A study on turnover intentions of software professionals in Chennai city

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The study was done among the 112 IT professionals employed in the various leading IT organizations located at Chennai Metropolitan City. The results revealed the importance of stress related factors, supervisor’s relationship, compensation and accommodation on quitting the job among IT professional.

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International Journal of Management INTERNATIONAL JOURNAL (IJM), OFISSNMANAGEMENT 0976 – 6502(Print), ISSN 0976 - (IJM) 6510(Online), Volume 6, Issue 4, April (2015), pp. 44-51© IAEME ISSN 0976-6502 (Print) ISSN 0976-6510 (Online) IJM Volume 6, Issue 4, April (2015), pp. 44-51 © IAEME: http://www.iaeme.com/IJM.asp ©IAEME Journal Impact Factor (2015): 7.9270 (Calculated by GISI) www.jifactor.com A STUDY ON TURNOVER INTENTIONS OF SOFTWARE PROFESSIONALS IN CHENNAI CITY Dr. R.SIVARETHINAMOHAN Research Supervisor, Bharathiyar University, Coimbatore, Tamilnadu, India Mr. P.ARANGANATHAN Research Scholar, Bharathiyar University, Coimbatore, Tamilnadu, India Associate Professor & HOD /MBA M.I.E.T. Engineering College, Trichy-620007, Tamilnadu, India ABSTRACT One of the critical problems faced in the IT organization is high employee turnover rates and today the organizations formulate constructive strategies to retain their talent work force. Particularly turnover intentions of software professionals are usually high since they enjoy good career opportunities in other organizations. Hence the organizations are in need to identify their turnover intentions and thereby increase their retention rates to ensure high productivity. Hence this research was conducted with the purpose is to study the impact of the various dimensions influencing turn over intentions such as stressors, supervisor relationship, compensation, and accommodation on turnover intention among IT professionals in Indian IT organizations. The study was done among the 112 IT professionals employed in the various leading IT organizations located at Chennai Metropolitan City. The results revealed the importance of stress related factors, supervisor’s relationship, compensation and accommodation on quitting the job among IT professional. Key words: Role Ambiguity, Role Conflict, Work-Exhaustion, Accommodation, Job Satisfaction, Work Schedule Flexibility, Career Accommodation, Etc 1. INTRODUCTION In the current business world, most of the activities of any organization are based on Information Technology and hence the continuity of IT infrastructure plays a significant role. The IT professionals have specialized skills and hence their attrition adversely impact the competitive position of the organization and finally affect the organizational success. Moreover the turnover of IT professionals increases the turn over expenses which adversely increase the overheads of the organizations. Many research studies have estimated that the average cost of replacing talented IT workers is twice their annual salaries. Hence the IT organizations take a number of efforts to decrease the turnover rate of the talented professionals. 44
International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 6, Issue 4, April (2015), pp. 44-51© IAEME It is also the fact that most of the IT professionals possess a strong tendency to do job hopping even for some minimum extra benefits. Talented IT professionals always have high demand and hence have more chances to land on new jobs. Identifying the reasons for causing the turnover of the employees remains a challenge for the management and researchers. This study aims to find out the effects of stressors (role ambiguity, role conflict, work - exhaustion), supervisor relationship, compensation, and accommodation on the IT professionals’ intention to quit their current jobs. IT professionals working in Chennai city were selected as the focus group in this study. It is obvious that IT professionals work in a dynamic environment where continuous updating of skills is required. In addition, IT professionals suffer from extensive projects and aggressive timelines which could lead to high levels of job stress. This research study will provide evidence to the impact of stressors, supervisor relationship, compensation, and accommodation on turnover intention among IT professionals. The findings of the research will enhance the importance of stress related factors, supervisor’s relationship, compensation and accommodation on quitting the job among IT professional who work in leading IT organizations located at Chennai city, Tamilnadu, India. 2. STATEMENT OF THE PROBLEM Indian IT industry always possesses a severe shortage of talented IT professionals even though the country produces many software professionals. Hence the Indian IT professionals today have considerable opportunities all over the world. In this context, head-hunting and job-hopping has become very usual resulting in high level of attritions among the IT Organizations. Even though the Indian Information Technology (IT) sector creates good demand for professionals still the companies face rising attrition levels as the professionals enjoy new opportunities that are now available in the marketplace. Hence understanding the attrition intentions and retaining talented professionals in the IT Organizations is therefore a great challenge posed on the HR Managers of IT Organizations. 3. LITERATURE REVIEW Mobley in (1977) developed a model that explains the process of dissatisfaction that an employee feels and how s/he arrives at a decision to leave the organization. Mobley identified several intervening variables that could serve as mediators to the effect of job satisfaction. Price & Muller (1981) observed that job dissatisfaction influenced actual turnover indirectly through its direct effect on turnover intention. The variables that affect job satisfaction are pay, promotion opportunities, immediate supervisor, fringe benefits, contingent rewards, rules and procedures, relation with co-workers, type of work done, and communication within the organization. Igbaria et al., (1994) found out that Job satisfaction and organizational commitment play very important roles in influencing employee intentions to stay with their organization. Lee (2000) the need for challenge and achievements, the components of job satisfaction, plays a significant role in influencing turnover intentions among IT professionals (Lee, 2000). Firth et al., (2004) job stress is the experience of job-related stress. It may result from work exhaustion and job-related anxiety. Also distinguished stressors into four categories: role ambiguity, role conflict, work-overload and work-family conflict. Messersmith,( 2007); Ahuja, (2007); Joseph, (2007); Love and Irani, (2007); Rutner, (2008); King, (2005); Reid, (2009); Messersmith (2007) found that IT professionals are usually confronted with many challenges, such as longer work hours, unrealistic deadlines for extensive projects, role overload, role ambiguity and work-overload, and these factors lead to stress. Kuruuzum(2009)the concept of organizational commitment gained increasing attention with a negative relationship between absenteeism, employee turnover and organizational commitment. Especially, this negative relationship between organizational commitment and turnover is found to be stronger in higher status occupations (e.g., professionals) than lower-status occupations (e.g., blue- color employees) (Cohen and Hudecek, 1993) Fethi Calisir and Cigdem A. Gumussoy and Ibrahim Iskin (2011) explore the effects of stressors (role ambiguity, role conflict, work-overload, and work-family conflict), job stress, job 45
International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 6, Issue 4, April (2015), pp. 44-51© IAEME satisfaction and organizational commitment on the information technology (IT) professionals’ intention to quit their jobs in Turkey. M Kannan and K Vivekanandan (2012), established that Organizational Satisfaction, Job Satisfaction, Interpersonal Relationship with Supervisor's and Life Satisfaction has significant impact on Turnover Intentions among new entrants working in software industry which is located in Chennai. Raman, Ramakrishnan and Bharathi, Vijayakumar and Allen, Shesha and Joseph, Shaji (2013) revealed the clarity of role and adequacy of resources, nurturing employee loyalty, organizational inspiration as the key drivers against turnover intentions. Interestingly, the study found that work- family-conflict and work stress did not lead to turnover intentions. 4. OBJECTIVE The study has been conducted with objective to study the impact of the dimensions such as stressors, supervisor relationship, compensation, and accommodation on turnover intention among IT professionals in Indian IT organizations located in Chennai metropolitan city. 5. METHODOLOGY This research study is descriptive in nature. The study was done among the 112 IT professionals employed in the various leading IT organizations located at Chennai Metropolitan City. The researchers used standard questionnaire developed by themselves, R.Sivarethinamohan & P.Aranganathan (2014) as a primary tool for data collection. The questionnaire focuses on ten dimensions of turnover intention as follows: Role ambiguity, Role conflict, Work-exhaustion, Supervisor's feedback, Leader Member exchange, Promotion Satisfaction, Fairness of individual rewards, Job security, Career accommodation and Work Schedule Flexibility totally consisting of 65 variables. The reliability of the tools was tested and found to be 0.783 after applying Spearman’s brown prophecy formula. Attempt is made to find out if the factors influencing employee turnover intentions have any significant relationship with variables and with demographic variables. The secondary data was collected from the various sources like magazines, journals, dailies, websites, books, etc. 6. RESPONDENTS The professionals employed in IT organizations located in Chennai were selected for conducting the research. The respondents were informed in advance about the purpose of the study and the research team assured the respondents that the data would be confidential and only the statistical inferences would be published without stating the company name, etc. Out of 120 questionnaires distributed to the respondents, 112 questionnaires were useable for analysis. (see Table -6.1 for demographic details of the sample). Table-6.1 Socio Demographic details: S.No Particulars Respondents in percentage 40 yrs 1 Age group in years 10.7% 63.4% 24.1% 1.8% UG PG Professional Degree(B.E.) 2 Qualification 1.8% 44.6% 55.4% >1 yr 1 to 2 yrs 3 to 5 yrs 6 to 10 yrs >10 yrs 3 Work experience in years 22.4% 18% 41% 14.1% 4.5% Male Female 4 Gender 69.6% 30.4% Married Unmarried 5 Marital Status 44.6% 55.4% 46
International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 6, Issue 4, April (2015), pp. 44-51© IAEME The analysis showed that only 30.4% of the respondents were females. 74.1% of the respondents were of the age less than 30 years. 55.4 % of the respondents were qualified with professional degrees and 44.6 % of the respondents were post graduated whilst 1.8% was qualified with UG degrees. 81% of the respondents have the work experience less than 5 years. 7. ANALYSIS OF DATA The data was analyzed using the statistical package SPSS 17.0. Descriptive statistics, multiple regression and correlation analysis and reliability estimates were used for the findings. 7.1 Multiple Regression Analysis 7.1.1 Stressors Vs Turnover Intention Table 7.1.1a Model Summary Std. Error of the Model R R Square Adjusted R Square Estimate 1 .739a .546 .534 .38228 a. Predictors: (Constant), work Exhaustion, Role Conflict, Role Ambiguity Table 7.1.1b Anova Model Sum of Squares Df Mean Square F Sig. Regression 18.994 3 6.331 43.322 .000a 1 Residual 15.783 108 .146 Total 34.777 111 a. Predictors: (Constant), work Exhaustion, Role Conflict, Role Ambiguity b. Dependent Variable: Turnover Intention Table 7.1.1c Coefficientsa Standardized Unstandardized Coefficients Model Coefficients t Sig. B Std. Error Beta (Constant) .618 .158 3.912 .000 Role Conflict .257 .051 .358 5.064 .000 1 Role Ambiguity .230 .051 .322 4.510 .000 work Exhaustion .254 .062 .304 4.120 .000 a. Dependent Variable: Turnover Intention Multiple correlation coefficient (R) = 0.739 indicates a good level of prediction. Coefficient of determination (R2) is the proportion of variance in the dependent variable that can be explained by the independent variables. R2 = 0 .546 shows that the independent variables Role conflict, role ambiguity and work exhaustion explain 54.6% of the variability of the dependent variable turnover intentions of the employees. The 3 independent variables statistically significantly predict the dependent variable, F(3, 95) = 43.322, p < .05. We can conclude that the regression model is a good fit of the data. Since p< 0.05, All independent variable coefficients are statistically significantly different from 0 (zero). 47
International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 6, Issue 4, April (2015), pp. 44-51© IAEME 7.1.2 Supervisor’s Feedback and Leader member exchange Vs Turnover Intention Table 7.1.2a Model Summary Std. Error of the Model R R Square Adjusted R Square Estimate 1 .764a .584 .576 .36445 a. Predictors: (Constant), Leader Member exchange, Supervisor's feed back Table 7.1.2b Anova Model Sum of Squares Df Mean Square F Sig. Regression 20.299 2 10.150 76.416 .000a 1 Residual 14.477 109 .133 Total 34.777 111 a. Predictors: (Constant), Leader Member exchange, Supervisor's feed back b. Dependent Variable: Turnover Intention Table 7.1.2 c Coefficientsa Standardized Unstandardized Coefficients Model Coefficients t Sig. B Std. Error Beta (Constant) .821 .127 6.461 .000 1 Supervisor's feed back .268 .042 .417 6.334 .000 Leader Member exchange .402 .052 .512 7.778 .000 a. Dependent Variable: Turnover Intention Multiple correlation coefficient (R) = 0.764 indicates a good level of prediction. R2=0 .584.It shows that the independent variables Supervisor’s Feedback and Leader member exchange explain 58.4% of the variability of the dependent variable turnover intentions of the employees. The 3 independent variables statistically significantly predict the dependent variable, F(2, 95) = 76.416, p < .05. We can conclude the regression model is a good fit of the data. Since p< 0.05, All independent variable coefficients are statistically significantly different from 0 (zero). 7.1.3 Compensation Vs Turnover Intentions: Table 7.1.3 a Model Summary Std. Error of the Model R R Square Adjusted R Square Estimate a 1 .775 .601 .590 .35827 a. Predictors: (Constant), Job security, Fairness of individual rewards, Promotion Satisfaction Table 7.1.3 b Anova Model Sum of Squares Df Mean Square F Sig. Regression 20.915 3 6.972 54.315 .000a 1 Residual 13.862 108 .128 Total 34.777 111 a. Predictors: (Constant), Job security, Fairness of individual rewards, Promotion Satisfaction b. Dependent Variable: Turnover Intention 48
International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 6, Issue 4, April (2015), pp. 44-51© IAEME Table 7.1.3 c Coefficientsa Standardized Unstandardized Coefficients Model Coefficients t Sig. B Std. Error Beta (Constant) .749 .154 4.868 .000 Promotion Satisfaction .342 .049 .528 6.951 .000 1 Fairness of individual .197 .056 .243 3.506 .001 rewards Job security .125 .048 .177 2.581 .011 a. Dependent Variable: Turnover Intention Multiple correlation coefficient (R) = 0.775 indicates a good level of prediction. R2=0 .601.It shows that the independent variables Promotion Satisfaction, Fairness of Individual Rewards and Job security explain 60.1% of the variability of the dependent variable turnover intentions of the employees. The 3 independent variables statistically significantly predict the dependent variable, F (3, 95) = 54.315, p < .05. We can conclude the regression model is a good fit of the data. Since p< 0.05, All independent variable coefficients are statistically significantly different from 0 (zero). 7.1.4 Accommodation Vs Turnover Intentions Table 7.1.4 a Model Summary Std. Error of the Model R R Square Adjusted R Square Estimate 1 .777a .603 .596 .35577 a. Predictors: (Constant), Work Schedule Flexibility, Career Accommodation Table 7.1.4 b Anova Model Sum of Squares Df Mean Square F Sig. Regression 20.981 2 10.490 82.883 .000a 1 Residual 13.796 109 .127 Total 34.777 111 a. Predictors: (Constant), Work Schedule Flexibility, Career Accommodation b. Dependent Variable: Turnover Intention Table 7.1.4 c Coefficientsa Standardized Unstandardized Coefficients Model Coefficients T Sig. B Std. Error Beta 1 (Constant) .807 .125 6.476 .000 Career Accommodation .292 .053 .436 5.522 .000 Work Schedule Flexibility .325 .061 .420 5.308 .000 a. Dependent Variable: Turnover Intention Multiple correlation coefficient (R) = 0.777 indicates a good level of prediction. R2=0 .603.It shows that the independent Work Schedule Flexibility and career accommodation explain 60.3% of the variability of the dependent variable turnover intentions of the employees. 49
International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online), Volume 6, Issue 4, April (2015), pp. 44-51© IAEME The 3 independent variables statistically significantly predict the dependent variable, F(2, 95) = 82.883, p < .05. We can conclude the regression model is a good fit of the data. Since p< 0.05, All independent variable coefficients are statistically significantly different from 0 (zero). 7.2 Bivariate Correlation Table 7.2.1 Turnover Intention Vs various components Components Pearson Correlation Sig. (2-tailed) N Role Conflict .560** .000 112 Role Ambiguity .541** .000 112 work Exhaustion .564** .000 112 Supervisor's feed back .594** .000 112 Leader Member exchange .656** .000 112 Promotion Satisfaction .728** .000 112 Fairness of individual rewards .540** .000 112 Job security .483** .000 112 Career Accommodation .708** .000 112 Work Schedule Flexibility .702** .000 112 The correlation between turnover intention and the various dimensions such as Role ambiguity, Role conflict, Work-exhaustion, Supervisor's feedback, Leader Member exchange, Promotion Satisfaction, Fairness of individual rewards, Job security, Career accommodation and Work Schedule Flexibility was .560, .541, .564, .594, .656, .728, .540, .483, .708, and .702 respectively and was significant at (.000) level of significance. 8. CONCLUSION This study attempted to measure the impact of stressors, supervisor relationship, compensation, and accommodation on turnover intention among IT professionals which is applicable to Indian sample. The findings of the research revealed the importance of stress related factors, supervisor’s relationship, compensation and accommodation on quitting the job among IT professional who work in leading IT organizations located at Chennai city, Tamilnadu, India which can be used as one of the retention tool in the organizations. REFERENCES 1. W. Mobley's (1977) “Intermediate linkages in the relationship between job satisfaction and employee turnover”, Journal of Applied Psychology, 62, 237-240 2. James L Price & Charless w Mueller (1981) “A casual model of Turnover for nurses” Academy of Management Journal, Vol 24, No.3 543-565, Sp. 3. Kuruuzum A Cetin E.I & Irmak S (2009) “Path analysis of organizational Commitment, job involvement and job satisfaction in the Turkish hospitality industry”, Tourism Review, , 64(1). 4. Firth, L., Mellor, D. J., Moore, K. A., & Loquet, C. (2004) “How can managers reduce employee intention to quit? Journal of Managerial Psychology”, 19(2), 170 -187 5. M Kannan and K Vivekanandan(2012) “A Study on Attrition among New Entrants in Software Testing Professionals” International Journal of Computer Applications 53(7):23-29, September 2012. 6. R.Sivarethinamohan and P.Aranganathan(2014), “ An Empirical Study on attrition intention among software professionals in Indian Information Technology organizations” Vol IV, Issue-VII July, 2014, 29-36 50
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