has shown very good results (Test&Broker, 2020; Sami&Junejo, 2017), including predictions of gold price direction (Perry, 2021; Aruna et al. 2021) especially by using a decision tree algorithm and support vector (Navin, 2015).

Covid-19 has damaged the global economy, as the series of lockdowns had negative impacts on the global economy (Altig et al. 2020; Borio 2020). Therefore, several studies intended to determine the relationship between COVID-19 infection rates and the price of gold. For this correlation different statistical analyses have been used such as the Vector Error Correction Model (Gautam et al, 2022) and GARCH model (Syahri & Robiyanto, 2020; Bentes et al. 2022; Abounoori & Zabol, 2020)

DATA

The time frame of the data set is dictated by the Covid-19 data set frame. Virus data and gold data are merged into one data set. For the models to be able to predict such a union of data, all N / A values have been dropped, and data regarding the value of gold start with the beginning of 2020, i.e. with the 1st of January. Also, the stock exchanges are closed from Friday from 4 pm to Monday at 8 am, and there is no weekend information.

A set of data containing information about gold was used from the Python library Yahoo! Finance. The following values were taken directly for prediction:

CLOSE - THE VALUE INDICATES THE FINAL PRICE OF GOLD ON THE STOCK EXCHANGE FOR THE GIVEN DAY.

HIGH - THE HIGHEST DAILY PRICE OF GOLD.

LOW - THE LOWEST DAILY PRICE OF GOLD.

VOLUME - DAILY TURNOVER, NUMBER OF TRANSACTIONS FOR THE GIVEN DAY.

Based on the close value, two columns were added, which represent the average price of gold in the previous three and nine days. The model is created based on the idea of Shah and Pachanekar (2020). This way of processing data is called moving average. It is good for making predictions for any given period and is also easily presented in a graph. When we take into account 3 days, this method is called simple moving average and is used as a significant indicator among brokers because it gives equal importance to all three prices and thus shows the price trend.

Data on the virus were taken from the website of the European Center for Disease Prevention and Control (opendata.ecdc.europa.eu, 2020). Since the data contains values for each country individually, they are grouped by date and aggregated into two categories, the number of cases per day and the number of deaths per day.

Figure 1. Gold price from the beginning of 2020

Gold Slose Price

2018-12-31 2019-05-24 2019-10-16 2020-03-11 2020-08-03 Date

Figure 2. The number of people infected with the Covid-19 virus in 2020 Covid-19

Death cases

Cases 2019-12-31 2020-02-19 2020-04-09 2020-05-29 2020-07-18 2020-09-06 2020-10-26

Date

Figure 3. Number of deaths from Covid-19 in 2020 Covid-19 Cases Date 2019-12-31 2020-02-19 2020-04-09 2020-05-29 2020-07-18 2020-09-06 2020-10-26

cases

MODELS USED FOR THE RESEARCH

The paper uses four popular models of machine learning that apply the following algorithms: linear regression, the decision tree, K-nearest neighbour, A support vector machine.

Linear regression tries to show the values of the dependent variable in the most accurate way possible about the independent variable with a linear function. This is a common way of predicting the value of financial instruments, especially if the values are inert. It is a process of finding a line between data points we already have, and we are using that line as an assumption that future data points will fall on it.

Figure 4. An example of linear regression (Thiebaut, 2019)

The decision tree is one of the best and most commonly used classification algorithms because, in addition to offering high prediction accuracy and clarity, it also easily maps nonlinear relationships. This algorithm easily solves regression and classification problems.

Figure 5. An example of the algorithm The decision tree (Jacobi, 2017)

K-nearest neighbour (kNN) can be used for classification and regression problems. It is a model that classifies data points based on the points that are most similar to it. It uses test data to "learn how to guess" what to classify in an unclassified point. More specifically, one might wish to weigh the evidence of a neighbour close to an unclassified observation more heavily than the evidence of another neighbour that is at a greater distance from the unclassified observation (Dudani,1976).

Figure 6. An example of the kNN model (Schott, 2019)

A support vector machine (SVM) is a model reminiscent of a more advanced version of linear regression. This model presents data as points in space that it classifies into two categories between which there is a gap. The SVM efficiently constructs linear or nonlinear classification boundaries and is able to yield a sparse solution through the so-called support vectors, that is, through those obser vations that are either not perfectly classified or are on the classification boundary (Van Der Burg & Groenen, 2016). For the model not to be a linear regression model, the so-called kernel trick is used, which implies observing individual zones, and not the whole set.

Figure 7. An example of SVM model (Alisneaky, 2011)

RESULTS

This research intends to predict the price of gold for one, five, and ten days in advance by using the models of linear regression, decision tree, K-nearest neighbour, and support vector machine. We attempted to see whether one model gives relatively accurate predictions of these prices and which ones. The algorithms did not change in the testing itself, but the intention is to get the best result through changes in the variables. Unlike other papers and research, we were adjusting the amounts of data we will push into the model. This allowed us the workaround on models becoming inert and it helped with weekend stock market missing data and removed N/A values. In other words, it was important to find the model that makes the most accurate prediction for the next day, and later on to predict the gold price five and ten days in advance.

Due to the specific nature of machine learning models, testing and result representation are adequately adjusted, with multiple repeating independent runs taking place during testing, and results showing statistical results of multiple iterations. Additionally, various parameter settings were tested in search of optimal performance.

The first iteration we tested and took as a basis is the prediction of the gold price considering only the historical price of gold as one example, and the second one considering the historical price of gold together with the variables of the Covid-19 virus. The train set for the first example is thirty days, and each day contains information on the high, low and close price of gold, the volume of trade, the average price of gold for the previous three and nine days, and information on the number of patients and deaths from the Covid-19 virus for the previous ten days.

Table 1. Results of baseline gold price prediction models

Linear regression Decision tree K-nearest neighbour Supp. Vector machine Gold Gold and Covid-19 Gold Gold and Covid-19 Gold Gold and Covid-19 Gold Gold and Covid-19

Explained_ variance_score -35.4651 -1.8951 0.9389 0.8926 0.8614 0.8707 0.8472 0.8468

Max_error 895.4937 202.7006 19.5200 22.8000 16.8292 16.7699 14.5399 14.5689

Mean_absolute_ error 16.1152 8.4048 1.9061 2.4486 3.5294 3.4420 4.0318 4.0369

Mean_squared_ error 5268.3565 415.8096 8.8095 15.8995 23.3938 21.9165 27.2889 27.3527

Mean_squared_ log_error 0.06014 0.0102 0.0003 0.0005 0.0007 0.0007 0.0009 0.0009

Median_ absolute_error 3.6564 3.5801 1.2399 1.3899 2.4911 2.5083 3.2707 3.2654

r2_score -35.6856 -1.8954 0.9386 0.8892 0.8370 0.8473 0.8099 0.8095

From the results of the first iteration, it was noticed that the most accurate prediction is given by the decision tree model, but completely contrary to our expectation, a more accurate solution is given by a model that takes into account only the historical price of gold.

Figure 8. Extreme values of decision tree model

Gold ETF Price

predicted_price actual_price

Also, it was noticed that the models have extreme values that do not appear in reality, and were probably caused by "trend velocity" that did not happen. Also, a large number of extreme values from models that include information about Covid are caused by weekend breaks in information. Based on that, it was decided to take the average of the number of patients and the number of deaths in the previous seven days instead of the ten-day data. This iteration in all models shows a more accurate prediction, and three of the four models show a more accurate prediction with information about the Covid-19 virus. Also, this gave us more accurate results, but not good enough.

Observing the results of the previous iteration, we concluded that the train set is potentially too large. It is based on the whole month-worth of information and potentially becomes inert, i.e. "overlearned". Therefore, for the next iteration, we left the data as it is, except that we set the train set to fifteen days.

From the results we noticed that all models give more accurate results. However, the best model turned out to be the decision tree model. It gives the best results both by looking only at the historical price of gold, but also the price of gold taking into account Covid-19 factors. Price prediction with Covid information is still more accurate in all models, only the support vector machine model gives a slightly less accurate result.

Figure 9. Model with Covid data without extreme values

Gold ETF Price

predicted_price actual_price

Also, here we saw that with this way of looking at the data we managed to cancel almost all extreme deviations of the decision tree model. It is seen that the linear regression model gives the worst predictions and has the highest extreme values. The other two models do not have perfect prediction accuracy, but they follow the gold price trend very well, so their value is also reflected in that.

Believing that the problem with the previous iterations was a train set, we tried a seven-day train set, believing that this would avoid the problem related to the stock market operation and the problem related to the weekend data missing.

The presentation of the results tells us that the best model for predicting the price of gold for tomorrow is the decision tree model, which, in addition to the historical price of gold, also contains data on the number of patients and the number of deaths from the Covid-19 virus with a prediction accuracy of 96.25%. The second-best model is still the decision tree, which only contains information about historical gold prices.

Table 2. Results of gold price prediction models with the model with the greatest accuracy

Linear regression Decision tree K-nearest neighbour Supp. Vector machine Gold Gold and Covid-19 Gold Gold and Covid-19 Gold Gold and Covid-19 Gold Gold and Covid-19

Explained_ variance_score -0.6391 -0.6295 0.9616 0.9627 . 0.9386 0.9387 0.9307 0.9306 Max_error 143.1799 143.1799 10.7200 10.7200 13.4921 13.4722 11.3136 11.3128

Mean_absolute_error 6.6431 6.5635 1.8054 1.8054 2.4035 2.4021 2.5986 2.5994

Mean_squared_ error 274.9183 273.2479 6.4203 6.2792 10.7402. 10.7300 12.1284 12.1423

Mean_squared_log_ error 0.1156 0.1155 0.0002 0.0002 0.0003 0.0003 0.0004 0.0004

Median_ absolute_error 2.8622 2.8233 1.3300 1.2699 1.8060 1.8060 2.0386 2.0307 r2_score 0.6412 -0.6313 0.9616 0.9625 0.9358 0.9359 0.9275 0.9275

10. A graphic view of the most accurate model, decision tree with gold and Covid data

ETF Price

Additionally, we performed more iterations to see the prediction results for the prices five, that is, ten days in advance and the same model gives us the most accurate results with an accuracy of more than 95%. For the prediction of results made five days in advance for the first time, a model other than a decision tree gives more accurate results, in the case of prediction based on the historical price of gold. That model is the K-nearest neighbour with the accuracy of 93%. Surely, still the most accurate model is decision tree model with Covid-19 data, but KNN was a surprise.

Lastly, the price prediction for ten days in advance gave us unsurprising results. In this case these decision tree models give the most accurate results. It is interesting that the maximum error is the smallest in the support vector machine model, but all other parameters are the most favourable in the case of the decision tree model. This model predicts the price of gold in ten days with an accuracy of 95.40%.

CONCLUSION

Linear regression tries to show the values of the dependent variable as accurately as possible in relation to the independent variable with a linear function. Many research papers deal with the prediction of the price of gold with the help of linear regression, which can be explained by the relatively stable price of gold in the past, but due to the instability caused by the Covid 19 virus, this model does not give accurate predictions. In fact, of all the four models tested, this model can be called the least applicable for this type of prediction. We attribute this to the fact that the data do not follow any linear trend and are too "scattered" for this type of prediction to give meaningful results.

The k-nearest neighbour model shows the highest accuracy of the prediction in the case of predictions made five days in advance, and only on the basis of historical data on the price of gold. The maximum error of the model is always quite similar for both the model with historical gold prices and the model with the Covid virus.

The support vector machine model in almost every iteration shows more precise results when the prediction is made only on the basis of the historical price of gold. Similar to the k-nearest neighbour model, the accuracy of this model is almost always over 80%. The maximum error of this model is almost the same regardless of what data we take into account, and very often it is smaller than the model that has higher levels of accuracy.

In each iteration and in almost every case, except one, the accuracy of the decision tree model is the highest compared to other tested models. The highest accuracy, of 96.25%, is given in the model trained on a seven-day data set, with information on the seven-day average number of patients and deaths from the Covid-19 virus where the prediction was made for the next day. It is believed that this level of precision is very successful in conditions of great imbalance.

Based on all the above, it is believed that the hypothesis that information on the number of infected and infected with the Covid-19 virus helps to create models with greater accuracy in determining the price of gold than those with only historical values of gold prices has been proven.

Future research could focus on adjusting the parameters of algorithms for creating models and testing other models. It is also believed that such models can be applied not only to the situation with gold and the Covid-19 virus but also to determine the price of any financial instrument at any time in a crisis if appropriate quantifiers of the crisis situation are inserted. Given that health crises have become more frequent in the last few decades, it is believed that this work will have wide applications in the future.

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PREDVIĐANJE KRETANJA CIJENE ZLATA S OBZIROM NA BROJ ZARAŽENIH KOVIDOM 19

Rezime:

Ovaj rad ima za cilj da testira nekoliko modela i odabere najbolji za predviđanje cene zlata na svetskom tržištu za naredni dan, odnosno pet ili deset dana unapred, uzimajući u obzir broj obolelih i umrlih od virusa Covid-19. Ova predviđanja mogu da pomognu donosiocima odluka da li je, kada i u kom iznosu, najbolje investirati u zlato i finansijske instrumente vezane za zlato, u odnosu na projektovanu cenu zlata iz datog modela. U radu se testiraju sledeći modeli: Stablo odlućivanja, K-najbliži sused, model linearne regresije i mašine za vektore podrške na osnovu informacija o cenama zlata i broju obolelih odnosno umrlih od virusa Covid-19. Rad će pokazati da čak i modeli koji sadrže samo podatke o ceni zlata daju prilično pouzdana predviđanja, ali da u ovakvim nestabilnim vremenima modeli koji uzimaju u obzir faktor nestabilnosti daju tačnija predviđanja. Istraživanje ima za cilj da odredi optimalnu količinu informacija na osnovu kojih će modeli „naučiti“ da daju što tačniji mogući rezultat. U ovom radu, za obradu podataka i modele korišćen je Pajton.

Ključne reči: Cena zlata, COVID-19, Drvo odlučivanja, K-najbliži susedi, Model linearne regresije, Mašina vektora podrške.

EJAE 2022, 19(2): 84 - 96

ISSN 2406-2588

UDK: 378.147.091.32:004.738.5 159.953:316.644-057.875 DOI: 10.5937/EJAE19-39714

Original paper/Originalni naučni rad

ONLINE LEARNING DURING THE PANDEMIC OF COVID-19: EXPERIENCES OF STUDENTS AND UNIVERSITIES

Ilija Savić*, Slavko Alčaković

Singidunum University, Belgrade, Serbia

Abstract:

The COVID-19 pandemic had a significant influence on university education and organization of lecturing. Most universities throughout the world had not been prepared for the new circumstances, and this ultimately affected both the organization and the quality of lectures.

Universities were obliged to follow trends and implement new strategies in lecturing in order to support their students where help was most required, and furthermore, in order to maintain the quality of their experiences and education. The objective of this research was to gain insight into how students reacted to the new pandemic situation and whether they are satisfied with online teaching so that universities could use the results to adapt and conduct online teaching in the future. The research found that students considered online learning had affected their efficiency, productivity, and level of motivation in the process of learning. Apart from these adversities regarding online teaching and learning, the survey found that the students’ attitude toward the implementation of technology in university education would improve the process of online lecturing and examination and enhance the present situation.

INTRODUCTION

Article info:

Received: August 19, 2022

Correction: September 06, 2022

Accepted: September 15, 2022

Keywords: Covid-19, Online learning, Information technology, ICT.

For a short period of time, the COVID-19 pandemic had a great impact on the entire economy, on every field and branch of society, and on university education, too. As indicated by UNESCO, it influ enced the education of over 220 million university students in the world (UNESCO, 2021). University education in the world had to undergo major changes, which required all its participants to adapt to the situation. Students were confused by the new teaching organization, teaching, and non-teaching staff were faced with completely new working conditions, and management had to make quick and risky decisions that could not be identified in advance (Marinoni, van’t Land, & Jensen, 2020). 1

1 This paper is an extended manuscript of a paper that was awarded at the 9th International Scientific Conference Sinteza 2022 (https://sinteza.singidunum.ac.rs/)

*E-mail: isavic@singidunum.ac.rs

One of the first and most prominent changes that occurred in the process of university education was in the lecturing process. The sudden closing of the university as a measure of social distancing has caused a complete change in the way lectures are held. The general face-to-face lecturing within the university premises was replaced by learning from one’s home by following the online lecturing platforms (Rashid & Yadav, 2020). Within a few days the traditional form of lecturing in the university premises, to which all employees, professors, and students had been used to, was transformed into online lecturing. The students, who had been accustomed to learning within university premises, were unprepared for these changes. In the past, online learning had been considered to be a method applicable to nonformal education. However, this method of lecturing turned out to be the solution to replace the traditional lecturing process (De Brouwer, Raimondi, & Moreau, 2020). Information and communication tech nologies (ICT) enable students and universities to take advantage of new educational opportunities that improve teaching and learning (Maatuk et al., 2022). Apart from the positive effect regarding online lecturing, this method of learning influenced the productivity and motivation of students in the process of learning. On the other hand, the initial response of many universities to the new situation applied ad-hock solutions in order to provide a swift and efficient solution. Recent studies indicate that many universities were forced to modify their lecturing process and apply online learning.

The purpose of this paper is to give an insight on how universities had transferred to new methods in the education process and to establish the positive and negative effects that online education had on students. Research had been undertaken to provide a better insight into the experience and opinions of university students and to establish the effect online learning had on them.

This paper consists of three sections. The first section covers the adaptation of universities in the world to the altered circumstances. The second deals with the students’ adjusting process, and the third is an analysis of the attitudes and challenges regarding online education and learning among university students in Serbia.

LITERATURE REVIEW

How did universities adapt to the Covid-19 situation?

Apart from the persisting crisis that COVID-19 had brought to the healthcare system, it had been followed by a socio-economic crisis, which influenced all aspects of life - its common functioning, businesses, and university education, too (Marinoni, van’t Land, & Jensen, 2020). It is common to define higher education as a set of specific and local organizations, roles, and interactions between subjects and economic transactions (Gumport, 2007). The consequences of the COVID-19 pandemic on higher education are negative on the global level. The new conditions are suitable for countries with underdeveloped education systems to implement new solutions and solve existing and new problems caused by the pandemic. Although many countries responded to disruptions in the education system in a timely manner by introducing new teaching models, some scientists predict a decline in the quality of acquired knowledge by students. It is necessary to pay a lot of attention to the maintenance of the quality of teaching and imparted knowledge (Pavlović et al., 2021) The adaptability of the business, changes in its organization, and an agile approach were required. Since the duration of the crisis could not be defined, this made it difficult to plan and create a strategy. Optimal measures undertaken to resolve a short crisis and provide a swift recovery might prove inefficient if the crisis lasts longer than planned (World Bank Group, 2020). Some universities had a straightforward response and reacted

SAVIĆ. I., ALČAKOVIĆ. S.  ONLINE LEARNING DURING THE PANDEMIC OF COVID-19: EXPERIENCES OF STUDENTS AND UNIVERSITIES

swiftly to the imposed changes and challenges, while others had a poor response in adopting online education, which presented a significant obstacle in adopting online learning methods and tools. One of the reasons is that online education requires more effort and different methods, in comparison to face-to-face education that had been previously applied (I. Elaine & Seaman, 2007). On the adaptation, impact, and changes in teaching, the following table shows that the percentage of higher education institutions where classes have been canceled is very low in all regions except Africa where classes have been suspended in most of the higher education institutions.

Table 1. Impact of COVID-10 pandemic on teaching and learning by region

Country Not affected

Africa 3%

America 3%

Asia & Pacific

Europe Almost 0%

Classroom teaching replaced by distance teaching and learning

Teaching suspended but the institutions is developing solutions Teaching canceled

Source: International Association of Universities, 2020

Karalis and Raikou stated that hasty solutions resulted in conflicting opinions and two diverging approaches. It was found in the former case that online education had been efficient and that one should focus on all its benefits (Karalis & Raikou, 2020). Singidunum University is an example of such a hasty reaction. When the State of Emergency was declared in Serbia on 13th March 2020, by which movements of its citizens had been restricted, within only 3 days the online education process was established through the Google Meet software. Thanks to the immediate response of both the management and employees, the students lost no lecture, exercise, or consultation (Singidunum University, 2020).

Digital technology has become one of the top priorities of higher education, and it directly affects all elements of the student experience (Bond et al., 2020). The students at the University of California and the University of Colorado complained of fatigue during their Zoom lectures. They solved this problem with the Otter for Education software (Otter, 2018) which offers online transcription and notes thus relieving students. The lecturers found this intelligent software to be extremely useful to the students with difficulties in learning and other difficulties previous to and during the online environment. In the online environment, remote testing posed a challenge for the lecturers. This was solved in over 500 institutions by applying the Examity validation system in the examination process. Here the examination process is based on biometric analysis of a push button, predictive analytics, and video review, by which the identity of the student is established, and the content of the examination preserved (Examity, 2022).

Chatbots have the ability to ask and answer questions, in this case from students or other interested users, without the involvement of university employees (Abdul-Kader & Woods, 2015). The Ocean County College had an e-mail communication problem and an engagement rate of only 10%. Then the college joined AdmitHub and initiated a chat box in 2017 named Reggie. In the second year of its implementation, the engagement soared for 26% and it was capable to answer 98% of the questions without requiring any human support (Mainstay, 2017).

LEARNING DURING THE PANDEMIC OF COVID-19: EXPERIENCES OF STUDENTS AND UNIVERSITIES

In a different case, Karalis and Raikou (Karalis & Raikou, 2020) stated that the introduction of information and communication technologies in university education might generally affect the quality of education, human relations, productivity, motivation, mental health, and other factors that are induced by the pandemic and by online learning. Apart from the mentioned successful adjusting to the online environment and implementation, certain universities noticed its negative consequences, too. Zhang and Gao (Gao & Zhang, 2020) wrote that professors at the Chinese universities noticed that the transfer to online education had been a challenge and presented an evolutionary environment for both lecturing and learning. When organizing online education one must consider the differences in education in a virtual environment, communication difficulties, the lack of concentration, and interaction with professors. Research made by the Organization for Economic Cooperation and Development found that less than 40% of lecturers considered themselves ready to use digital technologies for lecturing (OECD, 2020). High-performance digital education and improvement of digital skills and competence in online education must be considered a priority in online education. With the current global movement towards online teaching caused by COVID-19, technological improvements and solution-focused approaches would make a significant contribution to research and improvement of higher education (Seko & Lau, 2021). The increasing use of data and technology in education simultaneously affects the development of online learning platforms, learning analytics as well as the use of artificial intel ligence in education (Knighta, Gibson, & Shibani, 2020). The universities have to make changes in their organization and consider the differences and level gaps regarding digital skills in their professors, the improvement of their capacities, the better financial support of education and the following of the achieved results (Pavlović et al., 2021) Teaching staff are challenged to implement new ways of learning and research-based educational practices to facilitate students' acquisition and application of knowledge (Opre et al., 2022). But teaching staff who refuse to embrace change and learn and apply all the benefits of technology and online platforms will have to face the fact that this is not the future, but the present. Another big challenge for professors is the planning and preparation of new lectures that will be delivered online. The biggest challenges are creating a lesson plan, preparing exercises, practice tasks, defining evaluation criteria, and designing interactive activities. However, the fear of the aforementioned is unfounded in most cases. The essence of setting the general and specific goals of the course or subject, and defining the necessary practice tasks, content, and literature are very similar and do not change from the lecture model. All of the above is also applied during online classes with certain modifications so that students do not have difficulty understanding the things presented to them (Ko & Rossen, 2017). Besides, the COVID-19 pandemic affected the financial situation of universities. High expenses for buying new equipment, software, and other elements required for online lecturing brought serious financial consequences on the universities and dropped their income compared to the previous year. Technical solutions cannot be implemented without adequate resources in terms of quali fied people and, of course, finances (Børte, Nesje, & Lilljord, 2020). There was also a weaker financial situation among the students, so many were forced to skip their studies or postpone their exams. This further dropped the income of universities. Low income requires a reduction in expenses, hence in the reduction in the number of lecturers and other personnel (Burki, 2020). Burki found that Covid-19 pandemic cost Universities in Great Britain about 790 million pounds. Facing these challenges some institutions were forced to completely cancel lecturing. The report of the International Association of Universities (Marinoni, van’t Land, & Jensen, 2020) stated that 43% of universities in Africa had to make a pause in lecturing during the period of their seeking solutions by the institution, while in 24% of universities the lecturing had been completely terminated.

SAVIĆ. I., ALČAKOVIĆ. S.  ONLINE LEARNING DURING THE PANDEMIC OF COVID-19: EXPERIENCES OF STUDENTS AND UNIVERSITIES

Adaptation of students to the situation caused by COVID-19

After the universities had transferred to the new forms of lecturing the students were forced to follow lectures and exercises via certain online platforms. In comparison to certain professors, the students had less problems in adapting to new solutions. Nowadays students grew up using technologies. Prensky (Prensky, 2001) stated that they are “digital native” because their comprehension, learning and every day behavior is different compared to the elder generations, including lecturers with few digital skills. It is obvious that the lecturers are more and more aware of these differences and strive to learn and adopt the required skills to be able to participate in an interactive and efficient online environment. In a relatively short period of time, millions of people, including many students, have signed up for MOOCs (massive open online courses) which can have a negative impact on higher education (Pozón-López et al., 2021). However, many students had limited access to the lectures, either because of possessing inappropriate devices or had poor internet links. There is also a “digital disbalance” in society, therefore not all students had an appropriate communication environment outside the university for them to be able to transfer to online education (Rashid & Yadav, 2020). At the basis of human achievements is hard work, dedication, and strong motivation to achieve success. Students with high achievement motiva tion are ready to adapt to new conditions, to take risks and to persevere in an environment they are not used to. This leads to the conclusion that the level of motivation is at different level from student to student (Babić & Kordić, 2014). The influence of professors on students was limited, thus the students’ achievements in learning generally depended on their own efforts, i.e., their motivation, productivity, discipline, and proactivity (Gao & Zhang, 2020). In an online environment, students have to control their time, be attentive and learn. Students must be devoted, persistent and have self-control. Authors from the town of Novi Sad concluded that their students were not very satisfied with online education and that had higher expectations. Maybe they generally expected more from online education, and their expectations were not fulfilled. The research found that their average opinion regarding online education was below average (Grubić-Nešić, Milić, & Tomić, 2021). Factors that lead to student satisfaction with online teaching are a clear course structure, good organization of lectures, availability of professors and a sense of community in the online environment (McInnerney & Roberts, 2004). Dumford and Miller states that the students with a larger number of online courses reported that teaching effectiveness declined and that the quality of interactions with colleagues and professors. significantly reduced (Dumford & Miller, 2018). The pandemic has an impact on people's physical health, however, after all the experi ences related to the quarantine period and a completely changed lifestyle, the pandemic had a great impact on people's psychological health as well (Marić, 2021). Although previous surveys found that children and youngsters had mild forms of Covid-19 compared to adults, the surveys from the School of Medicine in Belgrade found that they are more prone to develop mental consequences. Among the mental consequences in youngsters, anxiety was the greatest problem because of the lack of contact with their colleagues, and diminished control of stress (Grujičić et al., 2020) Also, in a situation where the whole world, including medical workers and scientists in the field of medicine, encountered an unexplored virus, it is expected that a large amount of information, but also disinformation, will spread very quickly. The biggest problem for people's mental health is excessive exposure to multiple sources of information. Television, radio, portals, and social media are channels through which information spreads very quickly. People's lives and daily habits have changed, and this has had a great impact on the mental health of the population from every age category (Grujičić et al., 2020)

ONLINE LEARNING DURING THE PANDEMIC OF COVID-19: EXPERIENCES OF STUDENTS AND UNIVERSITIES

Two surveys found that the lack of presence in university premises had a bad impact on students. This was not the case only in Serbia but elsewhere, too. Social relations may have a significant influence and motivate one to study, which has an effect on academic success. The multiple obligations, continuous struggle to have good merits, lack of free time, the introduction of online education, new experimental methods applied in education put stress on the students, which might develop into more severe mental health issues (Ilić-Živojinović, 2015). A large amount of stress can be explained as "a state of mental or emotional strain or tension". Stress can lead to depression, panic, anxiety, sadness, pessimism, and lack of self-confidence (Zotović, 2002). In the second study on this subject, Tull and his partners found that staying at home, online education, and the stress that it brought resulted in an increased level of anxiety, financial worries, and loneliness. The lack of relations with people belonging to the same age group and their interactions and complete change in everyday habits may affect the mental health of students, their mood, motivation, and academic success (Tull, et al., 2020).

METHODOLOGY

The research in Serbia was undertaken in December 2021 with 454 participants. They were students from several universities, colleges, modules and branches of online education. The ratio of participants was 73,6% female and 26,4% male students. They were classified according to their year of study, though most of them were in the first year of study (26,4%). There were 19,6% from the second year, from the third 22,2%, and from the fourth year 19,8 participants. The least incorporated were those on master studies (11%) and PhD studies (0,9%).

The instrument applied was a created Google questionary, which the students would have to fill in online, for the purpose of this empiric research. It was distributed to the participants by mail and social networks. All participants that took part in the research were guaranteed anonymity and had been told that their answers would solely be used for research. The main research technique was the questionary, which was to establish the attitude of the participating students on the challenges they met when learning and acquiring knowledge in an online environment. The questionary consisted of 6 questions, of which the first two focused on one’s general opinion regarding online education and its efficiency. The next two questions focused on the motivation and productivity of online education. The last two questions were about the participants’ opinions on implementing technology in education and the online environment. The questions were closed type and the research had an empirical character. After completing the questionnaire online, the results were summed, and an analysis based on the results had been made. The analysis of the results applied was in the descriptive method.

LEARNING DURING THE PANDEMIC OF COVID-19: EXPERIENCES OF STUDENTS AND UNIVERSITIES

RESULTS AND DISCUSSION

The first question was about the attitude of the participants regarding online learning. The students’ answers were based on their experience after many months of learning in an online environment and their opinion regarding its efficiency.

1. Students' opinion on the effectiveness of online teaching

at all

Graph No.1 indicates that as much as 60,8% of the participants consider online learning relatively efficient. However, one should consider the number of participants that found it not at all efficient was 25,3%. Only 13,9% considered online learning very efficient. This co-insides with the previous research (Grubić-Nešić, Milić, & Tomić, 2021) which found a decline regarding online learning efficiency. These results clearly indicate that online education should be accustomed to students and should undergo further adjustment.

Graph 2. Online teaching equally helps in the acquisition of knowledge in relation to classical teaching

Graph No. 2 shows us to which extent do the students consider that online learning manages one to acquire knowledge and skills in online learning compared to standard (direct) learning. As much as 33% of the participants consider that they did not achieve equal skills and knowledge through online learning. If considering those that disagreed in certain aspects, this number reached 58,35% of participants. Only 8% of the participants absolutely agree that they had acquired the amount of knowledge and skills as if by standard learning.

Graph 3. Students' opinion on whether online teaching has affected the decline in productivity

in certain aspects

Graph No. 3 indicates that online learning reduced productivity in learning. 39,9 % of participants considered that online learning had affected their productivity, and if we include those who considered that it affected their learning to a certain degree, the percentage of those whose opinion was that online learning had a negative influence on their learning reaches 67,2%. Only 8% of the students were of a neutral opinion. When compared to the statements of Karalis and Raikou (Karalis & Raikou, 2020), who stated that the introduction of technology in university education might affect one’s productivity, our results confirm their standpoint.

Graph 4. The level of motivation of students while attending online classes

Graph No. 4 presents the average motivation level in students regarding online learning. Merit 1 indicates a very low level of motivation while merit 5 indicates a very high level of motivation. The average merit is 2,68. Only 8,4% of students were motivated by online learning, while approximately half of the participants (47,4%) said that their motivation was low. The results and the answers of the participants comply with the opinions of the authors of the existing research.

Graph 5. Technological solutions in online teaching would increase productivity and motivation to learn

Absolutely disagree

in certain aspects

agree nor disagree

in certain aspect

Graph No. 5 presents the opinion of students when technology and smart tools had been applied in online learning, whereby 64,7% of students said that the application of technology absolutely helped them and also improved their learning, while 34,1% agree it helped in certain aspects. The implementation of technology and smart tools in university education might have been completely strange to some students, and this is indicated by the 22,5% of students with a neutral opinion. Modern technologies have infiltrated not only the entire industry and business branches but the highest levels of education, too. This development of technologies forces universities all over the world to keep step with the trends and use all the benefits that technologies provide.

Graph 6. The use of technology and smart tools would enhance online learning

disagree Disagree in certain aspects

agree

disagree

in certain aspect

Finally, the students were asked to analyze their attitudes regarding the implementation of technology in lecturing and examinations. Out of 454 participants in the research, 68,5% considered that technology solutions adapted to online learning would eliminate the existing disadvantages of online learning. Although the students generally had an adverse opinion regarding online learning, according to their opinions we think that something could be done for it to be improved. Useful new solutions applicable for online learning and improvement of the reduced productivity and motivation in learning would bring them more free time. The number of students that do not believe in the potential and positive effect on online education present 7,5% of the participants.

CONCLUSION

The entire world population had been affected by the COVID-19 pandemic and many universities, likewise. The university education had undergone sudden changes, which required adjustment of the lecturers, of other staff members, and of students. One of the first and most important changes was the change in the form of lecturing. The traditional lecturing within the university premises had to be transferred to online platform lecturing.

The universities and their management were forced to hastily adopt and implement certain changes in the organization of their business. Certain universities had done this without any difficulty and swiftly, while others significantly lacked the flexibility and capacity to adapt to the online lecturing process.

Young university students had no problem in adopting new solutions, compared to the elder students and lecturers lacking digital skills. The duration of the COVID-19 pandemic throughout several semesters of online learning had a negative influence on the productivity, motivation, and general satisfaction of the students regarding acquired knowledge. The lack of free time, the new form of lecturing, the experimental forms applied in them, as well as the social distance had brought serious consequences on the mental health of students.

Based on the collected and analyzed data, we found that the sudden change in the lecturing process had an adverse effect on the satisfaction of university students in Serbia. In online learning, the efficiency, productivity, and motivation in students were low when compared to the traditional form of lecturing. The present experience of the students confirms the assumption that the implementation of technology in the lecturing and examination activities would significantly improve these parameters. Online teaching implies implementation of technology in any teaching context. The use of artificial intelligence can make it easier for professors to perform tasks such as checking the validity of tests or reviewing assignments, while students can more easily take notes during lectures with the help of smart software. The current lectures of professors can be further improved by developing distance learning software that can be easier to use and more interactive. Also, non-teaching staff can more easily communicate with students using chatbots based on artificial intelligence. The goal of using modern software and technology is to save time and increase the accuracy of the daily activities of professors, students, and all other university employees. Since we are living in a digital era in which the high educated population are daily exposed to challenges and changes, in future research will apply longitudinal methods, i.e., repeat the research regarding online learning to establish whether after a lapse of time there have been significant improvements. The plan is to create and distribute a questionnaire each year in order to analyze the situation and the attitude of students regarding online learning.

SAVIĆ. I., ALČAKOVIĆ. S.  ONLINE LEARNING DURING THE PANDEMIC OF COVID-19: EXPERIENCES OF STUDENTS AND UNIVERSITIES

ONLINE LEARNING DURING THE PANDEMIC OF COVID-19: EXPERIENCES OF STUDENTS AND UNIVERSITIES

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SAVIĆ. I., ALČAKOVIĆ. S.  ONLINE LEARNING DURING THE PANDEMIC OF COVID-19: EXPERIENCES OF STUDENTS AND UNIVERSITIES

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ISKUSTVA UNIVERZITETSKIH STUDENATA I NJIHOVI STAVOVI PREMA ONLINE UČENJU TOKOM PANDEMIJE COVID-19

Rezime:

Pandemija COVID-19 imala je značajan uticaj na univerzitetsko obrazovanje i organizaciju predavanja. Većina univerziteta širom sveta nije bila pripremljena za novonastale okolnosti, što je na kraju uticalo i na organizaciju i na kvalitet predavanja. Univerziteti su bili u obavezi da prate trendove i implementiraju nove strategije u nastavi kako bi podržali svoje studente tamo gde je pomoć bila najpotrebnija, a štaviše, kako bi zadržali kvalitet svog iskustva i obrazovanja. Cilj ovog istraživanja bio je da se stekne uvid u to kako su studenti reagovali na novu situaciju uzrokovanu pandemijom i da li su zadovoljni onlajn nastavom, kako bi univerziteti mogli da koriste rezultate za prilagođavanje i sprovođenje onlajn nastave u budućnosti. Istraživanje je pokazalo da studenti smatraju da je učenje putem interneta uticalo na njihovu efikasnost, produktivnost i nivo motivacije u procesu učenja. Osim ovih nedaća u vezi sa onlajn nastavom i učenjem, istraživanje je pokazalo da bi stav studenata prema primeni tehnologije u univerzitetskom obrazovanju unapredio proces onlajn predavanja i ispita i poboljšao sadašnju situaciju.

Ključne reči: Covid-19, Onlajn učenje, Informacione tehnologije, IKT.

COVID-19: EXPERIENCES OF STUDENTS AND UNIVERSITIES

EJAE 2022, 19(2): 97 - 113 ISSN 2406-2588

UDK: 658.14/.17:654.17/.19(497.11)"2020" 657.44

DOI: 10.5937/EJAE19-39525

Original paper/Originalni naučni rad

FINANCIAL ANALYSIS OF THE BROADCASTING SERVICE OF DIGITAL TELEVISION, RADIO PROGRAMS AND DATA TRANSMISSION IN THE REPUBLIC OF SERBIA

Faculty of Technical Sciences, University of Pristina in Kosovska Mitrovica, Kosovska Mitrovica, Serbia

Abstract:

Digitalization of radio and television programs as well as other multi media content is a very complex process with many aspects and requires large financial investments in the infrastructure of the system and all supporting elements. This paper provides a concise description of the institutional and regulatory frameworks in the digitalization process in the Republic of Serbia, the important reasons related to the choice of compression standard and standard for the transmission of television signals, as well as a description of the role of JP Emisiona tehnika i veze in the digitalization process. The aim of this paper is the financial analysis of earnings on an annual basis for the services of broadcasting TV programs in the first and second multiplexes, broadcasting radio programs within the DVB-T2 network and data transmission services after the digitalization process. The method and data required for the preparation of the financial analysis were derived on the basis of the price list of services published by the JP Emisiona tehnika i veze published in August 2020. The results are presented tabular and graphically.

INTRODUCTION

Article info:

Received: Jul 08, 2022

Correction: September 05, 2022

Accepted: September 16, 2022

Keywords: Digitalization, Digital television, Digital data transmission, DVB-T2, Financial analysis.

Digital television introduces a new era of broadcasting, many technical innovations that enable a significant increase in capacity and adaptability of networks, thereby opening numerous opportunities in terms of improving the quality of existing services and introducing new ones. (Shin & Song, 2012)

Some of the many advantages of digital television compared to the analog one are: better image and sound quality, digital signal reception which is more resistant to the influence of various interferences, lower transmission costs, capability of transmitting a greater number of channels and services, more efficient use of radio frequency spectrum, etc. (Petrović, Jakšić, Spalević, Milošević & Lazić, 2014)

Digital TV users are offered more diverse content through various transmission platforms and freedom to choose individual services in the form that suits them best. (Jakšić, Milošević, Jakšić, Maksimović & Todorović, 2022)

*E-mail: jelena.stojkovic@pr.ac.rs

Jelena Cerovina*, Ivana Milošević, Milan Simić

In 2009, the Republic of Serbia started the process of digitalization radio and television programs by adopting the Strategy for Switchover from Analog to Digital Broadcasting of radio and television programs. The strategy establishes basic strategic guidelines for the introduction of digital and the shutdown of analog television and radio programs, which are in line with the conclusions of the Regional Conference on Radio Communications of the International Telecommunication Union held in Geneva in 2006, according to which it was determined that the introduction of digital and the complete shutdown of analog television in Europe will be completed by June 17, 2015 at the latest (Ministry of Trade, Tourism and Telecommunications, 2013).

The original deadline for the completion of the digitalization process in Serbia, set for 2012, was missed due to the lack of financial resources and insufficient number of free frequencies. The problem was solved by relinquishing part of the frequency of Avala television, after the channel was shut down, for broadcasting a digital signal. The new deadline was set for 2013. However, this deadline was also missed due to technical problems. The digitalization process was completed on June 7, 2015, which was concluded based on the official data from the relevant ministry on the coverage of the territory of Serbia with a digital signal, as well as the confirmation from the international organizations (EU and OSCE) that the process was completed.

According to the data of the JP Emisiona tehnika i veze the earnings were many times higher than the funds invested in the digitalization process, i.e., in the amount of 37.5 million euros including 13.5 million euros received as donations from the European Union within the project “Assistance for the transition to digital broadcasting in Serbia" implemented in 2009 by the Ministry of Telecommunica tions and Information Society. A total of 13.5 million euros was invested in the equipment necessary for the reconstruction of transmission system for transmitting digital TV signals through network of ground transmitters. This equipment included TV transmitters worth 3 million euros, multifunctional transmission network worth 1.5 million euros, terminal and network equipment worth 2 million euros, antenna systems worth 3.5 million euros, communication and control-measurement equipment worth 3.5 million euros. Earnings from digitalization are estimated at more than 100 million euros (Ilić et al., 2017; Ministry of Telecommunication and Information Society, 2009).

In accordance with the provisions of the Law on Broadcasting, the former Radio Television of Serbia was divided into the national public broadcasting service and the public service of the province RTV Vojvodina (Ministry of Trade, Tourism and Telecommunications, 2002). Taking these provisions into account, this paper presents a financial analysis of TV program broadcasting services with unconditional access to Public Media Institutions (RTS and RTV), holders of licenses to broadcast TV programs in the entire territory of the Republic of Serbia, holders of licenses to broadcast TV programs in regional and local areas; as well as the service of broadcasting radio programs within the DVB T2 network and data transmission. The financial analysis was performed on the basis of the price list of services published by JP Emisiona tehnika i veze in August 2020 (JP Emisiona tehnika i veze, 2020).

EJAE

CEROVINA. J., MILOŠEVIĆ. I., SIMIĆ. M.  FINANCIAL ANALYSIS OF THE BROADCASTING SERVICE OF DIGITAL TELEVISION, RADIO PROGRAMS AND DATA TRANSMISSION IN THE REPUBLIC OF SERBIA

INSTITUTIONAL AND REGULATORY FRAMEWORK FOR TELEVISION DIGITALIZATION IN THE REPUBLIC OF SERBIA

The process of switching from analog to digital TV broadcasting requires government intervention (Ariansyah & Yuniarti, 2021). In this process, a key role is played by the government, regulatory bodies, media public service, commercial broadcasters, network operators, equipment manufacturers, authorized persons for the installation and maintenance of common antenna systems and cable distribution systems (Trujillo, 2013). In order to adopt an appropriate regulatory policy, it is necessary to understand the environment in which the radio and television industry operates, given that with the expansion and technological progress of the Internet, users can access information and entertainment contents using other media apart from radio and television (Hauge, 2014).

The first goal of the Broadcasting Switchover Strategy from analog to digital TV broadcasting is to define legislative activities in order to create a legal framework for digital broadcasting development in accordance with the international and European standards. When creating the new regulatory framework, the specifics of the legal system of the Republic of Serbia were taken into account, as well as the existing rights and market position of the broadcasters, holders of licenses for broadcasting programs that were valid even after the scheduled date for turning off analog broadcasting. The regu latory framework in the Republic of Serbia consists of the Strategy for the Development of the Public Information System in the Republic of Serbia, the Strategy for the Development of Broadcasting in the Republic of Serbia, the Strategy for the Development of Electronic Communications in the Republic of Serbia, the Strategy for the Development of the Information Society in the Republic of Serbia, the Law on Electronic Communications, the Law on Broadcasting, the Law on Public informing (Ministry of Trade, Tourism and Telecommunications, 2013).

The Strategy for the Development of the Information Society in the Republic of Serbia, together with the Strategy for the Development of Electronic Communications in the Republic of Serbia, defines the digital agenda of the Republic of Serbia. In accordance with the Strategy, the priorities in development of the information society are the transition to exclusively digital broadcasting of television and radio programs and the digital dividend (Šuput, 2014).

The Law on Electronic Communications resolves some of the issues that are very important for the functioning and development of electronic communications, such as: regulation of conditions and methods for performing activities in the field of electronic communications; design, construction or installation, use and maintenance of electronic communication networks, associated assets, electronic communication equipment and terminal equipment; management, use and control of the radio frequency spectrum; distribution and broadcasting of media content; protection of the rights of users and subscribers; security and integrity of electronic communication networks and services (Šuput, 2014).

The Law on Broadcasting regulates the conditions and manner of performing broadcasting activities, in accordance with the international conventions and standards, the establishment of RRA, as well as public broadcasting service institutions, determines conditions and the procedure for issuing licenses for broadcasting radio and television programs (Ljubojev & Dukić-Mijatović, 2018).

The Law on Public Information regulates the right to public information as the right to freedom of expression, as well as the rights and obligations of participants in the process of public information (Ministry of Trade, Tourism and Telecommunications, 2021).

EJAE

CEROVINA. J., MILOŠEVIĆ. I., SIMIĆ. M.  FINANCIAL ANALYSIS OF THE BROADCASTING SERVICE OF DIGITAL TELEVISION, RADIO PROGRAMS AND DATA TRANSMISSION IN THE REPUBLIC OF SERBIA

THE CHOICE OF STANDARDS IN THE FIELD OF DIGITAL TELEVISION AND THE ROLE OF PUBLIC COMPANY ETV IN THE DIGITIZATION PROCESS

Digital Video Broadcasting-Terrestrial standard (DVB-T) has successfully replaced the analog terrestrial transmission for video broadcasting in Europe (Samo, Slimani, Barrufa & Rugini, 2015, p.35). DVB-T has brought a higher quality service to TV program and has reduced use of bandwidth (Ayat, Hardani, Mirzakuchaki & Haddadi, 2016, p.43). The ITU has presented a model of the digital television system that is the basis for all implementations of the DVB system. The model consists of 4 subsystems, and in some approaches of 3 subsystems. The source encoding and compression subsystem uses data compression methods and error protection techniques applied to video, audio, and auxiliary digital data streams. The multiplex service and transport subsystem enables division of the digital data stream into information packets, unique identification of each packet or packet type, and multiplexing of video, audio, and auxiliary data stream packets into a single data stream. The physical layer subsystem (adaptation) uses information about the digital data stream to modulate the transmitted signal (Antone & Arsinte, 2013, p.48).

The success of DVB-T and the development of technical innovations resulted into the definition of the second-generation standard for digital terrestrial video broadcasting (DVB-T2), which was approved as a European standard in June 2008 (Samo et al., 2015, p.35). By switching from DVB-T to DVB-T2 standard, it is possible to expand the capacity of the digital television system to about 25% which would enable greater competition among active broadcasters on the market (D'Andreagiovanni, Lakhlef & Nardin, 2020). DVB-T2 uses OFDM (orthogonal frequency division multiplex) modulation. DVB-T2 standard allows high flexibility in multiplex allocation, coding, modulation, and RF parameters (Eizmendi et al., 2014, p.259). OFDM is a powerful modulation technique that achieves a high bit rate. With this technique, it is possible to divide the stream of digital data into several streams that are then transmitted on several frequency subcarriers located close to each other in the spectrum and characterized by orthogonality, that is, there is no interference between them, even though there are no guard bands (Yu & Sadeghi, 2012). “OFDM technique enables the creation of broadband multiplex by generating a single multiplex covering multiple broadcasting frequency channels, without changing of the space between them, and keeping the symbol and guard interval duration unchanged compared to the one in single channel case” (Mišković & Reljin, 2015, p.70). In order to transmit more services within the frequency range of TV channels (TV program, radio program, teletext) through the DVB-T2 system, it is necessary to apply the technique of coding (compressing) audio-video content and its multiplexing (Iacob, Demciuc & Avram., 2020).

JP Emisiona tehnika i veze decided to choose the DVB-T2 standard for digital terrestrial broad casting of television signals. The choice of this standard is based on the following facts: DVB-T2 offers extremely good signal protection; it is less sensitive to interference compared to DVB-T; within one multiplex a much larger number of TV programs in SD and HD resolution can be broadcast compared to the DVB-T standard, which increases the digital dividend (Oria, Lopez, Doblado, Perez Calderon & Baena, 2014). “SDTV is usually transmitted in resolution 720x576, while HDTV is using 1920x1080 resolution“ (Galetic, 2020).

The DVB-T2 standard is based on the choice of the MPEG-4 version 10 (H.264/AVC) standard for video signal compression. Some of the characteristics of MPEG-4 version 10 (H.264/AVC) standard are: encoders based on this standard require twice the lower bit rate, and subjectively, the quality of the reconstructed video signal is almost the same compared to MPEG-2 (Erol, Kossentini, Joch, Sullivan &

EJAE

CEROVINA. J., MILOŠEVIĆ. I., SIMIĆ. M.  FINANCIAL ANALYSIS OF THE BROADCASTING SERVICE OF DIGITAL TELEVISION, RADIO PROGRAMS AND DATA TRANSMISSION IN THE REPUBLIC OF SERBIA

Winger, 2009); the picture quality of MPEG-4 standard, according to the important international televi sion associations, is equally good at low and high flows (both for SDTV and HDTV) (Jaksić, Petrović, Jaksić, Milošević & Marinković, 2016); MPEG-4 standard is compatible with IPTV (Al-Jobouri, Fleury & Ghanbari, 2014); it provides support for all the new multimedia services; providing this standard is important because it requires much less throughput compared to DVB-T2.

JP Emisiona tehnika i veze establishes and manages a network for distribution, broadcasting and multiplexing of digital television programs. In order to manage that network, JP Emisiona tehnika i veze issues individual licenses for the use of radio frequencies in accordance with the law regulating the field of electronic communications. JP Emisiona tehnika i veze provides access to the multiplex to institutions of the public broadcasting service and holders of valid licenses for broadcasting television programs that were issued on the basis of a previously held public competition in accordance with the regulations governing broadcasting. Technical and commercial conditions are governed by the contract that the JP Emisiona tehnika i veze concludes with public broadcasting service institutions and holders of valid licenses for broadcasting television programs (Ministry of Trade, Tourism and Telecommunications, 2013).

METHODOLOGY

The financial analysis of the services of broadcasting TV programs, radio programs within the DVB T2 network and data transmission was carried out based on the price list of services published by the Emisiona tehnika i veze in August 2020.

Method 1: According to the Rulebook on the switchover from analog to digital broadcasting of television programs and access to the multiplex, the first multiplex is filled with programs from public media services in the Republic of Serbia and holders of licenses for broadcasting television programs throughout the Republic of Serbia. The second multiplex is filled with television broadcasting services for which a license has been issued to broadcast television programs in regional and local areas in accordance with the law (Ministry of Trade, Tourism and Telecommunications, 2015).

According to the data in the register of medical service providers on the website of the Regulatory Body for Electronic Media and based on the list of TV programs by distribution zones on the website of JP Emisiona tehnika i veze, 8 TV programs in SD resolution are broadcast in the distribution zones of Sombor, Subotica, Kikinda and Vršac within the first multiplex. In distribution zones Avala, Cer-Maljen, Deli Jovan, Rudnik-Crni Vrh, Ovčar-Tornik, Tupižnica, Jastrebac, Kopaonik, Besna Kobila, 7 TV programs in SD resolution, 1 TV program in HD resolution and 3 radio programs in DVB-T2 networks in the first multiplex (Regulatory body for electronic media, 2022; JP Emisiona tehnika i veze, 2022).

In accordance with the above-mentioned data, the total monthly price of TV program broadcasting services for Public Media Institutions (RTS and RTV) and license holders for broadcasting TV programs throughout the Republic of Serbia is obtained as the sum of individual TV program prices for each distribution zone from Table 1 multiplied by a commercial correction factor, which is 0.73 for SD resolution and 0.45 for HD resolution. The prices in Table 1 are taken from the price list of services published by JP Emisiona tehnika i veze for the service for which the salary calculation is made.

CEROVINA. J., MILOŠEVIĆ. I., SIMIĆ. M.  FINANCIAL ANALYSIS OF THE BROADCASTING

SERVICE OF DIGITAL TELEVISION, RADIO PROGRAMS AND DATA TRANSMISSION IN THE REPUBLIC OF SERBIA

Table 1. Individual prices of TV programs for the service of broadcasting TV programs for Public Media Institutions (RTS and RTV) and holders of licenses for broadcasting TV programs in the entire territory of the Republic of Serbia for each distribution zone in SD and HD resolution.

Distribution zones

SD resolution Price (dinars)

HD resolution Price (dinars)

Avala 1.748.291,71 4.370.729,28

Besna Kobila 205.198,56 512.996,39

Cer – Maljen 340.629,61 851.574,01

Crveni Čot 800.274,38 2.000.685,94

Deli Jovan 131.327,08 328.317,69

Jastrebac 693.571,13 1.733.927,81

Kikinda 168.262,82 420.657,04

Kopaonik 155.950,90 389.877,26

Tornik – Ovčar 439.124,91 1.097.812,28

Rudnik – Crni Vrh 496.580,51 1.241.451,27

Sombor 94.391,34 235.978,34

Subotica 201.094,59 502.736,47

Tupižnica 180.574,73 451.436,83

Vršac 82.079,42 205.198,56

Figure 1. Graphic display of individual TV program prices for TV program broadcasting services for Public Media Institutions (RTS and RTV) and license holders for broadcasting TV programs in the entire territory of the Republic of Serbia for each distribution zone in SD and HD resolution

Avala Besna Kobila Cer-Maljen Crveni Čot

Deli Jovan Jastrebac Kikinda Kopaonik

Tornik-Ovčar Rudnik-Crni Vrh Sombor Subotica

Tupižnica Vršac

SD resolution

HD resolution

Method 2: In the second multiplex, the following number of TV and radio programs are broadcast by distribution zone: in Sombor and Subotica, 5 TV programs in SD resolution, 1 TV program in HD reso lution and 3 radio programs within the DVB-T2 network; in Kikinda, 4 TV programs in SD resolution, 1 TV program in HD resolution and 3 radio programs within the DVB-T2 network; in Crveni Čot, 10 TV programs in SD resolution, 1 TV program in HD and 3 radio programs; in Vršac, 8 TV programs in SD resolution, 1 TV program in HD and 3 radio programs; in the Avala zone, 3 TV programs are broadcast in SD resolution; in Cer-Maljen and Besna Kobila zones, 7 TV programs in SD resolution; in Deli Jovan zone, 10 TV programs in SD resolution; in the area Rudnik-Crni Vrh, 11 TV programs in SD resolution; in Ovčar-Tornik zone, 14 TV programs in SD resolution; in Tupižnica zone, 8 TV programs in SD resolution; in Jastrebac zone 13 TV programs in SD resolution; in Kopaonik zone 12 TV programs in SD resolution (Regulatory body for electronic media, 2022; JP Emisiona tehnika i veze, 2022).

In accordance with the above-mentioned data, the total monthly price of the TV program broadcasting service by distribution zone, for holders of licenses for broadcasting TV programs in regional and local areas, is obtained as the sum of the individual prices of TV programs for the desired distribution zone from Table 2 multiplied by the commercial corrective by a factor that is 0.2 for both SD and HD resolution. The prices of TV programs by distribution zones in Table 2 are taken from the price list of services published by JP Emisiona tehnika i veze.

Table 2. Individual prices of TV programs by distribution zone of the TV program broadcasting service, for holders of licenses for broadcasting TV programs in regional and local areas.

Distribution zones

SD resolution Price (dinars)

HD resolution Price (dinars)

Avala 1.748.291,71 4.370.729,28

Besna Kobila 136.799,04 341.997,60

Cer – Maljen 227.086,40 567.716,00

Crveni Čot 800.274,38 2.000.685,94

Deli Jovan 87.551,38 218.878,45

Jastrebac 462.380,75 1.155.951,88

Kikinda 168.262,82 420.657,04

Kopaonik 103.967,27 259.918,18

Tornik – Ovčar 292.749,94 731.874,85

Rudnik – Crni Vrh 496.580,51 1.241.451,27

Sombor 94.391,34 235.978,34

Subotica 201.094,59 502.736,47

Tupižnica 120.383,15 300.957,88

Vršac 82.079,42 205.198,56

FINANCIAL ANALYSIS OF THE BROADCASTING SERVICE OF DIGITAL TELEVISION, RADIO PROGRAMS AND DATA TRANSMISSION IN

Figure 2. Graphic display of individual prices of TV programs by distribution zones of TV program broadcasting service, for holders of licenses for TV program broadcasting in regional and local areas.

5000000

4000000

3000000

2000000

1000000

0

SD resolution

HD resolution

Avala Besna Kobila Cer-Maljen Crveni Čot

Deli Jovan Jastrebac Kikinda Kopaonik

Tornik-Ovčar Rudnik-Crni Vrh Sombor Subotica

Tupižnica Vršac

Method 3: The broadcasting service of radio programs within the DVB T2 network includes reception of the modulation signal, coding, multiplexing, distribution, and broadcasting through a network of digital, terrestrial transmitters and repeaters. The total monthly price of the service is obtained as the sum of the price per radio program multiplied by the commercial correction factor given in Table 3. The price per radio program is taken from the price list of services published by JP Emisiona tehnika i veze. In the first and second multiplex in all distribution zones, 3 radio programs are broadcast each within the DVB-T2 network.

Table 3. The price per radio program of the broadcasting service of radio programs in the DVB T2 network by all distribution zones Service

Type of signal Price (dinars)

Commercial correction factor

Broadcasting of radio programs in the DVB T2 network Stereo audio signal 320.664 0,5

Method 4: According to the Article 8 of the Rulebook on switchover from analog to digital broad casting of television programs and access to the multiplex, the data flow within the multiplex is at least 2Mb/s per individual television program broadcast in SD resolution and at least 5Mb/s in HD resolution (Ministry of Trade, Tourism and Telecommunications, 2015). Table 4 gives the prices for individual capacity that falls within the corresponding range of capacities taken from the price list of services published by JP Emisiona tehnika i veze. The total monthly price of the data transmission service by distribution zones in Table 8 is obtained when the leased capacity expressed in Mbps (megabits per second) is multiplied by the price for the capacity range in Table 4. The price of the data transmission service refers to the data flow per individual TV program in SD and HD resolution.

CEROVINA. J., MILOŠEVIĆ. I., SIMIĆ. M.  FINANCIAL ANALYSIS OF THE BROADCASTING SERVICE OF DIGITAL TELEVISION, RADIO PROGRAMS AND DATA TRANSMISSION IN THE REPUBLIC OF SERBIA

ANALYSIS OF

SERVICE OF DIGITAL

TRANSMISSION

Table 4. Price of individual capacity in the corresponding capacity range of the data transmission service.

Capacity Price (dinars)

1Mbps-3Mbps 8.474,58 4Mbps-7Mbps 7.203,39 8Mbps-15Mbps 5.508,48 16Mbps-31Mbps 3.813,56 32Mbps-50Mbps 2.254,37 51Mbps-99Mbps 1.525,42 100Mbps-149Mbps 1.186,44 150Mbps-200Mbps 1.016,95

Tornik – Ovčar 292.749,94

Rudnik – Crni Vrh 496.580,51

AND

Figure 3. Graphic display of individual prices of the leased capacity in the corresponding capacity range of the data transmission service.

Pojedinačna cena 1Mbps-3Mbps 4Mbps-7Mbps 8Mbps-15Mbps 16Mbps-31Mbps 32Mbps-50Mbps 51Mbps-99Mbps 100Mbps-149Mbps 150Mbps-200Mbps

RESULTS AND DISCUSSION

Using method 1 and using prices based on the data from Table 1, the following results were obtained, presented tabular and graphically (Table 5 and Figure 4).

Table 5. Total prices on a monthly basis for broadcasting TV programs for Public Media Institutions (RTS and RTV) and licensees for broadcasting TV programs throughout the Republic of Serbia for each distribution zone in SD and HD resolution

Distribution zones

SD resolution Price (dinars)

HD resolution Price (dinars)

Avala 8.933.770,64 1.966.828,18

Besna Kobila 1.048.564,64 230.848,376

Cer – Maljen 1.740.617,31 383.208,305 Crveni Čot 4.673.602,38 /

Deli Jovan 671.081,379 147.742,961

Jastrebac 3.544.148,47 780.267,515 Kikinda 982.654,869 /

Kopaonik 796.909,099 175.444,767

Tornik – Ovčar 2.243.928,29 494.015,526

Rudnik – Crni Vrh 2.537.526,41 558.653,072

Sombor 551.245,426 /

Subotica 1.174.392,41 /

Tupižnica 922.736,87 203.146,574

Vršac 479.343,813 /

Figure 4. Graphic display of total prices for monthly TV programs for Public Media Institutions (RTS and RTV) and license holders for broadcasting TV programs throughout the Republic of Serbia for each distribution zone in SD

Avala Besna Kobila Cer-Maljen Crveni Čot Deli Jovan

Jastrebac Kikinda Kopaonik Tornik-Ovčar Rudnik-Crni Vrh Sombor Subotica Tupižnica Vršac

DIGITAL TELEVISION, RADIO PROGRAMS AND

Earnings on a monthly basis for the service of broadcasting TV programs for public media services RTS and RTV in the entire territory of the Republic of Serbia and other holders of licenses for broad casting TV programs in the entire territory of the Republic of Serbia in SD resolution in total for all distribution zones is 30,300,522 dinars, and for broadcasting in HD resolution amounts to 4,940,155 dinars. For the same broadcasting service, the annual earnings are 363,606,264 dinars for broadcasting in SD resolution, and 59,281,860 dinars for broadcasting in HD resolution.

Using method 2 and using prices based on the data from Table 2, the following results were obtained, presented tabular and graphically (Table 6 and Figure 5).

Table 6. The total price on a monthly basis for broadcasting TV programs in SD and HD resolution by distribution zone, for holders of licenses for broadcasting TV programs in regional and local areas

Distribution zones

SD resolution Price (dinars)

Avala 1.048.975,03 /

Besna Kobila 191.518,656 /

Cer – Maljen 317.920,96 /

HD resolution Price (dinars)

Crveni Čot 1.600.548,76 400.137,188

Deli Jovan 175.102,76 /

Jastrebac 1.202.189,95 /

Kikinda 134.610,256 84.131,408

Kopaonik 249.521,448 /

Tornik – Ovčar 819.699,832 /

Rudnik – Crni Vrh 1.092.477,12 /

Sombor 94.391,34 47.195,668

Subotica 201.094,59 100.547,294

Tupižnica 192.613,04 / Vršac 131.327,072 41.039,712

ANALYSIS OF THE BROADCASTING SERVICE OF DIGITAL TELEVISION, RADIO PROGRAMS AND DATA TRANSMISSION IN THE REPUBLIC OF SERBIA

2000000

1500000

1000000

500000

Figure 5. Graphical representation of the total price on a monthly basis for the service of broadcasting TV programs in SD and HD resolution with unconditional access by distribution zone, for holders of licenses for broadcasting TV programs in regional and local areas 0

Total monthly price for SD resolution Total monthly price for HD resolution

Avala Besna Kobila Cer-Maljen Crveni Čot Deli Jovan

Jastrebac Kikinda Kopaonik Tornik-Ovčar Rudnik-Crni Vrh

Sombor Subotica Tupižnica Vršac

Earnings on a monthly basis for the service of broadcasting TV programs for license holders in regional and local areas in total for all distribu tion zones in SD resolution is 7,451,990 dinars and in HD resolution it is 673,051 dinars. For the same broadcasting service in SD resolution for all distribution zones, the annual income is 89,423,880 dinars, and for broadcasting in HD resolution it is 8,076,612 dinars.

Using method 3 and prices accordingly, in Table 3, the total monthly price for broadcasting radio programs by distribution zone is given in Table 7.

Table 7. Total price on a monthly basis of the broadcasting service of radio programs in the DVB T2 network by all distribution zones

Service

Type of signal Price (dinars)

Commercial correction factor

Total monthly price (dinars)

Broadcasting of radio programs in the DVB T2 network Stereo audio signal 320.664 0,5 480.996

Using method 4 and prices accordingly, in Table 4, the total monthly price for broadcasting radio programs by distribution zone is given tabular and graphically (Table 8 and Figure 6).

ANALYSIS OF

SERVICE OF DIGITAL TELEVISION, RADIO PROGRAMS AND

TRANSMISSION IN

CEROVINA. J., MILOŠEVIĆ.

FINANCIAL ANALYSIS OF THE BROADCASTING

Table 8. The total monthly price for data transmission service by distribution zone in SD and HD resolution

Distribution zones

SD resolution Price (dinars)

HD resolution Price (dinars)

Avala 169.491,6 36.016,95

Besna Kobila 237.288,24 36.016,95

Cer – Maljen 237.288,24 36.016,95

Crveni Čot 305.084,88 36.016,95

Deli Jovan 288.135,72 36.016,95

Jastrebac 338.983,2 36.016,95

Kikinda 203.389,92 36.016,95

Kopaonik 322.034,04 36.016,95

Tornik – Ovčar 355.932,36 36.016,95

Rudnik – Crni Vrh 305.084,88 36.016,95

Sombor 220.339,08 36.016,95

Subotica 220.339,08 36.016,95

Tupižnica 254.237,4 36.016,95

Vršac 271.186,56 36.016,95

Figure 6. The total monthly price of the leased capacities in the corresponding data transmission service capacity range.

0

SD resolution

HD resolution

Avala Besna Kobila Cer-Maljen Crveni Čot Deli Jovan

Jastrebac Kikinda Kopaonik Tornik-Ovčar Rudnik-Crni Vrh

Sombor Subotica Tupižnica Vršac

SERVICE OF DIGITAL TELEVISION, RADIO PROGRAMS AND DATA TRANSMISSION IN THE REPUBLIC OF SERBIA

CEROVINA. J., MILOŠEVIĆ. I., SIMIĆ. M.

CONCLUSION

Based on the analysis, it can be concluded that the monthly earnings for broadcasting TV programs for public media services RTS and RTV in the entire territory of the Republic of Serbia and other holders of licenses for broadcasting TV programs in the entire territory of the Republic of Serbia in total for all distribution zones are 35.240.677 dinars in SD and HD resolution. For the same broadcasting service, the annual earnings are 422.888.124 dinars for broadcasting in SD and HD resolution. Earnings on a monthly basis for the service of broadcasting TV programs for license holders in regional and local areas in total for all distribution zones in SD and HD resolution amount to 8.125.041 dinars. For the same broadcast service in SD and HD resolution for all distribution zones, the annual income is 97.500.492 dinars. Earnings for broadcasting radio programs within the DVB-T2 network in total for all distribution zones on a monthly basis are 7.214.940 dinars, and at the annual level 86.579.280 dinars. Earnings on a monthly basis for the data transmission service amount to 4.269.069 dinars, and on the annual basis to 51.228.828 dinars. We conclude that the total annual income brought by the service of broadcasting digital television, digital radio programs within the DVB-T2 network and digital data transmission is 658.196.724 dinars. From 2015 to 2022, earnings for broadcasting TV programs, radio programs within the DVB T2 network and digital data transmission have amounted to 4.607.377.070 dinars, and in euro equivalent 38.394.808. Based on the results of the financial analysis and data on the invested financial resources in the amount of 37.5 million euros, we can conclude that the invested funds have paid off and that the earnings are certainly higher than predicted, given that the financial analysis does not include the earnings from the service of broadcasting TV programs in the third multiplex, nor the earnings from the service of broadcasting radio programs within the DAB+ network.

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Ariansyah, K. & Yuniarti, D. (2021). Understanding the adoption of digital terrestrial, cable-based, and satellitebased television to speed up the analogue switch-off in Indonesia. Telematics and Informatics, 62,101633. https://doi.org/10.1016/j.tele.2021.101633

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FINANCIAL ANALYSIS OF THE BROADCASTING SERVICE OF DIGITAL TELEVISION, RADIO PROGRAMS AND DATA TRANSMISSION IN THE REPUBLIC OF SERBIA

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CEROVINA. J., MILOŠEVIĆ. I., SIMIĆ. M.  FINANCIAL ANALYSIS OF THE BROADCASTING

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CEROVINA. J., MILOŠEVIĆ. I., SIMIĆ. M. 

ANALYSIS OF THE BROADCASTING SERVICE OF DIGITAL TELEVISION, RADIO PROGRAMS AND DATA TRANSMISSION IN THE REPUBLIC OF SERBIA

FINANSIJSKA ANALIZA SERVISA EMITOVANJA DIGITALNE TELEVIZIJE, RADIO PROGRAMA I PRENOSA PODATAKA U REPUBLICI SRBIJI

Rezime:

Digitalizacija radio i televizijskih programa, kao i drugih multimedi jalnih sadržaja, veoma je složen proces sa više aspekata i zahteva velika finansijska ulaganja u infrastrukturu sistema i svih pratećih elemenata. U ovom radu dat je sažet opis institucionalnih i regulativnih okvira u procesu digitalizacije u Republici Srbiji. Navedeni su bitni razlozi vezani za izbor kompresionog standarda i standarda za prenos televizijskih signala, kao i opis uloge JP Emisiona tehnika i veze u procesu digitali zacije. Cilj ovog rada je finansijska analiza zarade na godišnjem nivou za usluge emitovanja TV programa u prvom i drugom multipleksu, emitovanja radio programa u okviru DVB-T2 mreže i usluge prenosa podataka nakon procesa digitalizacije. Metod i podaci potrebni za izradu finansijske analize izvedeni su na osnovu cenovnika usluga objavljenog od strane JP Emisiona tehnika i veze objavljenog avgusta 2020. godine. Rezultati su prikazani tabelarno i grafički.

Ključne reči: Digitalizacija, Digitalna televizija, Digitalni prenos podataka, DVB T2, Finansijska analiza.

FINANCIAL ANALYSIS OF THE BROADCASTING

SERVICE OF DIGITAL TELEVISION, RADIO PROGRAMS AND DATA TRANSMISSION IN THE REPUBLIC OF SERBIA

EJAE 2022, 19(2): 114 - 128

ISSN 2406-2588

UDK: 005.961:640.4(497.11) 316.644:640.4-057.16 331.101.25

DOI: 10.5937/EJAE19-39093

Original paper/Originalni naučni rad

WORK-LIFE BALANCE AND WORK-RELATED ATTITUDES OF EMPLOYEES: CASE STUDY IN SERBIAN HOTEL INDUSTRY

Jasmina Ognjanović*, Aleksandra Mitrović

University of Kragujevac, Faculty of Hotel Management and Tourism in Vrnjačka Banja, Vrnjačka Banja, Serbia

Abstract:

The hotel industry is recognized in the labor market as insufficiently attractive for potential employees. Accordingly, hotel management must pay special attention to ensuring a balance between business and family obligations of employees, to create more favorable working conditions. Respecting the family obligations of employees results in positive work-related attitudes toward employees. This paper aims to investigate the nature of the connection between work-life balance and the work-related attitudes of employees. The research was conducted on a sample of 90 employees in three-, four- and five-star hotels in Serbia. The testing of the set research hypotheses was carried out using a non-parametric test for comparing groups, correlation analysis, and regression analysis. Using a non-parametric test to compare groups, a difference in the level of experience of work-life balance between male and female respondents was determined. It was also noted that men rated work-life balance worse than women. The results indicate a strong, positive, and statistically significant correlation between worklife balance and work-related attitudes of employees. Work-life balance contributes positively to the work-related attitudes of employees.

INTRODUCTION

Article info:

Received: Jul 11, 2022

Correction: August 06, 2022

Accepted: September 06, 2022

Keywords: Work-life balance, Employees’ attitudes, Human resource management, Hotel.

The hotel industry is a labor-intensive industry (Ognjanović, 2017) that bases business activities on the knowledge, skills, and abilities of employees to effectively use existing tangible and intangible assets in order to ensure complete guest satisfaction and experience. The hotel industry failed to build the image of an attractive employer in the labor market (Ognjanović, 2021). The characteristics such as hotel operation 24/7, the impact of shift work on the health of employees, insufficient job security, and weaker career development opportunities (Hewagama, 2015), did not contribute to making this industry attractive to potential employees. On the other hand, the accelerated development of the hotel industry led to an increase in the demand for a highly qualified workforce (Kong, Cheung, & Song, 2012).

*E-mail: jasmina.lukic@kg.ac.rs

This deficiency imposes a very complex task on human resources managers in order to succeed in creating more favorable working conditions. In the field of human resource management (HRM), there was an opinion that if hotel management wants to retain employees, it must improve morale, commitment, and satisfaction, and reduce stress and work-related problems of employees (Wilkinson, 2008). This leads to the conclusion that hotel management must think about these challenges and limitations, where they must prioritize activities that will ensure sustainable development (Pasamar, & Cabrera, 2013; Mitrović, Knežević, & Milašinović, 2022). One of the HRM activities, which is becoming particularly popular in modern business conditions, is work-life balance.

Work-life balance has emerged as an interesting topic in the last two decades as a result of significant work intensification, caused by economic uncertainty, organizational restructuring, and increased business competition (Hughes, & Bozionelos, 2007). An individual's perception of work-life balance is conditioned by job satisfaction, family satisfaction, life satisfaction, family functioning, and organi zational commitment (Helmle, Botero, & Seibold, 2014). Empirical findings suggest that employees who feel good and do not experience excessive stress, both at work and at home, are more likely to be satisfied with their jobs (Hughes, & Bozionelos, 2007; Helmle et al., 2014). Analyzing the possibility of harmonizing business and family obligations of employees and taking the necessary steps to improve the situation is directly related to organizational success (Hughes & Bozionelos, 2007). Appreciation and understanding of work-life balance are especially important for the hotel industry, whose entire offer is largely based on the knowledge and skills of employees. By developing work-life balance, hotel management can improve the attractiveness of the hotel industry in the labor market and influence employee satisfaction.

What is recognized in the literature as a problem, when it comes to HRM in hotels, is that employers ignore the issue of work-life balance (Wilkinson, 2008). On the other hand, employees in the hotel industry suffer from a lack of work-life balance (Kaya & Karatepe, 2020). The situation is further complicated by the fact that with the lack of professionals, the pressures on existing employees are increasing and additional engagement is required from them (Wilkinson, 2008). Considering the unfavorable characteristics of the hotel industry on the labor market, the issue of work-life balance should be specially addressed by human resources managers.

Several research gaps have been identified in the literature. Firstly, owners and managers do not have enough knowledge about the factors with the help of which work-life balance can be managed (Helmle et al., 2014). For this reason, the study analyzes the impact of work-life balance on the workrelated attitudes of employees. The existing literature on work-life balance indicates that the impact of flexible working and family-friendly policies is not clearly understood and that differences at the level of different industries and different levels of the organization have been observed but not empirically investigated: it is simply assumed that there is a positive correlation between strong work-life balance programs and employee loyalty to the company (Moore, 2007). This research gap is attempted to be overcome by conducting research in the hotel industry and seeks to examine the importance of work-life balance among hotel employees. Secondly, a large part of researchers in the field of worklife balance have limited their research in the Anglo-Saxon context (Pasamar, & Cabrera, 2013). The concept of work-life balance is not only a western phenomenon, but due to globalization, it has also spread to the east (Rehman, & Roomi, 2012), so research needs to be conducted in this context as well. Thirdly, it has been noted in the literature that work-life balance has been studied from the aspect of the role of women in the family (Burnett, Gatrell, Cooper, & Sparrow, 2010; Rehman, & Roomi, 2012). Work-life balance is an issue of greatest concern to both genders (Hughes, & Bozionelos, 2007).

OGNJANOVIĆ. J., MITROVIĆ. A.  WORK-LIFE BALANCE AND WORK-RELATED ATTITUDES OF EMPLOYEES: CASE STUDY IN SERBIAN

For these purposes, the research was conducted in an emerging economy (Serbia) and includes both male and female respondents.

Most research in this area has focused on the consequences that work-life balance has on the indi vidual and the organization (Helmle et al., 2014). Previous studies analyzed the relationship between work-life balance and employee performance (Soomro, Breitenecker, & Shah, 2018), work-life balance, and job performance (Talukder, 2022). However, the relationship between work-life balance and employee attitude has not been analyzed in the literature. Also, previous research did not focus on the hotel industry, which is particularly interesting since it is not recognized as attractive in the labor market. The commitment of the hotel management to create working conditions that will contribute to the understanding of family obligations also affects the shaping of the behavior and attitudes of employees. Hotel management must ‘focus on the wishes and needs of employees in such a way that employees perceive that the outputs are greater than the inputs and they, therefore, feel obliged to respond positively to the organization with an appropriate attitude, and its resulting impact on organizational performance’ (Tortosa Edo, Llorens-Monzonís, Moliner-Tena, & Sánchez García, 2015, p.488). By observing and modeling employee behavior and undertaking activities to improve employee attitudes, it is possible to influence employee results such as job satisfaction, organizational commitment, and service performance (Li, & Huang, 2017). Therefore, the paper aims to investigate the nature of the relationship between work-life balance and the work-related attitudes of employees.

In addition to the introduction and conclusion, the paper consists of three parts. The second part provides an overview of the most significant aspects of work-life balance, as well as an overview of previous research that dealt with the topic of work-life balance, with a special analysis of the connection with the attitudes of employees. The third part includes a description of the used research instrument as well as a description of the observed sample. The fourth part presents the results of the research with a discussion of the obtained results. In the conclusion, the results of the research are summarized, the practical implications and limitations of the research are presented, and suggestions for the implemen tation of future research are given.

LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT

Work-life balance in human resources management

The first studies on work-life balance appeared in the 1970s as a ‘women's issue’, and then in the 1980s, studies directed towards this topic began to focus on the development of effective employment/ retention policies (Moore, 2007). The motivation for studying work-life balance stems from the need to promote flexible work for employees, with the basic goal of making the division of labor in the family and caring for children "gender-neutral" (Burnett et al., 2010). A good work-life balance implies that employees use the possibilities of flexible working hours programs to balance their work and other obligations outside of work (Moore, 2007). Work and family are seen as two key sources of people's stress because they require most of a person's time, attention, and energy during the day (Young, McLeod, & Carpenter, 2022). The purpose of establishing a work-life balance is for employees to find the rhythm that will enable them to combine work with their non-work responsibilities, activities, and aspirations (Hughes, & Bozionelos, 2007). This will contribute to the improvement of the employee's quality of life as well as organizational efficiency (Pasamar, & Cabrera, 2013).

OGNJANOVIĆ. J., MITROVIĆ. A.  WORK-LIFE BALANCE AND WORK-RELATED ATTITUDES OF EMPLOYEES: CASE STUDY IN SERBIAN HOTEL INDUSTRY

Work-life balance is defined in a variety of ways. It is the level of satisfaction that individuals feel when they can function both at home and work, with a minimal conflict between both roles (Helmle et al., 2014). Work-life balance can also be defined as a measure in which the efficiency and satisfaction of an individual in work and family roles are compatible with the priorities of the individual's life role at a given moment (Helmle et al., 2014). Moore (2007:386) defines a good work-life balance "as a situation in which workers feel that they are capable of balancing their work and non-work commitments, and, for the most part, do so". The primary theoretical explanation for the unique experiences of employees regarding work-life balance can be linked to social role theory (Thrasher, Wynne, Baltes, & Bramble, 2022). According to this theory, all people have different social roles at any given time, with each role defined as a set of specific expectations that drive behavior and cognition within those roles (Thrasher et al., 2022). Young et al. (2022) observe work-life balance from a psychological aspect and connect the analysis of work-life balance with occupational stress theory.

The potential benefits of increasing managers' awareness of the need to develop work-life balance are of particular importance, given that previous research has shown that family-to-work conflict and work-to-family conflict affect the emotional well-being of owners and employees, their job, and firm satisfaction performance (Helmle et al., 2014). The authors (Stoilova, Ilieva-Trichkova, & Bieri, 2020) believe that how employees will react to business and family obligations and establish a balance between them depends on the characteristics of human capital. Most of the work performed depends on the action of knowledge, ability, and skills of employees to use tangible and intangible assets. The motivation of employees to perform their work tasks in the best way is the result of the psychological outcome of conflict/stress that occurs as a result of (in)balance between life and work (Rehman, & Roomi, 2012). For this reason, HR managers must monitor and analyze factors that affect the balance between work and family responsibilities. Research shows that employees who are under stress and who have not established a work-life balance are more likely to make mistakes and take sick leave (Wilkinson, 2008). The development of work-life balance also affects the reduction of company costs. A reduced employee turnover rate results in financial savings and can be a motivation for companies to invest in work-life balance (Wilkinson, 2008).

Certain factors hindered the development of the quality of work-life balance. Pasamar and Cabrera (2013) believe that decision-makers often do not pay enough attention to the dynamics of the environment in which they operate. That is why researchers on work-life balance must pay more attention to the institutional environment. Barriers to the development of work-life balance in companies are also business cultures that promote and reward long-term work and high organizational commitment, to the detriment of other company obligations (Wilkinson, 2008). The development of work-life balance can also be hindered by managers who do not have a developed awareness that understanding and respecting the needs of employees (both business and family) can positively affect their behavior and actions in the company.

Work-life balance has been considered rather narrowly because it was originally considered that this issue refers to individuals, especially women, who are employed in companies and have family responsibilities (Hughes, & Bozionelos, 2007). Rehman and Roomi (2012) conduct research among men and women and conclude that strategic planning, organizing, and delegating may be the most efficient strategies used by women to ensure work-life balance. Stoilova et al. (2020) put the level of education among women and men as the focus of work-life balance research. They concluded that higher education increases the likelihood of considering work-life balance as an important factor in job choice for men, while lower education reduces the chances of considering this factor for women.

MITROVIĆ.

BALANCE AND WORK-RELATED ATTITUDES OF EMPLOYEES: CASE STUDY IN SERBIAN HOTEL INDUSTRY

Helmle et al. (2014) concluded that spousal support did not influence individual perceptions of worklife balance. It is assumed that work-life balance can be a factor valued differently by men and women in the hotel industry precisely because of the working conditions. This primarily refers to the impact of shifts on family obligations as well as the nature of the hotel's seasonal business. These characteristics could be particularly unfavorable for women. According to the above, it would be useful to investigate the assessment of work-life balance among employed men and women in the hotel industry.

Hypothesis 1: There is a statistically significant difference in the level of perceived work-life balance between men and women in hotels

Work-life balance and work-related attitudes of employees

Employee attitudes are defined as "the extent to which members of a work organization can satisfy important individual needs through their experiences in the organization" (Karia, & Abu Hassan Asaari, 2019:281). The attitudes can also be seen as the result of the reaction of individuals to the objective and experienced characteristics of the work organization (Karia, & Abu Hassan Asaari, 2019). It is considered that employee attitudes precede the behavior of employees and have several psychological functions for employees: they help to form knowledge, define strategies for solving problems, to organize memory (Talukder, Vickers, & Khan, 2018). It can be concluded that the contribution to the development of work-life balance is reflected through the provision of the well-being of employees (both physical and mental), which has an impact on the results of the organization (Helmle et al., 2014).

Managerial support helps employees to foster positive attitudes towards their organization, which in turn affects employee engagement (Kaur, & Randhawa, 2021). Talukder et al. also agree with this conclusion (2018), looking at managers' attitudes and behavior as drivers of employees' ability to maintain work-life balance. For this reason, Moore (2007) indicates the need to analyze the development of work-life balance among managers. The same author, based on the conducted research, concludes that managers are better able to maintain work-life balance compared to operational workers and focus more on achieving status, while operational workers are more focused on achieving personal satisfaction (Moore, 2007). The relationship between managers and employees regarding the provision of work-life balance should be monitored and analyzed in particular, since the results of the research by the authors Hughes and Bozionelos (2007) show that if the work-life balance is not applied in the right way, it can be a source of negative attitudes of employees towards company management.

A certain number of authors (Soomro et al., 2018; Jain, Le Sante, Viswesvaran, & Belwal, 2021) observe employee attitudes through job satisfaction. Talukder et al. (2018) state that job satisfaction is one of the most frequently studied aspects in the field of work-life balance. Hughes and Bozionelos (2007) conclude that work-life imbalance is not only a source of concern but also a major source of employee dissatisfaction.

Research shows that the development of an appropriate work-life balance policy contributes to ensuring employee loyalty to the company and positive attitudes towards work (Moore, 2007). By undertaking activities that will improve employees’ attitudes, it is possible to ensure an influence on the behavior of employees (Talukder et al., 2018), and thus on the way to achieving the company's goals. Employee imbalance in any form, when work spills over into family life or when family life spills over into work, is a potential pattern of stress, dissatisfaction, and unconstructive work attitudes of employees (Soomro et al., 2018) because organizational work-family resources are usually applied in response to the wishes and values of employees.

EJAE

OGNJANOVIĆ. J., MITROVIĆ. A.  WORK-LIFE BALANCE AND WORK-RELATED ATTITUDES OF EMPLOYEES: CASE STUDY IN SERBIAN HOTEL INDUSTRY

These resources are expected to help with stress resistance, resulting in positive effects for employees. Based on the stated position, the authors Talukder et al. (2018) and Talukder (2022) indicates the connection between organizational work-family resources and employee attitudes. That is why the recommendation of the authors Soomro et al. (2018) is to determine the intensity of the conflict between life and business obligations so that it does not become a permanent stressor that leads to poorer performance and irresponsible work attitudes. Young et al. (2022) conclude that work-life balance is related to the level of employees’ occupational commitment. Considering the characteristics of the hotel industry (labor-intensive activity, insufficiently good working conditions, high turnover of employees) as well as the crucial role of work-life balance in the well-being of employees (Karkoulian, Srour & Sinan, 2016), there is a need to examine the impact of work-life balance on work-related attitudes of employees in hotels. Based on what has been defined, the following hypotheses have been proposed:

Hypothesis 2: There is a positive, strong, and statistically significant correlation between the work-life balance and work-related attitudes of employees.

Hypothesis 3: Work-life balance contributes positively to the work-related attitudes of employees

MATERIAL AND METHODS

Research instrument and sample description

For the research, employees in three-, four- and five-star hotels in Serbia were surveyed. The information about the number of hotels, names, and the category was taken from the website of the Ministry of Trade, Tourism, and Telecommunications of the Republic of Serbia. The information on email addresses was taken from the hotels’ websites. The employee survey was conducted in October 2020. The questionnaire was sent to 273 addresses. After an online survey, a telephone survey, and an oral survey, the number of respondents was reduced to 90 employees, giving a response rate of 33%.

The survey was conducted using a questionnaire that contains three parts. The first part includes socio-demographic information about the respondents and employees of the hotel. The second part refers to the items based on which the development of work-life balance is analyzed. This part includes three items that are defined based on the research conducted in the papers of Tanwar and Prasad (2016) and Zhu, Wang, Yu, Hu, Wen, and Liu (2014). The third part of the questionnaire refers to the attitudes of employees. It includes four items that are defined based on the research conducted in the papers of Engstrom, Westnes, and Westnes (2003) and Nemec Rudež and Mihalič (2007).

BALANCE AND WORK-RELATED ATTITUDES OF EMPLOYEES:

Table

Sample description

Socio-demographic characteristics Absolute number

Hotel category

4-stars

5-stars

Gender Men

Women

Vocational education Secondary school

% representation in the sample

16% High school

University

32% Master/Magister

Number of years working in the hotel industry up to 5 years

from 6 to 10 years

32%

31% more than 10 years

Source:

Table 1 shows the sample according to the observed socio-demographic characteristics. In the observed sample, the largest number of surveyed employees work in a 3-star hotel (60%). Women respondents are more dominant in the sample (64%), compared to the participation of the male respondents (36%). Looking at the vocational education of the respondents, the highest share is held by the respondents with high school (36%) and a university degree (32%). By observing the characteristic "number of years of work in the hotel industry", almost equal participation of employees with work experience of "up to 5 years" was recorded; "from 6 to 10 years" and "more than 10 years".

Methods

To process the collected data, the statistical program SPSS, Statistical Package for Social Sciences, was used. To determine statistical significance, a confidence interval of ά=0.05 was used. First, the sample was described based on the results of descriptive statistics. Then, a reliability analysis was carried out to determine the reliability of the used statements. The testing of the set of research hypotheses was carried out using a non-parametric test for comparing groups (Hypothesis 1), correlation analysis (Hypothesis 2), and regression analysis (Hypothesis 3).

OGNJANOVIĆ. J., MITROVIĆ. A.

BALANCE AND WORK-RELATED ATTITUDES OF EMPLOYEES: CASE STUDY IN SERBIAN HOTEL INDUSTRY

RESEARCH RESULTS AND DISCUSSIONS

Descriptive statistics, normality of sample distribution and reliability analysis

The mean value of the independent variable work-life balance is Mean = 4.51, while the mean value of the dependent variable work-related attitudes of employees is Mean = 4.73. The higher value of the standard deviation is recorded by the work-life balance variable (SD = 0.69). Observed by gender, men employed in hotels rate work-life balance worse than women. The mean for men is 4.24, while for women Mean is 4.66. The obtained skewness values for the observed two variables are negative, which means that the results are distributed in such a way that they are closer to higher values. Most of the kurtosis results are positive, indicating that the distribution is more peaked than normal. The results of descriptive statistics and correlation analysis are shown in Table 4.

The normality of the sample distribution was not proven. To check the normality of the distribution, the Kolmogorov-Smirnov test was used, since the sample size is greater than 50 units. The value of statistical significance for the observed variables is p = 0.000, so the empirical distribution cannot be approximated as normal.

The reliability and consistency of the items are measured based on the value of Cronbach's alpha coefficient. The value of this coefficient above 0.7 indicates high reliability and consistency of the used items (Nunnally, 1978). Cronbach's alpha coefficient for the entire model is 0.776, which means that the reliability of the observed items is at an acceptable level.

Non-parametric test for comparison of groups

To test the difference in the level of experience of work-life balance between the male and female hotel employees, a non-parametric test is used to compare groups - the Mann-Whitney U test. The non-parametric test was used since the normality of the sample distribution has not been proven. The Mann-Whitney U test is applied to test the difference between two independent groups on a continuous scale (Pallant, 2017). The test results are shown in Table 2, while the Ranks results are shown in Table 3.

Table 2. Mann-Whitney U test results

Source: Author’s calculation

The results shown in Table 2 show that Hypothesis 1 is supported, which means that there is a statistically significant difference in the level of experienced work-life balance between the men and women employed in the hotels (p = 0.015). Based on the Mean Rank values, shown in Table 3, it can be concluded that work-life balance has a higher value among women (Mean Rank = 50.09) than among

BALANCE AND WORK-RELATED ATTITUDES OF EMPLOYEES: CASE STUDY IN SERBIAN HOTEL INDUSTRY

men (Mean Rank = 37.17). Mean values of work-life balance were calculated, especially for women and especially for men. The mean work-life balance for women is 4.66, while the Mean work-life balance for men is 4.24.

Table 3. Ranks

Sex N Mean Rank Sum of Ranks Men 32

Women 58 50.09 2905.50

Source: Author’s calculation

Correlation analysis

The direction and strength of the relationship between work-life balance and work-related attitudes of employees are examined by correlation analysis. Correlation analysis is carried out using Spearman's rho coefficient, considering that the normality of the distribution has not been proven. If the correlation coefficient ranges from 0 to 0.29 (or from 0 to -0.29), it is a weak correlation between the variables; if it ranges from 0.30 to 0.49 (or from -0.30 to -0.49), it is a medium correlation, and if this coefficient is greater than 0.50 (or -0.50), there is a strong correlation between the variables (Pallant, 2017).

Table 4. Results of descriptive statistics and correlation analysis

Variables Mean Standard deviation Skewness Kurtosis Work-life balance Attitudes of employeeStatis. St. err Statis. St. err

Work-life balance 4.51 0.69 -2.07 0.25 6.66 0.50 1

Attitudes of employee 4.73 0.47 -1.77 0.25 2.72 0.50 0.514** 1

Source: Author’s calculation

Based on the results of the correlation analysis, shown in Table 4, it can be concluded that Hypothesis 2 is supported, that is, there is a positive, strong, and statistically significant correlation between worklife balance and work-related attitudes of employees. The Spearman's rho value ( = 0.514; p = 0.000) indicates that an increase in work-life balance by 1 unit leads to an increase in work-related attitudes of employees by 0.514 units and vice versa.

STUDY IN SERBIAN HOTEL INDUSTRY

Regression analysis

Analysis of the impact of work-life balance on the work-related attitudes of employees is performed using simple regression analysis. The application of this analysis implies the fulfillment of certain assumptions: autocorrelations and multicollinearity. Autocorrelation is observed based on the value of the Durbin-Watson statistic, which should not be greater than 4. Multicollinearity indicates a high degree of correlation between variables. It is measured based on the value of the VIF coefficient, which should not be greater than 5, and the value of Tolerance, which should be greater than 0.10 (Pallant, 2017). The assumptions of the regression analysis for the observed model are fulfilled. The results of the regression analysis are shown in Table 5.

Table 5. Results of regression analysis

Variables β t Sig. Work-life balance 0.434

Source: Author’s calculation

Dependent variable: Work-related attitudes of employees Significant: ** p ≤ 0.01; * p ≤ 0.05 R2 =0.189 F =20.47 DW = 1.48 VIF = 1 p = 0.000

Based on the presented results of the regression analysis, it can be concluded that Hypothesis 3 is supported, that is, work-life balance positively contributes to the work-related attitudes of employees (p = 0.000). The value of the coefficient of determination R2 is 0.189, which means that 19% of the variability of work-related attitudes of employees is explained by the regression model, while the rest is influenced by other factors. The value of Adjusted R Square is 0.179, while the F statistic is 20.47. Based on the value of the β coefficient, it can be concluded that an increase in work-life balance by one standard deviation leads to an increase in work-related attitudes of employees by 0.434 standard deviation units.

Discussion of results

Having in mind the observed research gaps in the literature, the contribution of the paper is reflected in the following. First, the research was conducted in the hotel industry, which is recognized as laborintensive and where dominant resources are employed in the process of providing hotel services. That is why it is important to determine the factors that affect the attitude of employees, to improve their engagement and thus work results. As the work environment in the hospitality industry changes rapidly, managers need an effective tool to ensure employee attitude and employee satisfaction. (Borovčanin, Kilibarda, Milošević, & Knežević, 2020). One of those tools, as the research results show, is work-life balance. The importance of work-life balance should be especially analyzed and monitored by hotel managers, bearing in mind that it is characteristic of the hotel industry that employment relationships are significantly different compared to other industries (Manolopoulos, Peitzika, Mamakou & Myloni, 2022).

OGNJANOVIĆ.

MITROVIĆ.

BALANCE AND WORK-RELATED ATTITUDES OF EMPLOYEES:

Second, the research was conducted in an emerging country, thus providing a theoretical contribution to the literature since research on the work-life balance variable is being extended to the eastern context. In emerging countries, the position of employees is different compared to employees in developed countries, which further emphasizes the importance of activities/variables that can improve the attitude and satisfaction of employees. Third, the research deals with the analysis of work-life balance among employed men and women in the hotel industry. This complements the perceived lack of research and contributes to the analysis of employed men, not only women in the hotel industry.

The results of applying a non-parametric test for comparing groups show that there is a difference in the experience of work-life balance between the men and women in the hotel industry. The women rate work-life balance better, which indicates better management commitment to working conditions for women. The results are consistent with the results of research (Hughes, & Bozionelos, 2007; Rehman, & Roomi, 2012; Stoilova et al., 2020), which claim that there is a difference in the experience of work-life between the genders. Also, the findings are contrary to the results reached by Rasmussen et al. (2020) that the satisfaction of work-life balance is similar for men and women. The results should also be considered in the context of the Covid crisis. Due to being overloaded with family responsibilities, it is assumed that managers understood the responsibilities of women, which was not the case for men. Results of the research lead us to the conclusion that it is necessary to analyze the work-life balance between men and women separately to identify certain areas that need normative changes as well as policy measures aimed at greater gender equality (Stoilova et al., 2020). Understanding the difference in valuing work-life balance between men and women can be a useful tool for managers to improve employee productivity, innovation, and employee attitudes (Gursoy, Chi, & Karadag, 2013).

The results of the research also show that the balance between private and business life determines the attitude of employees towards working in a hotel. Such results are consistent with the findings of the authors (Moore, 2007; Talukder et al., 2018; Talukder, 2022). Management must develop work-life balance for employees because otherwise, this factor can be a source of negative attitudes toward hotel management (Hughes, & Bozionelos, 2007). Regular monitoring and control of work-life balance ensure positive attitudes of employees, which are a necessary condition for improving their performance (Talukder et al., 2018). Management of work-related attitudes of employees and identification of factors that influence them leads to greater customer satisfaction (Im & Kim, 2022).

If employees want to maintain a good work-life balance, the best way to do this is not to encourage programs and policies but to encourage different attitudes towards the company, focusing more on social arrangements and less on promotion, hierarchy, and self-sacrificing work (Moore, 2007). Employees who failed to establish a work-life balance will not be sufficiently committed to the organization, which is associated with low effort and low performance of employees (Hughes, & Bozionelos, 2007).

EJAE

OGNJANOVIĆ. J., MITROVIĆ. A.  WORK-LIFE BALANCE AND WORK-RELATED ATTITUDES OF EMPLOYEES: CASE STUDY IN SERBIAN HOTEL INDUSTRY

CONCLUSIONS

The results of the research indicate that women perceive work-life balance in hotels better than men. Hotel management shows an understanding of the role of women in work and the family. On the other hand, men in hotels are less satisfied with the established balance between business and family obligations. The results also indicate that work-life balance contributes positively to the work-related attitudes of employees. A positive correlation between these variables has also been confirmed. The hotel industry is characterized by unfavorable working conditions for employees. These conditions can be improved by establishing a balance between life and work, which will also change the attitude of employees towards working conditions in the hotel. By developing the work-life balance variable, hotel management significantly contributes to employee motivation and satisfaction, which positively reflects the hotel's attractiveness in the labor market. It should be noted that the research was conducted during the pandemic crisis and that this could have influenced the results obtained in this way.

Practical implications. The results of the research contribute to the existing literature by expanding the understanding of the importance of work-life balance for managers and hotel employees in the field of human resource management. Hotel managers must take appropriate measures in their business plans to include the time, resources, and activities that they will set aside for the family obligations of employees. Further, the managers can conduct an annual survey of employees to evaluate the activities of the management in the matter of establishing a balance between life and work and possibly give certain suggestions on how to improve these activities. In the survey process, managers must pay special attention to men and their attitudes regarding work-life balance, considering that men rated this business factor more poorly. By respecting family obligations, the management shows that it cares about its employees, which contributes to the commitment of the employees and their positive attitude towards the hotel. Such a positive attitude of employees spreads among potential guests of the hotel, competitors, potential employees, and business associates of the hotel. All this creates a positive image of the hotel, not only in the labor market, but also in the goods market, but also affects the experience of the hotel service among guests.

Research limitations. The first limitation refers to the comprehensiveness (width) of observation of the dependent and independent variables. It is assumed that the observation of variables through certain sub-variables would give more detailed results on aspects of work-life balance. Also, the dependent variable work-related attitudes of employees can be observed through certain sub-variables (e.g., job satisfaction and organizational commitment, see Jain et al., 2021). Another limitation is related to the sample size. Although the response rate is satisfactory (33%), when collecting data, it was observed that employees were not interested in participating in the survey. The third limitation concerns the structure of the sample. Based on the data shown in Table 1, it can be concluded that the participation of employees in 5-star hotels is low. These hotels are perceived as significant drivers of the hotel business, in terms of defined business culture and excellent organizational structure, so their greater participation would provide more valuable information for research and conclusions.

Future research could be based on the inclusion of a larger number of work-life balance sub-variables and the analysis of their impact on various aspects of employees' work. Researchers could try to quantify the value of work-life balance so that they could track the progress of this variable over time. Further, future research can be based on a comparison of the development of the work-life balance variable between hotels of different categories.

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BALANCE AND WORK-RELATED ATTITUDES OF EMPLOYEES:

STUDY IN SERBIAN HOTEL INDUSTRY

BALANS IZMEĐU ŽIVOTA I POSLA I STAVOVI ZAPOSLENIH PREMA POSLU: STUDIJA SLUČAJA U HOTELSKOJ INDUSTRIJI SRBIJE

Rezime:

Hotelska industrija prepoznata je na tržištu rada kao nedovoljno atraktivna za potencijalne zaposlene. Iz tih razloga, menadžment hotela mora posebnu pažnju posvetiti obezbeđivanju ravnoteže između poslovnih i porodičnih obaveza zaposlenih, kako bi stvorili povoljnije uslove rada. Uvažavanjem porodičnih obaveza zaposlenih može se uticati na pozitivan stav zaposlenih prema poslu. Cilj rada je istražiti prirodu veze između balansa između života i posla i stavova zaposlenih prema poslu. Istraživanje je sprovedeno na uzorku od 90 zaposlenih u hotelima Srbije sa tri, četiri i pet zvezdica. Testiranje postavljenih istraživačkih hipoteza sprovedeno je primenom neparametarskog testa za poređenje grupa, korelacione analize i regresione analize. Primenom neparametarskog testa za poređenje grupa, utvrđena je razlika u nivou doživljaja balansa između života i posla među muškim i ženskim ispitanicima. Zabeleženo je i to da su muškarci lošije ocenili work-life balance u odnosu na žene. Rezultati ukazuju na jaku, pozitivnu i statistički značajnu korelaciju između balansa između života i posla i stavova zaposlenih. Balans između života i posla pozitivno doprinosi stavovima zaposlenih prema poslu.

Ključne reči: Balans između života i posla, Stavovi zaposlenih, Upravljanje ljudskim resursima, Hotel.

J., MITROVIĆ. A.  WORK-LIFE BALANCE AND WORK-RELATED ATTITUDES OF EMPLOYEES: CASE STUDY IN SERBIAN HOTEL INDUSTRY

EJAE 2022, 19(2): 129 - 141

ISSN 2406-2588

UDK: 3.077:004.738 007:35]:004.4.057.8 330. 341.1

DOI: 10.5937/EJAE19-39004

Original paper/Originalni naučni rad

USING OPEN GOVERNMENT DATA FOR ECONOMIC DEVELOPMENT

Nevena Petrović, Petar Milić*, Bojan Prlinčević

University of Pristina – Kosovska Mitrovica, Faculty of Technical Sciences, Kosovska Mitrovica, Serbia

Abstract: Publishing of open government data brings enormous benefits both to providers and consumers. On the one hand, governments increase their transparency and enable development of smarter and richer solutions, while on the other hand it enables various stakeholders to extract new information and create value from them. In this paper we investigate applicability of open government data for economic development and creation of value from published data. Different aspects of open government data consumption are explored, such as effectiveness, transparency and quality – and how they interrelate. They are of great importance for valorisation of open government data, and we will show that leveraging economic value of OGD must be accompanied by governments’ ability to make high quality OGD available.

INTRODUCTION

Article info:

Received: Jul 05 2022

Correction: August 19, 2022

Accepted: August 25, 2022

Keywords: E-government, Open data, Transparency, Quality, Economic development.

Governments around the world are launching the Open Government Data (OGD) portals to ensure that citizens, businesses and other stakeholders have the necessary prerequisite for exploitation of OGD in different areas. Opening government data is the first step towards creating an open and transparent government. Government data must be provided in a way to allow opportunities for users to go beyond passive recipients (Wirtz et al., 2019). OGD influence the development of a country as a whole, and at the same time accelerate innovation in a variety of sectors with trend of continuity. Constant evolution of OGD in terms of accessibility, reusability and application of innovative e-services implies building smarter and richer solutions (Milić et al., 2018). Moreover, they enable various stakeholders to extract new information and new knowledge.

Valorisation of OGD through datafication of everyday life contributes to profitability and creating of new socio-economic reality. Furthermore, this is a path to creating vital means by which labour market is producing and reproducing smart services and smart data (Burns & Welker, 2022).

*E-mail: petar.milic@pr.ac.rs

In this regard, political economy mainly focuses on material exchange of value and profit, while in the era of open government movement, this is pushed to the investment of energy to make government services “smarter”. Achievement of this goal is closely related to open data and innovations policies and their proper application for stimulation of economic growth. For example, stakeholders of OGD may rely on published data about reports, which can serve as valuable input for estimation of potential value of these efforts. Having investigated the OGD impact on producing new services and innovations, Mergel et al. (2018) claim that according to a Gartner study, open data policies could stimulate OGD based services up to a value of 96.5 million USD. As OGD in economic domain are mainly raw material, they serve for contemporary innovations, which leads to the growth of companies. Furthermore, OGD policies are extremely important as they ensure transparency of government information. Transparency then brings confidence and collaboration between government and citizens. Moreover, in the context of open government, transparency extends the accountability of public authorities as well as reuse to create new products and services. This mutual interaction develops an understanding of common and differing elements in the policies, identifying their variations at the same time, which consequently affects their impact.

This paper brings the discussion about utilization of OGD in economic domain, especially for the purposes of stimulation of economic development and how OGD can be exploited to create value from them. The goal of this paper is to contribute to a better understanding of how OGD facilitate public accountability for effectiveness and direct usefulness of these processes. In the following sections of the paper, we will explore the transparency and effectiveness aspect of OGD. In addition, utilisation of OGD for value creation and economic development shall be described. Final sections of the paper are dedicated to the discussion about quality aspects of provision of OGD and findings conclusions.

EFFECTIVENESS AND TRANSPARENCY OF OPEN GOVERNMENT DATA

OGD represent new currency in the digital world and is essential to the knowledge economy, serving as a valuable source for business and economy growth (Milić et al., 2015). According to a World Bank report on the impact of OGD on economic growth (The World Bank, 2014), a direct economic benefit of provision of data-rich services on the Internet can be identified with very low marginal costs of distribution, exemptation from upstream data charges and restrictions, as well as market availability. Different kinds of OGD such as weather data, economic statistics, geo data and road traffic information can lead to innovations in government services and the creation of new jobs and work opportunities.

Businesses are considered to be direct beneficiaries of effective usage of OGD due to the fact that they have means and interest in direct translation of available data into new commercial products, services and innovations. Governments own data such as official registers (either company or cadastres) together with geospatial data, providing core reference for the economy as a whole. Harrison and Sayogo (2014) reported that OGD may give an insight into the fiscally-related transparency, participation and accountability, along with information about national budgets as the focal policy domain. Therefore, publishing OGD provides an overview of the usage of public resources and government commitment to fulfilling stated performance objectives. Accountability data must take precedence over statistical data published on OGD portals in order to avoid risk of relegating the accountability objective in favor of economically valuable data disclosure (Lourenco, 2015).

The economic impact of releasing and (re)using OGD is just one of the arguments at the forefront of the debate about opening government data. For example, in order to enable effective public service provision, exposing data about malfunctioning service providers may lead to the better selection of service by citizens with regard to the services they consume. Similarly, OGD can ensure higher returns on public investment, and at the same time make it easier for policy makers to address difficult challenges, improve public policies and the efficiency and quality of public services (Bogdanović-Dinić et al., 2014). In this way, OGD can fuel the development of services for the benefit of society. Keeping this in mind, businesses themselves are moving towards the valorisation of intangible assets (Lemma, 2012).

OGD are the main prerequisite for building transparent and accountable open government oriented not only to the short-term considerations regarding information availability to all, but also to the longterm considerations regarding information usability by all (Milić et al., 2022). In this way, users will be able to create more value from OGD. Cuicinello et al. (2015) claim that government transparency is defined as a measure of citizen’s insight into business, processes and operations of the government. Most of the methodologies used for measuring transparency are oriented toward certain aspects of transparency, such as budget transparency. For example, this is one of the key aspects for ranking the countries according to the International Budget Partnership (IBP), which ranks countries based on a questionnaire with 125 questions related to the transparency of government budget (Ramkumar & deRenzio, 2009). A practical example on how this approach can be used is shown in Figure 1 – a screenshot of an application1 developed on the basis of OGD on the Serbian Open Data Portal. The Office for Information Technology and eGovernment of Serbia has developed an application for visual representation of data on city and municipal budgets.

Figure 1. Visualisation of data on city and municipal budgets on the Open Data Portal of Serbia

Data-driven government transparency is an important constituent of the institutional incentives in the form of the economic gain, accountability and trust in public administration. In order to achieve this goal, governments around the world have introduced soft measures such as financial aids in adoption and consumption of OGD (Ruijer et al., 2020). The same authors claim that creation of certain forms of data-driven transparency may be a deliberate strategy to generate strategic gains. Kingsley and Graham

MILIĆ.

(2017) found the correlation between data-driven government transparency and country-level foreign capital inflows. The effect of this correlation varies to a great extent based on foreign investors’ own private information and their flexibility in responding swiftly to change. Moreover, a research carried out by Hope et al. (2021) points in the same direction, confirming that there is a positive association between government transparency and operational efficiency of firms in emerging markets.

UTILIZATION OF OPEN GOVERNMENT DATA FOR ECONOMIC DEVELOPMENT

Availability of OGD is a first step toward its (re)use as a data product. Furthermore, data products provide digital development for traditional sectors such as transportation, health, manufacturing and retail (Attard et al., 2016). The same authors stress the importance of a continuing government commitment with an adequate financing amount allocated for identifying and opening datasets with a high value creation potential. Proper presentation of published OGD data to various stakeholders is a necessary prerequisite for their efficient consumption and value creation. Visual forms of repre sentation of OGD, such as charts, cubes and interactive tables contribute to easier understanding and interpretation of available information (Milić et al., 2018). An example of such data is given in Figure 2, where we can see various possibilities for data interpretation.

Figure 2. Availability of tabular data on Open Data Platform of the city of Edmonton.

Statistical data are most adequate for this purpose, since enhanced visualisation yields concrete and logical conclusions on the basis of the obtained indicators. Albino (2017) contributes to this by identifying a proof of concept with open data from a government agency that supports and finances investments in small and medium enterprises. The results of his research reveal a connection with developments of predictions about possible investment expenditures. Tinholt (2017) reports that according to a Finnish study, companies that reuse government released geographical data, either freely or at marginal costs, have a 15% higher annual growth rate compared to countries that charge such information with an objective of recovering costs.

By using participation and collaboration tools as key pillars of Web 2.0, value co-creation from OGD is enabled. Exploitation of these tools, non-technical end user contribution can be achieved and social and commercial value obtained (Khayyat & Bannister, 2017). Previously mentioned value co-creation can be understood as development of new service, product, or an idea and concept. The importance of semantic web (SW) technologies for value creation from OGD should be born in mind, too. SW technologies offer the possibility for collaborative work of government and citizens with the aim of increasing transparency and added value from OGD. For example, London Borough of Camden Food Premises database integrates with Google maps data in order to generate innovative service offer from government data (Ristoski & Paulheim, 2016). In addition, a recommendation system for finding relevant business partners developed by utilizing SW technologies was proposed by Zhang et al. (2017). The proposed system helps government agencies make recommendations to businesses about business partners, according to their requirements.

In order for users to be able to create and capture value from OGD and find ways to generate revenue, the existence of proper business models and business architectures must be ensured (Zeleti et al., 2016). Their aim is to tap into the potential value of OGD. As there are a variety of business models, it is up to each organization to either explicitly or implicitly choose a particular business model. Magalhaes et al. (2014) contribute to this topic by stressing the importance of value proposition as the cornerstone of the business model concept. Various business models utilizing OGD as the foundation for entrepre neurial innovations and start-ups, as well as specific OGD datasets for business decisions, are mostly based on reliable and accurate OGD (Safarov et al., 2017).

An interesting approach to creating value from utilized OGD is given by Gao and Janssen (2020). They point out that little attention is paid to the application of Artificial Intelligence (AI) both in academic research and practice. On the examples of Germany (AI parking), Singapore (Chatbot) and UK (Crime prevention), they showed how AI tools can be exploited with a view to saving time and money, or for economic benefit reflected in new investments and business improvements. They also point out the need for guidance and legal framework for proper exploitation of AI. Similarly to this research, Loukis et al. (2020) reveal how OGD, together with AI, can be used to predict the impact of recessionary economic crisis on companies. By applying AI, they found a relation between resilience/ vulnerability of a company to future economic crisis in accordance with a decrease in sales revenue, profitability, employment etc.

Nevertheless, according to Misuraca & van Noordt (2020) the application of AI systems has been criticised by both the government agencies who use it and citizens. They concluded that the underlying function of the AI is not transparent enough for its users (citizens) as they are not aware of the profiling mechanism. An exploratory study on applied AI systems reveals that clerks have questioned less than 1 in 100 decisions made by AI. Therefore, AI-led decision-making must be accompanied by legal, moral and ethical frameworks (Tan, 2020). Furthermore, incorporation and interpretation of user opinion, along with incorporation of dispersed knowledge in the process of creating necessary conditions for successful implementation of AI based on OGD is recommended. Janssen et al. (2020) claim that each AI system could be subject to a risk audit to anticipate and address the possible undesirable effects of the AI algorithms.

PETROVIĆ. N., MILIĆ. P., PRLINČEVIĆ. B.  USING OPEN GOVERNMENT DATA FOR ECONOMIC DEVELOPMENT

QUALITY OF OPEN GOVERNMENT DATA

Zeleti et al. (2016) argue that harnessing economic value of OGD along with leveraging associated business opportunities must be accompanied by government ability to sustain the availability of high quality OGD. As OGD are published on OGD platforms, better usability of OGD is in direct relation with usability of OGD platforms. A research by Nikiforova (2019) confirms this, showing that users will not find OGD platforms usable and fit to their needs if they are faced with any issues related to OGD. In this way, the trust in government institutions is irrevocably lost if low quality OGD are disclosed. Furthermore, most of OGD are consumed in innovative applications and adequate description of those data by using metadata on OGD platforms is necessary. In order to check readiness of government portals to provide quality OGD for their users, we conducted an analysis of several OGD portals where we checked definition of metadata fields for description of dataset necessary for their exploitation in innovative application. Results are shown in Table 1.

Table 1. Examined OGD portals.

platform portal

CKAN

number of datasets

AVG number of complete metadata fields per dataset

https://data.gov.rs/api/1/datasets 1822 64% 67% https://dados.gov.pt/api/1/datasets 4910 65% 39%

AVG number of machinereadable formats per dataset uData

https://data.public.lu/api/1/datasets/ 1600 63% 13% https://www.data.gouv.fr/api/1/datasets/ 41037 66% 40%

https://ckan.publishing.service.gov.uk/api/3/action/package_list 1822 64% 67%

https://open.canada.ca/data/api/3/action/package_list 31755 63% 29%

https://ckan.opendata.swiss/api/3/action/package_list 6963 74% 13%

https://datos.gob.mx/busca/api/3/action/package_list 9287 60% 14%

https://data.go.th/api/action/package_list 5898 74% 45%

https://data.gov.au/api/3/action/package_list 13376 72% 13%

https://www.govdata.de/ckan/api/3/action/package_list 49571 64% 5%

https://open.africa/api/3/action/package_list 6490 64% 45%

https://data.gov.ie/api/3/action/package_list 13373 75% 36%

https://data.humdata.org/api/3/action/package_list 31796 71% 39%

https://data.gov.ro/api/3/action/package_list 2691 69% 78%

https://data.gov.sk/api/3/action/package_list 2841 72% 60%

https://dados.gov.br/api/3/action/package_list 11029 75% 56%

https://data.buenosaires.gob.ar/api/3/action/package_list 423 78% 46%

http://opendata.hu/api/3/action/package_list 67 60% 21%

OPEN GOVERNMENT

ECONOMIC

DKAN

DKAN

Open DataSoft

number of datasets

AVG number of complete metadata fields per dataset

AVG number of machinereadable formats per dataset

https://data.gov.gh/api/3/action/package_list 315 100% 90%

https://data.city.kyoto.lg.jp/api/3/action/package_list 606 100% 78%

https://data.gov.jm/api/3/action/package_list 32 100% 83%

https://dadesobertes.diba.cat/api/3/action/package_list 76 90% 81%

https://opendata.by/api/3/action/package_list 229 100% 49% http://data.mmr.cz/api/3/action/package_list 43 73% 100%

https://dati.gov.it/opendata/api/3/action/package_list 52519 72% 82%

https://data.cambridgeshireinsight.org.uk/api/3/action/package_list 235 72% 65%

https://opendata.transport.nsw.gov.au/api/3/action/package_list 206 60% 5%

https://datosabiertos.rosario.gob.ar/api/3/action/package_list 245 100% 78%

https://data.nicva.org/api/3/action/package_list 164 100% 80%

https://opendata.bonn.de/api/3/action/package_list 327 100% 82% https://dati.comune.genova.it/api/3/action/package_list 138 100% 81% https://data.louisvilleky.gov/api/3/action/package_list 280 100% 53% https://data.gov.sa/Data/en/api/3/action/package_list 6442 100% 75%

https://data.edmonton.ca/api/catalog/v1 2519 100% 100% https://data.cityofnewyork.us/api/catalog/v1 3516 100% 100% https://www.dati.lombardia.it/api/catalog/v1 5432 100% 100% https://data.texas.gov/api/catalog/v1 1284 100% 100% https://data.honolulu.gov/api/catalog/v1 306 100% 100% https://cohesiondata.ec.europa.eu/api/catalog/v1 1139 100% 100% http://www.datos.gov.co/api/catalog/v1 28964 100% 100% https://healthdata.gov/api/catalog/v1 4308 100% 100% http://www.pivcide.pr/api/catalog/v1 70 100% 100% http://data.usaid.gov/api/catalog/v1 1510 100% 100% http://data.sfgov.org/api/catalog/v1 1087 100% 100% http://citydata.mesaaz.gov/api/catalog/v1 930 100% 100% http://data.cincinnati-oh.gov/api/catalog/v1 156 100% 100% http://data.novascotia.ca/api/catalog/v1 1113 100% 100% http://www.data.act.gov.au/api/catalog/v1 1127 100% 100%

https://public.opendatasoft.com/api/v2/catalog/datasets 623 50% 100% https://data.explore.star.fr/api/v2/catalog/datasets 42 57% 100% https://data.laregion.fr/api/v2/catalog/datasets 1711 46% 100%

PETROVIĆ. N., MILIĆ. P., PRLINČEVIĆ. B.  USING OPEN GOVERNMENT DATA FOR ECONOMIC DEVELOPMENT

Open DataSoft

https://www.data.corsica/api/v2/catalog/datasets 502 56% 100%

https://opendata.vancouver.ca/api/v2/catalog/datasets 177 36% 100%

https://ressources.data.sncf.com/api/v2/catalog/datasets 216 51% 100%

https://opendata.wuerzburg.de/api/v2/catalog/datasets 107 62% 100%

https://opendata.comune.bologna.it/api/v2/catalog/datasets 425 53% 100%

https://data.gouv.nc/api/v2/catalog/datasets 153 49% 100%

https://transparencia.sns.gov.pt/api/v2/catalog/datasets 148 58% 100%

https://data.education.gouv.fr/api/v2/catalog/datasets 92 50% 100%

https://opendata.bristol.gov.uk/api/v2/catalog/datasets 221 64% 100%

https://data.leicester.gov.uk/api/v2/catalog/datasets 181 66% 100%

https://data.montreuil.fr/api/v2/catalog/datasets 152 66% 100%

https://data.bs.ch/api/v2/catalog/datasets 152 54% 100%

Based on what is shown in Table 1, we can see that the level of complete metadata fields and machine-readable formats is not very high. In addition to this, it can be noticed that SOCRATA and OpenDataSoft OGD platforms have the best results for the level of average number of machine-readable formats per dataset. This is because these platforms mostly publish tabular data and offer the possibility to export them in various machine-readable formats such as CSV, XML, JSON, RDF etc. Furthermore, of all tested portals, only SOCRATA powered OGD portals have all complete metadata fields, i.e. all metadata defined. Some of the analysed OGD portals have less than 50% (or near that value) of the level of complete metadata fields per dataset on OGD portals, which may throttle the power of OGD. These portals should address this issue, as more detailed metadata for each dataset on portals contribute to the overall quality of OGD, which in turn improves application processing.

A continued commitment of governments to publishing high quality OGD contributes to their economic value. For instance, Mastodon C (a Big Data company) exploits OGD to identify unnecessary spending in prescription medicine.2 Similarly, Saez Martin et al. (2016) identify a positive association with a country’s economic capacities as a determinant factor for the quality of an OGD portal. On the basis of this, we can conclude that a relationship between OGD quality and economic development can be identified. More specifically, government institutions in this way can stimulate economic growth by creating an environment for the adequate consumption of its services. In so doing, governments complementary contribute to raising productivity, innovations, political progress etc., contributing at the same time to institutional development in the long-term perspective.

Citizens, as well as other stakeholders of OGD, are even more willing to use OGD when they are convinced that enhancement in individual performance and gaining economic value is available. Wirtz et al. (2018) suggest hiring external usability experts for reviewing OGD so as to ensure they can be utilized to generate value and benefit. According to a study by Tinholt (2017), a very low percentage of country-level OGD portals publish data that can be classified as comprehensive, i.e. data with high value gain, granular in nature and including extensive datasets. For example, thanks to the efforts made to ensure efficient management of OGD quality in Spain (Spanish Open Data Portal Annual Report, 2012), infomediary sector (companies that base their work on OGD) employs around 4,000 people and generates 330 – 550 million Euros annually, which is in direct relation with OGD reusability.

EJAE

MILIĆ.

Periodic assessments of these characteristics of OGD portals will yield new insights into them, with the aim of monitoring whether OGD still have the potential for generating value.

Collecting feedback from OGD re-users is a promising way to increase data quality. For example, an EU study (2020) revealed that in Denmark more feedback was obtained after making address data owned by government publicly available, as part of a crowdsourcing map service OpenStreetMap. The same study revealed that accurate and precise data in the area of public transport could help to save 27 million hours annually for all European travellers. In order to collect citizen opinion and feedback, as well as opinions of other stakeholders, the government of Singapore sponsored a “hackathon” to identify bottlenecks in usage and exploitation of OGD (Chui et al., 2020). Events like this raise the awareness of the necessity of having valuable OGD available. Zuiderwijk and Janssen (2013) identified the lack of the provision of feedback to data providers, or discussions with them after using OGD, and these mechanisms can be used to improve open data quality, data release processes and policies. Rudmark and Andersson (2021) showed that feedback loops in OGD ecosystems can serve as a source for improvements of OGD. Their research revealed that avoiding making OGD a new, separate publication targeting only external users proved to be a requisite quality measure in several studies of public transportation organization in Sweden.

A step forward in creating an adequate environment for publishing of quality OGD was made by Alexopulos et al. (2014). Their research presents the ENGAGE open data infrastructure, the aim of which is to serve as a pipeline for publishing OGD in accordance with novel Web 2.0 oriented func tionalities. Alawadhi et al. (2021) found that the existence of adequate strategies for publishing OGD would contribute to valuable deliverables. Consequently, this boosts income and productivity, affecting positively the economic cycle in the countries and encouraging the government sector to support the concept of open data and enact the necessary laws for that. The existence of strategy-led re-using of OGD is not just for pure financial profit – it could also be a part of the political or social agenda, or it could be used for hobby activities, academic exercises, or even pure altruistic motivation to advance public good (Sandoval-Almazán et al., 2021).

CONCLUSIONS

The research topic presented in this paper by using descriptive approach represents а brief summary of the extant literature about creating value from OGD. Our intention was to explore how OGD contributes to economic development and how technical aspect of provision of OGD must be consulted in order not to produce negative effects. Moreover, the importance of OGD reusing for value creation is emphasized, implying that the government datasets should be reused by a diverse set of stakeholders. Continuous development of provisioning and usage sides of OGD helps to achieve this aim. It has been shown that if adequate attention is paid to the policy-led production and consumption of OGD, then quality, transparency, accountability and economic benefits will be obtained.

More importantly, our aim was to explore three interrelated topics of open government initiatives – effectiveness, transparency and quality. Proper understanding of these three dimensions enables potential beneficiaries to take advantage of the overall impact of open government on both the organi zations and individuals. Keeping in mind that data created by governments are public good nowadays, it becomes clear why governments should make an effort to maximize the outcome out of the data.

PETROVIĆ. N., MILIĆ. P., PRLINČEVIĆ.

USING OPEN GOVERNMENT DATA FOR ECONOMIC

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MILIĆ.

KORIŠĆENJE OTVORENIH PODATAKA VLADE ZA EKONOMSKI RAZVOJ

Rezime:

Objavljivanje otvorenih podataka vlade donosi ogromnu korist i dobavljačima i potrošačima. S jedne strane, vlade povećavaju svoju transparentnost i omogućavaju razvoj pametnijih i bogatijih rešenja, dok sa druge strane omogućavaju različitim zainteresovanim stranama da izvlače nove informacije i stvaraju vrednost iz njih. U ovom radu istražujemo primenljivost podataka otvorene vlade za ekonomski razvoj i stvaranje vrednosti iz objavljenih podataka. Istražuju se različiti aspekti potrošnje podataka otvorene vlade, kao što su efikasnost, transparentnost i kvalitet – i kako su oni međusobno povezani. Oni su od velikog značaja za valorizaciju otvorenih vladinih podataka i pokazaćemo da korišćenje ekonomske vrednosti OPV mora biti praćeno sposobnošću vlada da učine dostupnim visokokvalitetne OPV.

Ključne reči: E-uprava, Otvoreni podaci, Transparentnost, Kvalitet, Ekonomski razvoj.

CIP -

33

The EUROPEAN Journal of Applied Economics / editor-in-chief Žaklina Spalević. - Vol. 12, No. 1 (2015)- . - Belgrade :

Singidunum University, 2015- (Belgrade : Caligraph). - 28 cm

Polugodišnje. - Je nastavak: Singidunum Journal of Applied Sciences = ISSN 2217-8090.

Drugo izdanje na drugom medijumu: The European Journal of Applied Economics (Online) = ISSN 2406-3215

ISSN 2406-2588 = The European Journal of Applied Economics

COBISS.SR-ID 214758924