IMPACT OF JOB SATISFACTION ON QUALITY WORK LIFE AMONG THE IT EMPLOYEES

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1 IMPACT OF JOB SATISFACTION ON QUALITY WORK LIFE AMONG THE IT EMPLOYEES V.GEETHA Research Scholar, Kalasalingam University, Tamilnadu DR.M.JEYAKUMARAN Department of Business Administration, Kalasalingam University, Tamilnadu, YAVANA RANI.S Department of Business Administration, Kalasalingam University, Tamilnadu ABSTRACT In this paper, we examine quality of working life (QWL) and compare the predictors of QWL among 250 employees in a variety of information technology (IT) jobs in five companies. Quan titative data was gathered through questionnaires, totally 250 questionnaires were distributed to the respondent 220 questionnaires were returned and analyzed using SPSS version 16. The following QWL factors were examined: job satisfaction, Uncertainty and Attrition, fatigue& tension, the following predictors of QWL were studied: Adequate and Fair Compensation, Safe and healthy working conditions, Opportunities for training and development, Opportunities for career advancement, Social integration, Discrimination, Welfare Measures, and demographics(age, marital status, parental status. And education). Data were analyzed using descriptive statistics, chi-square test and regression analysis to test the formulated hypotheses and the significance and reliability of the findings. The findings suggest there is a positive and significant relationship between QWL and employees job satisfaction. Analysis shows that male workers are having high QWL than female workers in IT jobs. Quality of work life increases with Job satisfaction and decreases with Job Uncertainty and Attrition and Fatigue and Tension. IT companies are creating a positive environment for efficient and smooth work. Finally, the results of this survey can also used as baseline measures against which the findings of future quality of work life surveys can be compared. Such comparisons place this type of research within a continuous quality improvement framework. Key Words: Job Satisfaction, Quality of Work Life, Information Technology 1.1 INTRODUCTION One of the major problems facing by the developing and developed country is quality of work life. The issue is not just one of achieving greater human satisfaction but it also aims at improving productivity, adaptability and overall effectiveness of organization. The quality of work life is more concerned with the overall climate of work and the impact that work has on people as well as on organization effectiveness. Direct participation of employees in problem solving and decision making, particularly in the areas related to their work, and is considered to be a necessary condition for providing greater autonomy and opportunity for self-direction and self-control. The ultimate objective is of upgrading the quality of work life at work. The term quality of working life (QWL) was probably coined originally at the first international conference on QWL at Arden House in 1972 (Davis & Cherns, 1975). Quality of working life has also been viewed in a variety of ways including: (a) as a movement; (b) as a set o f organizational interventions, and (c) as a type of working life felt by employees (see Carlson, 1980). Our paper focuses on the third perspective of QWL. That is, our main concern is finding out what comprises a quality working life experience among organizational employees in India. In the present study, we are concerned with how the employee perceives a high quality working life experience. There are a number of reasons why investigation of the perceptions of quality of working life for employees merits investigation. The present study attempts to make an identification of factors perceived to be important in a quality working life experience. It aims to explore the conception Indian workers have of QWL REVIEW OF LITERATURE Many factors influence an employee s commitment to the organization and satisfaction with his or her job. One particular powerful factor that prior research has repeatedly shown to be significantly 20

2 correlated to the job attitudes of interest (namely organizational commitment, j ob satisfaction and turnover intention) is work exhaustion, or job burnout (Moore, 2000; Moore & Burke, 2002). The research literature in IT and the popular press suggest that technology professionals are particularly vulnerable to work exhaustion and stress (Kalimo & Toppinen, 1995; McGee, 1996). Igbaria and Greenhaus (1992) tested a model of turnover intentions and QWL among 464 management information systems (MIS) employees using employee questionnaires. The model consisted of five sets of variables: 1) demographic variables; 2) role stressors; 3) career experiences; 4) work-related attitudes or QWL; and 5) turnover intentions. Results indicated that two measures of QWL, job satisfaction and organizational commitment, had the strongest and most direct influence on turnover intentions, and the impact of other variables on turnover intentions was primarily mediated by these two variables. Education was the only demographic variable that had a direct effect on turnover intention. Higher educated employees had higher turnover intention and lower job and career satisfaction. Employees with low salaries and those who perceived limited career advancement opportunities tended to hold stronger turnover intention than those with higher salaries and more career advancement opportunities, through both direct and indirect effects. Role stressors had a positive, indirect effect on turnover intentions through low job and career satisfaction and organization commitment. Organizational commitment had a strong, negative effect on turnover intention, but inconsistent with prior research, job satisfaction had stronger effects than organizational commitment on turnover intention (Igbaria & Greenhaus, 1992). This study confirms that a range of job and organizational factors can influence QWL that, in turn, can influence turnover intention among IT workers. Many factors influence an employee s commitment to the organization and satisfaction with his or her job. One particular powerful factor that prior research has repeatedly shown to be significantly correlated to the job attitudes of interest (namely organizational commitment, job satisfaction and turnover intention) is work exhaustion, or job burnout (Moore, 2000; Moore & Burke, 2002). The research literature in IT and the popular press suggest that technology professionals are particularly vulnerable to work exhaustion and stress (Kalimo & Toppinen, 1995; McGee, 1996) The title was quality of work life in public sector banks an empirical study. To find out how for the satisfaction of human needs according to his or her priority acts motivational factors in determining quality of work life. It aims at finding out which type of needs of bank employees are highly dissatisfied, so that efforts could be made to fulfill them first as motivator. Findings: Employees in commercial banks believe that work is a source of need fulfillment and a satisfaction too. Their most dissatisfied needs are esteem needs followed by self actualization needs and social needs probably they are more in need of human tough. Dr.Umesh C. Patnaik (1993) QWL has been defined by many researchers in a variety of ways, thus presenting some disagreement on a precise definition; however, there is general consensus of its multidimensional qualities and usefulness as a concept (Baba & Jamal, 1991).. Davis (1983) has defined QWL as the quality of the relationship between employees and the total working environment, with human dimensions added to the usual technical and economic considerations (p.80). Using this definitio n, we examine a range of indicators of QWL: job satisfaction, organizational involvement, fatigue, tension, and burnout (emotional exhaustion). The Sociotechnical Systems Theory (STS) (Trist, 1981), the Organizational Health Model (Sauter, Lim, & Murphy, 1 996) and the Balance Theory (Smith & Carayon -Sainfort, 1989) provide theoretical perspectives for examining work systems. The STS emphasizes the interrelatedness of the social and technical systems within an organization and integrates job and organizational design perspectives, through linking the job design theories of human relations, job enrichment and participation. The Organizational Health Model asserts that organizational characteristics (e.g., management practices, organizational values) directly i nfluence organizational health i.e. performance outcomes and satisfaction outcomes (Sauter et al., The Balance Theory is a theoretical framework that examines job and organizational design characteristics within each component of the work system that interact to influence the stress load upon an individual (Smith & Carayon-Sainfort, 1989). It identifies sources of occupational stress (stressors or psychosocial work factors) that can influence stress, attitudes and behaviors (e.g., turnover intention). Cooper & Marshall, 1976; Karasek, 1979; Theorell & Karasek, 1996). In this study, we examined four job design factors: IT demands, role ambiguity, decision control, and challenge. In addition to these job design factors, we use four demographic characteristics: age, parental status (having children versus not), marital status (type of living condition, e.g., living alone versus not), and education level (highest level of formal education achieved, e.g., high school or G.E.D., some college, Bachelors degree, some graduate/professional study, or graduate/professional degree). 21

3 3.1. OBJECTIVES 1. To measure the QWL among the Information Technology employees 2. To Compare QWL among women and men. 3. To find the relationship between Job characteristics /demographics and QWL among men and women. 4.1.RESEARCH METHODOLOGY In this research five IT companies are selected by considering the Certified Network expert (CNX IT) index list. The data collection tool used is a 65-item questionnaire. The 65 items were divided in to 10 dimensions. Seven dimensions consist of dependent variables and three dimensions consist of Independent variables. The questionnaire has sent to the respondent by post and through . Data collection for this project started in December 2008 and is still in progress, we used data collected up to September DATA COLLECTION The survey was conducted in five IT industries. A stratified random sampling procedure was employed; totally 250 questionnaires were distributed to the respondent. However, only 220 survey questionnaires were returned, yielding a response rate of 80% ANALYSIS AND INTERPRETATION Analysis was conducted using the statistical software program SPSS. To look for significant differences between female and male in the QWL factors, the mean values reported by women and by men were compared using t-test. We then examined the influence of demographic factors on QWL. This step of analysis helped us identify the demographic variables to enter in the regression analysis of QWL. Regression analysis was then conducted between job satisfaction (dependent variable) and the 3 job characteristics (Job satisfaction, Uncertainty & Attrition, Fatigue & tension) and demographics variables where applicable (independent variables) for female and male. The same will be followed for each of the rest of the QWL factors, i.e. Uncertainty and Attrition, fatigue& tension. Null Hypothesis : There is no significant difference between male and female with respect to the dimension of QWL feelings from Table 1, P value is less than 0.01, null Hypothesis is rejected at 1% level with respect to dimension of uncertainty and attrition, fatigue and tension and overall QWL. Hence there is significant difference between Male and Female with respect to uncertainty and attrition, fatigue and tension and overall QWL. Since P value is less than 0.05, Null hypotheses is rejected at 5% level with respect to job satisfaction. Hence there is a significant difference between Gender with respect to Job satisfaction. Job satisfaction, Uncertainty & Attrition, and Fatigue & tension are more with female workers than the male workers. Because the female workers are having more family burden. If the company should provide welfare measures like Crèches, Job security, Rest Room, Flexible time of working hours, entertainment etc., in order to improve the level of QWL feelings. Null Hypothesis: There is no significant difference between income group with respect to dimension of Job characteristics From Table 2, P value is less than 0.01, null hypothesis is rejected at 1% level of Monthly Income with regard to Safe and Healthy Working Conditions, Opportunities for training and development, Opportunities for career advancement, Social integration, Welfare Measures and Job characteristics Based on DMRT, Monthly Income group between is significance with other income groups at 5% level with respect to Safety and Healthy Working Conditions. Monthly Income group below is significance with other income groups at 5% level with respect to Opportunities for career advancement. Monthly Income group between is significance with other income groups at 5% level with respect to Welfare Measures. Since P value is less than 0.05, Null hypothesis is rejected at 5% level with respect to discrimination. Hence there is significant difference between Monthly Income with respect to discrimination. Based on Duncan Multiple Range Test (DMRT) the monthly income g roup below 10,000 and to varies significantly with other the groups with 5% level. There is no significant difference between monthly income with regard to Adequate and Fair compensation since P value is greater than So Null Hypothesis is accepted at 5% level with regard to Discrimination. 22

4 Null Hypothesis: There is no association between levels of Job characteristics and QWL From Table 3, P value is less than 0.01, Null Hypothesis is rejected at 1% level, hence there is association between level of Job characteristics and QWL From the table3, it is inferred 68.4% of employees QWL is low when the Job characteristics factors is also low. 49.2% of employees QWL is high when Job characteristics factors is high When Job characteristics factors is high, Quality of work life of employees is increasing accordingly, because the concern should fulfill the expectations of the employees, they will devotion of their energies with full pledged to the concern. Multiple Regressions of Job Characteristics and QWL 1. Dependent Variable Quality Work Life 2. Independent Variable- Job Satisfaction(X1) Job Uncertainty and Attrition(X2) Fatigue and Tension(X3) 3. Multiple R value R Square value F-Value P-Value ** QWL.The three predictor variables are Job Satisfaction, Job Uncertainty and Attrition, Fatigue and Tension. As depicted in the coefficients table (Ta ble 5), the estimates of the model coefficients for βo is ,β1 is 0.813, β2 is , β3 is Therefore, the estimated model is as below: Quality Work Life (Y) = (X1) (X2) (X3)..(I) The R-squared of implies that the four predictor variables explain about 12.3% of the variance in the QWL. The ANOVA table revealed that the F-statistics ( ) and the corresponding p -value is highly significant (0.000) or lower than the alpha value of This indicates that the slope of the estimated linear regression model line is not equal to zero confirming that there is linear relationship between QWL and the predictor variables. As depicted in Table 5, the Beta value for job satisfaction is the highest (0.321), f ollowed by Job Uncertainty and Attrition (0.106). The Beta value for Fatigue and Tension is the smallest ( ) indicating that it made the least contribution. From Table 5, p value is less than.01, the independent variable Job Satisfaction is statistically significant in the model. The other independent variables i.e., Job Uncertainty and Attrition and Fatigue and Tension are not significant at 95% confidence limit. The equation we have obtained means that Quality of work life will increase with Job satisfaction and will decrease with Job Uncertainty and Attrition and Fatigue and Tension DISCUSSION Based on the literature, we expected that female in IT jobs would report poorer QWL than male in IT jobs (Baroudi & Igbaria, 1995; Igbaria & Greenhaus, 1992), leading to greater turnover for women in IT. It can be seen that in our study female workers IT jobs equal QWL with male workers in IT jobs. There were some difference between women and men with regard to the job characteristics that influence QWL.68.4% of employees QWL is low when the Job characteristics factors is also low. 49.2% of employees QWL is high when Job characteristics factors is high. Similarly education, employment, marital Status play vital role for QWL and Gender, age designation, income Size of the family and children has made least contribution to QWL. When Job characteristics factors is high, Quality of work life of employees is increasing accordingly, because the concern should fulfill the expectations of the employees, they will devotion of their energies with full pledged to the concern. Quality of work life will increase with Job satisfaction and will decrease with Job Uncertainty and Attrition and Fatigue and Tension Conclusion The result of this study supports the proposition that the degree of satisfaction in QWL is related to the degree to which the individual believes his or her success criteria have been met, especially if the individual places great importance on these criteria which include Adequate and Fair Compensation, Opportunities for career advancement, Social integration and Welfare Measures. 23

5 It can also be concluded from the data, that job satisfaction correlates with his/her level of QWL. Job satisfaction contributes more for quality of work life, Job Uncertainty and Attrition and Fatigue and Tension made the least contribution t QWL. In the current context, the emphasis is on income, position and personal growth and opportunity in career mobility as potential success indicators. Further, this is related to having a harmonious successful home environment from spousal and family support that is highly valued where career balance is expected to provide some impact as found in this study. It can thus be concluded that the essential predictors of QWL appears to be career related. QWL can be heightened through harmonious safety and healthy working conditions that serves as a psychological dynamism. This study has the potential value for further research. To ensure representative ness, the study should be replicated to cover a bigger sampling frame in other states and the results should be compared to those found in this study. REFERENCES Baba, V., & Jamal, M. (1991). Routinization of job context and job content as related to employees' quality of working life: A study of Canadian nurses. Journal of Organizational Behavior, 12, Cooper, C. L., & Marshall, J. (1976). Occupational sources of stress: A review of the literature relating to coronary heart disease and mental ill health. Journal of Occupational Psychology, 49(1), Igbaria, M., & Greenhaus, J. H. (1992). Determinants of MIS employees' turnover intentions: A structural equation model. Communications of the ACM, 35(2), Kalimo, R., & Toppinen, S. (1995). Burnout in computer professionals. Paper presented at the Paper presented at the Work, Stress and Health 1995: Creating Healthier Workplaces, Washington, DC. Moore, J. E. (2000). One road to turnover: An examination of work exhaustion in technology professionals. MIS Quarterly, 24(1), Moore, J. E., & Burke, L. (2002). How to turn around 'turnover culture' in IT. Communications of the ACM, 45(2), Sauter, S., Lim, S. Y., & Murphy, L. R. (1996). Organizational Health: A New Paradigm for Occupational Stress at NIOSH. (Japanese Journal of) Occupational Mental Health, 4(4), Smith, M. J., & Carayon-Sainfort, P. (1989). A balance theory of job design for stress reduction. International Journal of Industrial Ergonomics, 4, Cooper, C. L., & Marshall, J. (1976). Occupational sources of stress: A review of the literature relating to coronary heart disease and mental ill health. Journal of Occupational Psychology, 49(1), Trist, E. (1981). The Evaluation of Sociotechnical Systems. Toronto: Quality of Working Life Center. Umesh Patnaik (1993), Personnel Today, National Institute of Personnel Management Vol.13, Jan May Davis, L. & Cherns, A. (Eds.). (1975). The quality of working life. New York: Free Press. Carlson, H. (1980). A model of quality of work life as a developmental process. In W. Warner Burke & L. D. Goodstein (Eds.), Trends and Issues in 0D: Current Theory and Practice (pp ). San Diego,CA: Univ. Associates. Annexure Table 1: Student t- test for significant difference between Genders with respect to Dimension of Male Female Dimension of QWL Mean S.D Mean S.D QWL Note: ** denotes significant at 1% level * denotes significant at 5% level t value P value Job satisfaction * Uncertainty and Attrition ** Fatigue & tension ** Overall QWL feelings ** 24

6 Table 2: ANOVA for significance difference between monthly incomes with respect to dimension of Job characteristics F value P value Monthly income in Rs. Dimensions of Job Below Above Characters Adequate and Fair Compensation Safe and healthy working ** 14.11a 16.06b 13.85a 14.00a conditions Opportunities for training and development ** 24.92c 23.41b 21.99ab 21.65a Opportunities for career ** 20.11b 18.17a 18.59a 17.59a advancement Social integration ** 17.81a 21.68b 20.72b 21.97b Discrimination * 14.94a 16.23b 14.97a 16.08b Welfare Measures ** 38.11c 35.65ab 34.26a 36.76bc Job characteristics ** b b a ab Note: different alphabets between the income groups denotes significant at 5% level by using Duncan Multiple Range Test (DMRT) Table-3: Chi-square test for Association between levels of Job characteristics and QWL Level of Job Level of QWL Row Chi-square p value characteristics total value Low Average High Low (68.4) (21.1) (10.5) Average (9.6) (71.2) (19.2) ** High (22.0) (28.8) (49.2) Column total Table 4 : Analysis of variance (ANOVA) Table 5: Multiple Regressions Variable Unstandardized Coefficients Standardized Coefficients t-value P-Value. B Std. Error of B Beta X ** X X Constant