17_jwe_1-2 UDC: 331.445:613(497.11) 159.944.4:331.1-055.2 JEL: L26 COBISS.SR-ID: 238908684 ORIGINAL SCIENTIFIC PAPER The Impact of Stress and Health on Quality of Working Life of Women in SMEs in Republic of Serbia Oliver Momčilović Sports Academy, Belgrade, Serbia Tijana Cvetić Faculty of Engineering University of Kragujevac, Kragujevac, Serbia Sladjana Vujičić1 Faculty of Business Economics and Entrepreneurshp, Belgrade, Serbia Aleksandar Antonijević Faculty of Engineering University of Kragujevac, Kragujevac, Serbia A B S T R A C T This paper gives analysis of impact of stress and health on quality of life of female workers in small and medium enterprises in Republic of Serbia. Research was conducted via questionnaire which held statementss regarding stress, health and quality of life, and was distributed to female workers in small and medium enterprises. Research results based on proposed model prove that stress and health have significant impact on overall quality of working life and that by altering each one of the variables mentioned or both at once level of quality of working life of female workers changes. Total of 198 respondents contributed to this research from all business positions. KEY WORDS: quality of working life, stress, health, system model 1 Corresponding author, e-mail: sladjanakonto@gmail.com Momčilović, O., et al. The Impact of Stress, JWE (2017, No. 1-2, 114-136) 115 Introduction In the second half of the twentieth century, the position of women was greatly improved which had direct impact on their quality of life. Women entrepreneurs not only contribute to economic growth and development but also help create new jobs, so that is the legitimate aspirations of women to have equal access to all available resources (Prljic, Vucekovic, Vujicic, 2015). Speaking in percentages, women entrepreneurship in Serbia is far less present than men entrepreneurship, so it is necessary to invest special efforts to create an ambience that will encourage women to be involved in entrepreneurship more intensively (Ravic, Nikitovic, 2016). Legal, structural social changes and raising awareness about the plight of women have contributed to it. One of the crucial facts was the fact that during the Second World War, and after its completion the labor market was in deficit with the male labor force, which was replaced by a woman, especially in the post-war period of economic development and expansion of production capacity. Negative phenomenon is the fact that their contribution to employment in the household has not changed and neither the requirements of the market in line with their family needs. Women who want to develop a career are directed to act as a "surrogate men," as Crompton and Le Feuvre established (1996). Judy Wajcman (1998) in study of older managers put forward the fact that 2/3 of women-skilled managers do not have children who live with them, while for men is the reverse case where 2/3 of the managers live with their children. Reproductive function and role in the family still stand as an obstacle to improving the quality of life of women and particularly women entrepreneurs (Galić, 2011). Satisfaction of stakeholders (interested parties) of a particular organization undoubtedly affects the competitiveness and image of the same. The term quality of life at work (Quality of Working Life - QWL) is given to the importance of the late 1960s as a way of understanding the effects of workplace health and general well-being. By the 1970s, concern of employers was aimed at improving working conditions. 1980s concept of quality of life at work also included other aspects of improving job satisfaction and productivity such as the reward system, employee commitment, and respect of the rights of workers. Radical changes in the business world such as globalization, information technology, global business competition and scarcity of natural resources have caused changes in respect of employees in the definition of "good" company. The trend of the past has been to define the image of the company based on its financial 116 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 114-136) indicators. Today, ethics, quality of life at work and job satisfaction of the workers themselves are the main prerequisites for the sustainability of business organizations. Quality of life at work is a broad concept that offers many different perceptions and therefore it is difficult to define. Many authors believe that the quality of life at work is based on a subjective feeling of employees in the organization while most psychologists agree that the term quality of life at work relates to the very well-being of employees (Indrani, Devi, 2011). Objective of this paper represents determination of level of Quality of working life of female workers in small and medium enterprises in Serbia. In this paper, there are several tasks of research, including: Determining respondents level of Quality of working life, a. defining the system model research, independent and dependent variables - perceptive characters based on the question groups from a set of electronic questionnaire, b. to analyze the partial relations of independent variables - system model elements observational characters: Stress and Health, and the dependent variable Quality of working life, from which are made following research hypothesis: H1 - Stress has significant influence on Quality of working life. H2 - Health has significant influence on Quality of working life. H3 - Stress and Health have significant influence on Quality of working life. Research was conducted via questionnaire which holds 11 statements. Respondents were female workers from small and medium enterprises. Purpose of this paper lays in understanding the connection between forementioned variables and their impact on women’s quality of working life. Quality of Working Life To ensure satisfaction and customer loyalty, organizations must consider the welfare of their employees and work environment, the impact of its operations and processes in the local community. The long-term effects that their products have during and after use must also be taken into account. The situation is very clear: the organization will succeed or it will simply disappear from the market (Gavric, Sormaz, Ilic, 2016). Standardized management systems such as ISO 9001, ISO 14001 and ISO 18001 have been developed to meet these requirements. Dealing with these Momčilović, O., et al. The Impact of Stress, JWE (2017, No. 1-2, 114-136) 117 three standards separately and ensure that they match with the existing strategy of the organization proved to be extremely challenging, which is why organizations have integrated management systems into its management portfolio. The need for integrated management systems was created as a solution for adding ISO 14001 or ISO 18001 standards to already existing ISO 9001 standard (Wilkinson, Dale, 1999). Quality of life at work does not only represent job satisfaction but it is one of its many aspects. It is generally accepted that different people have different views on what constitutes a high quality of life at work. The impact on the individual's working life is the outcome of many interactive factors, where the character of each individual may vary from group to group and from time to time. An important distinction can be drawn between the subjective and objective aspects of quality of life at work (quality of working life). The subjective aspect of quality of life at work stems from the workers who receive them directly by filling out their duties and indirect actions undertaken, as well as the subjective feeling of well- being and satisfaction indicators. The objective aspect of quality of life at work stems from the results, where its main features contribute to creating value both for the individual and for the economy as a whole (Greenan, Kalugina, Walkowiak, 2013). Quality of life at work is a multi-dimensional concept that scientists have defined in different ways. Some studies link the concept of QWL with the well-being of workers, living conditions at work, sufficient income, the distribution of profits, employee autonomy, social interactions, employee satisfaction, employee involvement, promotion and labor relations. Walton (1975) emphasizes eight dimensions of QWL's, 1) Adequate and fair compensation 2) Safe and healthy work conditions, 3) The permanent possibility of using human resource development, 4) An opportunity for further growth and security, 5) Social integration in the organization 6) The constitutionality of a working organization 7) Work and the total living space 8) The social significance of working life. Levine et al. (1984) suggests seven most important generators of OWL, 1) The degree to which superiors treat employees with respect, 2) Diversity in the daily work schedule, 3) Work challenge, 118 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 114-136) 4) The feeling that proven work opens future opportunities for advancement, 5) Self-respect, 6) Degree to which the life outside of work affects the life at work and the degree to which completed work contributes to society (Almarsh, 2015). According to various researchers, the quality of life at work represents the degree of employee satisfaction. Employee`s activities in the organization are regulated by specific standards and regulations, laid down in social and labor relations in the conditions of risk and uncertainty. Researching employment level of young people in Russia, as basic elements that form the quality of working life has revealed the specific role of the education system on delay of the release of potential labor force to the labor market. Due to the lack of experience of the overwhelming number of applicants of full-time university students, respondents' understanding and expectations concerning quality of their working life is a special method of questioning. Quality of life at work is formed as a result of the interaction of many different factors. This determines not only the need for systematization and classification of factors, but also factors critical analysis of the position of formation of quality of working life. Quality of working life components are fair wages, safe and healthy working conditions, job security and content of work (Safina et al., 2015). Measuring Quality of Working Life Measuring quality of life at work is not an easy task since the business environment is composed of a large number of components. There is no consensus on a definition of quality of life at work or a consensus on what makes a quality job (Kalleberg, Reskin, Hudson, 2000). As mainly, measurement of quality working life is based on the reports of employees which often encounter potential limitations of this type of measurement to be reflected in the bias of employees themselves (subjectivity). The advantages of this type of measurement are reflected in obtaining first-hand information and subjective feeling. There are subjective and objective indicators of the quality of life at work. The objective often includes salary, benefits, autonomy and control, opportunity for advancement and job security. Mostly the components of quality of life at work are subjective because they are based on the analysis Momčilović, O., et al. The Impact of Stress, JWE (2017, No. 1-2, 114-136) 119 of questionnaires. Subjectivity may vary due to the choice of the questionnaire and the way the data is collected. Objectivization lies in the collection of data of employees from the administration while the subjectivity lies in the data collected from the workers themselves. There are two approaches to measuring the quality of working life: 1. First approach measures the quality of working life through various specific dimensions of work such as wages, internal awards, advancement opportunities and security and then all these components combine to give a general assessment of the quality of working life. 2. The second approach is based on the direct inquiry to employees to assess their job satisfaction. The best example is to question employees about their level of job satisfaction. This approach does not measure all relevant characteristics but already assumes that employees are able to self-rate their general satisfaction. The disadvantage of this approach is the lack of information on the evaluation of various dimensions of the work and environment (Dahl, Nesheim, Olsen, 2009). Many authors have measured the quality of life at work using a variety of models, some of them are: Model proposed by Dupius (1989), QLSI (Quality of Life Systematic Inventory), which improves the perception of quality of life and its evaluation. Quality of life at work as an element of the quality of life can also be measured with the help of this model, which was labeled QWLSI (Quality of Working life Systematic Inventory) (Martel, Dupuis, 2006). The second, qualitative study was conducted among the severely mentally ill persons in social enterprises through two interviews. Data collected in this way were analyzed by Colaizzo`s method. The results show that the quality of life and safety of people represents a sense of belonging to the company (Lanctôt, Durand, Corbière, 2011). H. Narehan performed the testing of connectivity of the quality of life at work with the quality of life in multinational companies in Malaysia. The results from 179 respondents indicate a significant impact on the quality working life to the quality of life and the authors propose to multinational companies planning programs in order to increase the quality of working life (Narehan et al., 2014). Group of authors from Iran indicates a positive link between the quality of life at work and career advancement among Iranian academics. The 120 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 114-136) results of their study suggest where the possibility of increasing the quality of life of academics at universities had a high impact on the education system and community development in the country (Parsa et al., 2014). Gayathiri, Ramakrishnan (2013) explore the concept and variables of measuring the quality of life at work and connection between employed medical staff satisfaction with their performance. The main idea of this paper is to point out that with increasing the quality of life at work job satisfaction increases which improves the performance of an organization. In today's business environment, organizations must be flexible and must implement strategies to improve the quality of life at work of employees in order to meet the organization's objectives and the needs of employees. Quality of life at work has caused great interest and importance to all countries. Quality of life at work is related to the level of happiness or satisfaction of a person in their workplace. For those who enjoy their careers and in their workplace is said to have a high level of quality of life at work. Organizations that cherish the quality of life at work see employees as a valuable part of the system in the organization and not as an expense. This approach motivates employees that in addition to economic organizations are in pursuit to satisfy their social and psychological needs (Das, Panda, 2015). Analyze of the Impact of Stress and Health on Quality of Working Life In this paper, there are several tasks of research, including: 1. Determining respondents level of Quality of working life, a. defining the system model research, independent and dependent variables - perceptive characters based on the question groups from a set of electronic questionnaire, b. to analyze the partial relations of independent variables - system model elements observational characters: Stress and Health, and the dependent variable Quality of working life, from which are made following research hypothesis: 2. H1 - Stress has significant influence on Quality of working life. 3. H2 - Health has significant influence on Quality of working life. 4. H3 - Stress and Health have significant influence on Quality of working life. Momčilović, O., et al. The Impact of Stress, JWE (2017, No. 1-2, 114-136) 121 Empirical Research Questions about the profile of respondents with possible responses to an electronic questionnaire are defined as follows: Chronological age of the respondents: - from 18 to 30 years, - from 31 to 50 years, and - over 51 years. Employment status of the respondents - to 10 years, - from 11 to 20 years, and - over 21 years. Koulutus of the respondents - Primary or Secondary school, and - College or University. The electronic questionnaire holds the following statements: 1. Relations between management and employees in my workplace are good. 2. I don’t feel stressful at my workplace. 3. I don’t feel exploited at my workplace. 4. My health is good. 5. In the past year I didn’t have any problems with sleeping or insomnia. 6. In the past year I didn’t have any back pain daily for one week or longer. 7. In the past year I didn’t have pain in your hands, wrists, arms or shoulders daily for one week or longer. 8. Conditions in my workplace provide me maximum productivity. 9. Management in my workplace is efficient and peaceful. 10. The Overall physical effort I am doing every day on the job is insignificant. 11. I am satisfied with my workplace. The electronic questionnaire holds the evaluation of statements: 1. strongly disagree, 122 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 114-136) 2. disagree, 3. neither agree neither disagree, 4. agree, and 5. strongly agree. Task 1. Profile information of the respondents From (Table 1 and Chart 1) we can see that out of 198 respondents 48 respondents or 24.24% aged 18 to 30 years, 114 or 57.57% of respondents aged 31 to 50 years and 36 respondents or 18, 18% is over 51 years of age. Table 1: Chronological age of the respondents Level Count Prob from 18 to 30 years 48 0,24242 from 31 to 50 years 114 0,57576 over 51 years 36 0,18182 Total 198 1,00000 Source: Authors Chart 1: Chronological age of the respondents Source: Authors From (Table 2 and Chart 2) we can see that out of 198 respondents 91 respondents or 45.96% of service up to 10 years, 56 respondents or 28.28% of service from 11 to 20 years and 51 respondents or 25.75 % is over 21 years of service. Momčilović, O., et al. The Impact of Stress, JWE (2017, No. 1-2, 114-136) 123 Table 2: Employment status of the respondents Level Count Prob to 10 years 91 0,45960 from 11 to 20 years 56 0,28283 over 21 years 51 0,25758 Total 198 1,00000 Source: Authors Chart 2: Employment status of the respondents Source: Authors From (Table 3 and Chart 3), we can see that out of 198 respondents 106 respondents or 53.53% have completed primary or secondary school, and 92 respondents or 46.46% completed college or university. Table 3: Koulutus respondents Level Count Prob Primary or Secondary school 106 0,53535 College or University 92 0,46465 Total 198 1,00000 Source: Authors 124 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 114-136) Chart 3: Koulutus of respondents Source: Authors By cross-tabulations of data between the employment status of the respondents and chronological age of the respondents, we can see the frequency and percentage of respondents (Table 4 and Chart 4). We can conclude that most of the respondents were: − From 18 to 30 years of age and 10 years of service, 47 or 97.92% of the total number of respondents for age 48, and 51.56% of the total number of respondents up to 10 years of service 91. − From 31 to 50 years of age and from 11 to 20 years of service 52 or 92.86% of the total number of respondents for this age, 114 or 45.64% of the total number of respondents from 11 to 20 years of service 56, and − Over 51 years of age and over 21 years of service 33 respondents or 91.67% of the total number of respondents, 36 or 64.71% of the total number of respondents over 21 years of service was 51. We can conclude that there is the least subjects with: − From 18 to 30 years of age and over 21 years of service, 0 respondents, − Over 51 years of age and 10 years of service, 0 subjects Momčilović, O., et al. The Impact of Stress, JWE (2017, No. 1-2, 114-136) 125 Table 4: Contingency Analysis of Chronological age of the respondents By Employment status of the respondents from 18 to 30 years from 31 to 50 years over 51 years All to 10 years 47 23,74 97,92 51,65 44 22,22 38,60 48,35 0 0,00 0,00 0,00 91 45,96 from 11 to 20 years 1 0,51 2,08 1,79 52 26,26 45,61 92,86 3 1,52 8,33 5,36 56 28,28 over 21 years 0 0,00 0,00 0,00 18 9,09 15,79 35,29 33 16,67 91,67 64,71 51 25,76 All 48 24,24 114 57,58 36 18,18 198 Source: Authors Chart 4: Contingency Analysis of Chronological age of the respondents By Employment status of the respondents Source: Authors By cross-tabulations of data between Chronological age of the respondents by Koulutus respondents, we can see the frequency and percentage of respondents (table 5. and chart 5.). We can conclude that most of the respondents were: 126 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 114-136) − From 18 to 30 years of age with primary or secondary education, 28 or 58.33% of the total number of respondents for age 48 or 26.42% of the total respondents with primary or secondary school 106, and − From 31 to 50 years of age with primary or secondary education, 60 or 52.63% of the total number of respondents in this age, 114 or 56.60% of the total number of respondents with primary or secondary education 106. We can conclude that respondents over 51 years of age with primary or secondary education 18 or 50.00% of the total number of respondents in this age of 36, or 16.98% of the total number of patients with primary or secondary education 106. Also, we can conclude that respondents over 51 years of age who have completed college or university education 18 or 50.00% of the total number of respondents for those age 36 or 19,57% of the total number of respondents with college or university education is 92. We can conclude that there is the least subjects with: − From 18 to 30 years of age and over 21 years of service 0 respondents, − Over 51 years of age and 10 years of service 0 subjects Table 5: Contingency Analysis of Chronological age of the respondents By Koulutus respondents Count Total % Col % Row % from 18 to 30 years from 31 to 50 years over 51 years All Primary or Secondary school 28 14,14 58,33 26,42 60 30,30 52,63 56,60 18 9,09 50,00 16,98 106 53,54 College or University 20 10,10 41,67 21,74 54 27,27 47,37 58,70 18 9,09 50,00 19,57 92 46,46 All 48 24,24 114 57,58 36 18,18 198 Source: Authors Momčilović, O., et al. The Impact of Stress, JWE (2017, No. 1-2, 114-136) 127 Chart 5: Contingency Analysis of Chronological age of the respondents By Koulutus respondents Source: Authors Task 2. Defining model elements System model in this study is composed of two distinct elements (hereinafter referred to as the independent variables) and a dependent element (hereinafter referred to as the dependent variable). Independent variable is made of elements: Health and Stress and a dependent variable of the element Quality of Working Life (QWL) as shown in (Figure 1). Figure 1: System model Quality of Working Life Source: Authors Task 3. Determination of partial relationships - the correlation between the independent variables to the dependent variable Interpretation of results of Pearson correlations: STRESS HEALTH QWL 128 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 114-136) − Table 6. shows the Descriptive Statistics for all variables of the model, where the values of the average score are: • Stress 3,506, • Health 2,489, i • Quality of working life (QWL) 3,743. Table 6: Descriptive Statistics for variables Stress Health QWL Mean 3,506734 2,489899 3,7436869 Std Dev 0,854773 0,6366744 0,6522301 Std Err Mean 0,0607461 0,0452465 0,046352 Upper 95% Mean 3,6265301 2,5791286 3,8350966 Lower 95% Mean 3,386938 2,4006694 3,6522771 N 198 198 198 Source: Authors In (Table 7) is given Scatterplot Matrix Correlations of elements of the model. The number of cases in the sample totals N = 198 is correct and there is no missing data. From the presented diagrams the direction of relationship between variables, as well as the strength of correlation r can be seen. We can note a positive correlation between variables in a number of cases, that it is the largest correlation coefficient between variable Stress and QWL and it amounts r = 0.587, these variables are moderately correlated - related. Table 7: Scatterplot Matrix Correlations Source: Authors Momčilović, O., et al. The Impact of Stress, JWE (2017, No. 1-2, 114-136) 129 Task 4. Analysis of the impact of partial variables Stress and Health for variable QWL In (Table 8) Summary of Fit is calculated coefficient of determination (RSquare) r2 = 0.344537 that indicate what percentage of variance of the dependent variable QWL is explained in model and the multiple correlation coefficient (R) r = 0.586972 which indicates the strength of the connection between variables. It means that 58.69% of the variability of the dependent variable QWL can explain through the influence of independent variables Stress. Here variables are moderately correlated - related Table 8: Summary of Fit for variable Stress and QWL Rsquare 0,344537 RSquare Adj 0,341193 Root Mean Square Error 0,529395 Mean of Response 3,743687 Observations (or Sum Wgts) 198 Source: Authors In order to assess the statistical significance, observe (Table 9) ANOVA. Here are the results of tests of the null hypothesis that the r2 in population is equal 0. Statistical significance was (Sig. = 0.0001), which means that r <0.0005. Hypothesis H1 - variable Stress significantly affect the variable QWL is confirmed. Table 9: ANOVA Source DF Sum of Squares Mean Square F Ratio Model 1 28,873787 28,8738 103,0253 Error 196 54,930822 0,2803 Prob > F C. Total 197 83,804609 <,0001* Source: Authors From (Table 10) coefficients (Coefficients) is determined how the independent variable in the model Stress contributed to the prediction of the dependent variable QWL. In this case the beta coefficient is 0,586973, which means that the independent variable Stress contributes to explaining the dependent variable QWL. Column Prob> |t|. observes the contribution of 130 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 114-136) variables in the equation (the value of Sig. <0.05.). In this case, the independent variable Stress makes a significant contribution to the equation. Table 10: Coefficients Term Estimate Std Error t Ratio Prob>|t| Std Beta Intercept 2,1730681 0,159247 13,65 <,0001* 0 Stres 0,4478865 0,044126 10,15 <,0001* 0,586973 Source: Authors Linear regression equation reads as follows: or: On (diagram 1) is given diagram of linear regression equation. Diagram 1: Diagram of linear regression equation for the dependent variable QWL Source: Authors In (Table 11) Summary of Fit is calculated coefficient of determination (RSquare) r2 = 0,177083 that indicate what percentage of variance of the dependent variable QWL is explained in model and the multiple correlation coefficient (R) r = 0,420812 which indicates the strength of the connection between variables. It means that 42,08% of the variability of the dependent variable QWL can explain through the influence of independent variables Health. Here variables are relatively poorly correlated- related Momčilović, O., et al. The Impact of Stress, JWE (2017, No. 1-2, 114-136) 131 Table 11: Summary of Fit for variable Health and QWL Rsquare 0,177083 RSquare Adj 0,172884 Root Mean Square Error 0,593177 Mean of Response 3,743687 Observations (or Sum Wgts) 198 Source: Authors In order to assess the statistical significance, observe (Table 12) ANOVA. Here are the results of tests of the null hypothesis that the r2 in population is equal 0. Statistical significance was (Sig. = 0.0001), which means that r <0.0005. Hypothesis H2 - variable Health significantly affect the variable QWL is confirmed. Table 12: ANOVA Source DF Sum of Squares Mean Square F Ratio Model 1 14,840335 14,8403 42,1770 Error 196 68,964274 0,3519 Prob > F C. Total 197 83,804609 <,0001* Source: Authors From (Table 13) coefficients (Coefficients) is determined how the independent variable Health in the model contributed to the prediction of the dependent variable QWL. In this case the beta coefficient is 0,420812, which means that the independent variable Health contributes to explaining the dependent variable QWL. Column Prob> | t |. observes the contribution of variables in the equation (the value of Sig. <0.05.). In this case, the independent variable Health makes a significant contribution to the equation. Table 13: Coefficients Term Estimate Std Error t Ratio Prob>|t| Std Beta Intercept 2,6703079 0,170569 15,66 <,0001* 0 Health 0,4310934 0,066379 6,49 <,0001* 0,420812 Source: Authors 132 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 114-136) Linear regression equation reads as follows: or: On (diagram 2) is given diagram of linear regression equation. Diagram 2: Diagram of linear regression equation for the dependent variable QWL Source: Authors Task 5. Analysis of influence of group variables Stress and Health for variable QWL In (Table 14) Summary of Fit is calculated coefficient of determination (RSquare) r2 = 0,390736 that indicate what percentage of variance of the dependent variable QWL is explained in model and the multiple correlation coefficient (R) r = 0, 625088 which indicatess the strength of the connection between variables. It means that 62,50% of the variability of the dependent variable QWL can explain through the influence of independent variables Stress and Health. Here variables are moderately strong correlated – related Table14: Summary of Fit for variables Health and QWL Rsquare 0,390736 RSquare Adj 0,384487 Root Mean Square Error 0,511705 Mean of Response 3,743687 Observations (or Sum Wgts) 198 Source: Authors Momčilović, O., et al. The Impact of Stress, JWE (2017, No. 1-2, 114-136) 133 In order to assess the statistical significance, observe (Table 15) ANOVA. Here are the results of tests of the null hypothesis that the r2 in population is equal 0. Statistical significance was (Sig. = 0.0001), which means that r <0.0005. Hypothesis H3 - variables Stress and Health significantly affect the variable QWL is confirmed Table 15: ANOVA Source DF Sum of Squares Mean Square F Ratio Model 2 32,745436 16,3727 62,5290 Error 195 51,059173 0,2618 Prob > F C. Total 197 83,804609 <,0001* Source: Authors From (Table 16) coefficients, is determined how the independent variables Stress and Health in the model contributed to the prediction of the dependent variable QWL. In this case the beta coefficient is 0, 499245, which means that the independent variable Stress individually contributes most to explaining the dependent variable QWL. Column Prob> | t |. observes the contribution of variables in the equation (the value of Sig. <0.05.). In this case, the independent variables Stress and Health make a significant contribution to the equation. Table 16: Coefficients Term Estimate Std Error t Ratio Prob>|t| Std Beta Intercept 1,8156512 0,179813 10,10 <,0001 0 Stress 0,3809461 0,046068 8,27 <,0001 0,499245 Health 0,2378245 0,061848 3,85 0,0002 0,232152 Source: Authors Linear regression equation reads as follows: or: On (diagram 3) is given 3D Surface diagram of values of all the variables of the proposed model. 134 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 114-136) Diagram 3: 3D surface diagram of the variables: Stress, Health i QWL Source: Authors Conclusion There is no consensus on a definition of quality of life at work or a consensus on what makes a quality job but all authors agree that quality of life at work can be represented by the degree of employee satisfaction. Organizations that cherish the quality of life at work see employees as a valuable part of the system in the organization and not as an expense. This approach motivates employees that in addition to economic, organizations are in pursuit to satisfy their social and psychological needs. This paper represents contribution to understanding the connection between forementioned variables and their impact on women’s quality of working life. By forementioned proven hypothesis (H1 - Stress has significant influence on Quality of working life, H2 - Health has significant influence on Quality of working life and H3 - Stress and Health have significant influence on Quality of working life) we can have influence at the level of job satisfaction by altering the level of independent variables individually. Referenecs [1] Almarsh, O. S. 2015. “A Measurement Scale for Evaluating Quality of Work Life: Conceptualization and Empirical Validation.” Trends In Applied Sciences Research, 10(3): 143-156. Momčilović, O., et al. The Impact of Stress, JWE (2017, No. 1-2, 114-136) 135 [2] Dahl, S., Nesheim, T., & Olsen, K. “Quality of Work: Concept and Measurement.” SSRN Electronic Journal. [3] Das, U., & Panda, J. 2015. “A study on measuring the Quality of Work Life among the Power Sector Employees with Special Reference to Orissa Hydro power Corporation Limited, Bhubaneswar, Odisha, India.” International Journal Of Advance Research In Computer Science And Management Studies, 3(4), 28-29. Retrieved from [4] Galić, B. 2011. “Žene i rad u suvremenom društvu – značaj “orodnjenog” rada.” Sociologija i prostor. 49. 189 (1): 25. [5] Gavric G., Sormaz G., Ilic Dj. 2016. “The impact of organizatioanal culture on the ultimate performance of company.” Internationa Review, 3- 4:25-31. Belgrade: Faculty of Business Economics and Entrepreneurship, Medimond, Italy. [6] Gayathiri, R., & Ramakrishnan, L. 2013. “Quality of Work Life - Linkage with Job Satisfaction and Performace. “International Journal Of Business And Management Invention, 2(1): 01-08. [7] Greenan, N., Kalugina, E., & Walkowiak, E. 2013. “Has the quality of working life improved in the EU-15 between 1995 and 2005?” Industrial And Corporate Change, 23(2): 399-428. [8] Indrani, G. G., & Devi, D. 2011. “A Literature Review on Quality of Work Life.” IJAR, 4(8): 101-104. [9] Kalleberg, A., Reskin, B., & Hudson, K. 2000. “Bad Jobs in America: Standard and Nonstandard Employment Relations and Job Quality in the United States.” American Sociological Review, 65(2): 256. [10] Lanctôt, N., Durand, M., & Corbière, M. 2011. “The quality of work life of people with severe mental disorders working in social enterprises: a qualitative study.” Qual Life Res, 21(8): 1415-1423. [11] Martel, J., & Dupuis, G. 2006. “Quality of Work Life: Theoretical and Methodological Problems, and Presentation of a New Model and Measuring Instrument.” Soc Indic Res, 77(2): 333-368. [12] Narehan, H., Hairunnisa, M., Norfadzillah, R., & Freziamella, L. 2014. “The Effect of Quality of Work Life (QWL) Programs on Quality of Life (QOL) among Employees at Multinational Companies in Malaysia.” Procedia - Social And Behavioral Sciences, 112: 24-34. [13] Parsa, B., Idris, K., Samah, B., Wahat, N., & Parsa, P. 2014. “Relationship between Quality of Work Life and Career Advancement among Iranian Academics”. Procedia - Social And Behavioral Sciences, 152: 108-111. [14] Prljic S., Vucekovic M., Vujicic S. 2015. ”The Importance of Information and Communication Technologies in the Development of Women Entrepreneurship.” Journal of Women,s Entrepreneurship and Education, 3-4/2015: 65-79. Belgrade: Institute of Economic Sciences. 136 Journal of Women’s Entrepreneurship and Education (2017, No. 1-2, 114-136) [15] Ravic N., Nikitovic Z. 2016. “Entrepreneurial Education As a New Paradigm of the Development of Women Entrepreneurship in the Republic of Serbia.” Journal of Women,s Entrepreneurship and Education, 3-4/2016: 102-116. Belgrade: Institute of Economic Sciences. [16] Safina L., Kolesnikova J., Karasik E.,Yurieva O., Fakhrutdinova, A. 2015. “The Higher Education Impact on the Quality of Young People Working Life.” Procedia - Social And Behavioral Sciences, 191: 2412-2415. [17] Wilkinson, G., & Dale, B. 1999. “Integrated management systems: an examination of the concept and theory”. The TQM Magazine, 11(2). Article history: Received: 15 February, 2017 Accepted: 12 May, 2017