Open Access Open Access  Restricted Access Subscription Access

Use of Structural Equation Modeling to Empirically Study the Turnover Intentions of Information Technology Professionals in Pune City


Affiliations
1 Symbiosis International University, Symbiosis Centre for Information Technology, Pune, Maharashtra, India
2 Freelance Management Consultant, Chennai, Tamil Nadu, India
 

Organizations are still finding strategies to retain good workforce, and understand the turnover intentions of employees. Software companies in India are providing good salary packages, excellent performance based bonus and incentives, but all this does not prevent employees from quitting. This paper provides an indepth understanding on the effect of various factors like work–family life conflict, work stress, role ambiguity, job satisfaction and organizational commitment, on the turnover intentions of an IT employee. This study was carried out in Pune, Maharashtra. The study 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.

Keywords

Organizational Commitment, Job Satisfaction, Turnover Intentions, Work–Family Conflict, Work Stress, Role Ambiguity, Information Technology
User

  • Dowling W (1972). Conversation with David McClelland, Organisational Dynamics, vol 1(1), 56–72.
  • Latham G (2000). Motivat employee performance through goal–setting, In Locke E (Ed), HandBook of Principles of Organisational Behaviour, 2nd Edn., 107–119.
  • Orlikowski W J, and Baroudi J J (2002). Studying information technology in organisations: research approaches and assumptions, Information Systems Research, vol 2(1), 1–28.
  • Eucker T (2007). Understanding the impact of tacit knowledge loss, Management Review, vol 10(1), 10.
  • Kacmar K, Andrews M et al. (2006). Sure every one can be replaced...but at what cost? turnover as a predictor of unit–level performance, Academy of Management Journal, vol 49(1), 133–144.
  • Liu B, Liu J et al. (2010). Person–organisation fit, job satisfaction, and turnover intention: an empirical study in the chinese public sector, Social Behaviour and Personality: An International Journal, vol 38(5), 615–625.
  • Outlay C N, Pratt R M E et al. (2012). Team and organisational identificaiton among informational systems personnel: an exploratory investigation of post IT outsourcing personnel impacts, 4th Hawaii Interantinonal Conference on System Sciences, 5142–5151.
  • Cotton J, and Tuttle J (1986). Employee turnover: a meta–analysis and review with implications for research, Academy of Management Review, vol 11(1), 55–70.
  • Kamalanabhan S K (2010). A three dimensional analysis of turnover intentions among employees of ITES/BPO sector, South Asian Journal of Management, vol 17(3), 85–103.
  • Maertz C P, and Campion M A (1998). 25 years of voluntary turnover research: a review and critique, Cooper C L & Robertson I T (Eds.), International Review of Industrial and Organizational Psychology, Wiley, Chichester, England, vol 13(Annual Volume), 49–83.
  • Vikramasinghe V (2010). Imact of time demand of work on job satisfaction and turnover intention: software developers in offshore outsourced software development firms in Srilanka, Strategic Outsourcing: An International Journal, vol 3(3), 246–255.
  • Dogherty T W, Bluedom A C et al. (1985). Precursers of employee turnover: a multiple–sample causal analysis, Journal of Organizational Behaviour, vol 6(4), 257–271.
  • Mobley W H (1977). Intermediate linkages in the relationshsip between job satisfaction and employee turnover, Journal of Applied Psychology, vol 62(2), 237–240.
  • Tett R P, and John P M (1993). Job satisfaction, organiastional commitment, turnover intention and turnover: path analysis based on meta–analytic findings, Personal Psychology, vol 46(2), 259–293.
  • Moore J E, and Burke J E (2002). How to turn around turnover culture in IT, Communications of the ACM, vol 45(2), 73–78.
  • Griffith R W, Hom P W et al. (2000). A meta–analysis of antecedents and correlates of employee turnover: update, moderator tests, and research implications for the next millennium, Journal of Management, vol 26(3), 463–448.
  • Igbaria M, and Greenhaus J H (1992). Determinants of MIS employees’ turnover intentions: a structural equation model, Communications of the ACM, vol 26(3), 34–46.
  • Igbaria M, and Guimares T (1999). Exploring differences in employee turnover intentions and its determinants among telecommuters and non–telecommuters, Journal of Management Information System, vol 16(1), 147–164.
  • Steel R P (2002). Turnover theory at the empirical interface: problems of fit and function, Academy of Management Review, vol 27(3), 346–360.
  • Igbaria M, Meredith G et al. (1994). Predictors of intention of IS professionals to stay with the organization in South Africa, Information & Management, vol 26(5), 245–256.
  • Mathiee J E, and Zajac D M (1990). A review and meta–analysis of the antecedents, correlates, and consequences of organizational commitmen, Psychological Bulletin, vol 108(2), 171–194.
  • Hendrix W H, Robertson T et al. (1999). Effects of procedural and distributive justice on factors predictive of turnover, Journal of Social Behavior and Personality, vol 13(4), 611–632.
  • Smith M, and Brough P (2003). Personal recruitment and selection, In O’Driscoll M T (Ed.), Organisational Psychology in Australia and New Zealand, 31–35.
  • Kahn R L, Wolfe D M et al. (1964). Organizational stress: studies in role conflict and ambiguity, review by: Harry Levinson, Administrative Science Quarterly, vol 10(1), Special Issue on Professionals in Organizations (Jun., 1965), 125–129. http://www.jstor.org/stable/pdfplus/2391654.pdfacceptTC=true&acceptTC=true&jpdConfirm=true
  • Greenhaus J H, and Beutell N J (1985). Sources of conflict between work and family roles, Academy of Management Review, vol 10(1), 76–88.
  • Cooper C L, Spector P E et al. (2004). A cross national comparative study of work family stressors, working hours, and well–being: China and Latin America versus the Anglo world, Personal Psychology, vol 57(1), 119–142.
  • Frone M, Russell M et al. (1997). Relation of work–family conflict to health outcomes: a four–year longitudinal study of employed parents, Journal of Occupational and Organizational Psychology, vol 70(4), 325–335.
  • Ruderman M N, Ohlot P J et al. (2002). Benefits of multiple roles for managerial women, Academy of Management Journal, vol 45(2), 369–386.
  • Foley S, Ngo H–Y et al. (2005). The effects of work stressors, perceived organizational support, and gender on work–family conflict in Hong Kong, Asia Pacific Journal of Management, vol 22(3), 237–256.
  • Netmeyer R G, Boles J S et al. (1996). Development and validation of work–family conflict and family–work conflict scales, Journal of Applied Psychology, vol 81(4), 400–410.
  • Frone M R (2003). Work–family balance. Available from psycnet.apa.org
  • Ahuja M K, Chudoba K et al. (2007). IT road warriors: balancing work family conflict, job autonomy, and work overload to mitigate turnover intentions, MIS Quarterly, vol 31(1), 1–17.
  • Moore J E (2000). One road to turnover: an examination of work exhaustion in technology professionals, Management Information Systems Quarterly, vol 24(1), 141–168.
  • Chan K B, Lai G et al. (2000). Work stress among six professional groups: the Singapore experience, Social Science and Medicine, vol 50(10), 1415–1432.
  • Carayon P, Smith M J et al. (1999). Work organization, job stress, and work–related musculoskeletal disorders, Human Factors, vol 41(4), 644–663.
  • Amstrong D J, Reimenschneider C K et al. (2007). Advancement, voluntary turnover and women in IT: a cognitive study of work family conflict, Information and Management Journal, vol 44(2), 142–153.
  • MacDonald W (2003). The impact of job demands and workload on stress and fatigue, Australian Psychologist, vol 38(2), 102–117.
  • Smith M, and Bourke S (1992). Teacher stress: examining a model based on context, workload, and satisfaction, Teaching and Teacher Education, vol 8(1), 31–46.
  • Sethi V, Barrier T et al. (2004). An examination of the correlates of burnout in information system professionals, Information Resources Management Journal, vol 12(3), 5–13.
  • Kim S E (2007). Is mission attachment an effective management tool for employee retention? an empirical analysis of a nonprofit human services agency, Review of Public Personnel Administration, vol 27(3), 227–248.
  • Rizzo J R, House R J et al. (1970). Role conflict and ambiguity in complex organizations, Administrative Science Quarterly, vol 15(2), 150–163.
  • Ivancevich J M, Matteson M T et al. (1990). Worksite stress management interventions, American Psychologist, vol 45(2), 252–261.
  • Jackson S E, and Schuler R S (1985). A meta–analysis and conceptual critique of research on role ambiguity and role conflict in work settings, Organizational Behavior and Human Decision Processes, vol 36(1), 16–78.
  • Bedeian A G, and Armenakis A A (1981). A path–analytic study of the consequences of role conflict and ambiguity, Academy of Management Journal, vol 24(2), 417–424.
  • Dunham R B, Grube J A et al. (1994). Organizational commitment: the utility of an integrative definition, Journal of Applied Psychology, vol 79(3), 370–380.
  • Iverson R D, and Buttigeig D M (1999). Affective, normative and continuance commitment: can the right kind of commitment be managed?, Journal of Management Studies, vol 36(3), 307–333.
  • Brunetto Y, Farrharton R et al. (2012). Supervisor relationships, teamwork, role ambiguity and discretionary power: nurses in Australia and the United Kingdom, International Journal of Public Administration, vol 35(8), 532–543.
  • Hoppock R (1935). Job Satisfaction, Harper, New York.
  • Zhou Z, and Chunfeng C (2009). Structural empowerment, job satisfaction, and turnover intention of chinese clinical nurses, Nursing & Health Sciences, vol 11(4), 397–403.
  • Locke E (1976). The nature and causes of job satisfaction, In Dunette M D (Ed.), Handbook of Industrial and Organizational Psychology, Rand McNally, Chicago, 1297–1343.
  • Greenberg J, and Baron R A (1997). Work related attitudes: feelings about jobs, organisation and people, Behavior in Organizations: Understanding and Managing the Human Side of Work, 5th Edn., Chapter 5, Prentice Hall, Upper Saddle River, NJ, Carsten.
  • Porter L, and Steers R (1973). Organisational, work and personal factors in employee turnover and absenteesim, Psychological Bullettin, vol 80(2), 151–176.
  • Carsten J, and Spector P (1987). Unemployement, jobsatisfaction and employee turnover: a meta–analytic test of the muchinsky model, Journal of Applied Psychology, vol 72(3), 374–381.
  • Spector E (1996). Feelings about work: job attitudes and emotions, Industrial and Organizational Psychology Research and Practice, Chapter 9, John Wiley and Sons Inc, USA, 222–251.
  • Amah O E (2009). Job satisfaction and turnover intention relationship: the moderating effect of job role centrality and life satisfaction, Research and Practice in Human Resource Management, vol 17(1), 24–35.
  • Lacity C M, Iyer V et al. (2008). Turnover intentions of Indian IS professionals, Information System Front, vol 10(2), 225–241.
  • Paille P, and Grima F (2011). Citizenship and withdrawal in the workplace: relationship between organizational citizenship behaviour, intention to leave current job and intention to leave the organization, The Journal of Social Psychology, vol 15(1), 478–493.
  • Bhatnagar J (2007). Talent management strategy of employee engagement in Indian ITES employees: key to retention, Employee Relations, vol 29(6), 640–663.
  • Meyer J P, Allen N J et al. (1993). Commitment to organisations and occupations extension and test of a three–component conceptualization, Journal of Applied Psychology, vol 78(4), 538–552.
  • Mowday R T, Porter L W et al. (1982). Employee–organization linkages: the psychology of commitment, absenteeism, and turnover, Review by: Stanley E, Seashore American Journal of Sociology, vol 88(6) (May, 1983), 1315–1317. http://www.jstor.org/stable/pdfplus/2778990.pdf?&acceptTC=true&jpdConfirm=true
  • Meyer J P, and Allen N J (1997). Meaning of commitment, Commitment in the Workplace: Theory, Research and Application, Chapter 2, Sage, Thousand Oaks, CA, 8–22.
  • Lee–Kelly L, Blackman D A et al. (2007). An exploration of the relationship between learning organizations and the retention of knowledge workers, The Learning Organization, vol 14(3), 204–221.
  • Silverthrone C (2005). Organisational and national culture, Organisational Psychology in Cross Cultural Perspective, Chapter 4, NYU Press, New York, 41–56.
  • Aydogdu S, and Asikgil B (2011). An empirical study of the relationship among job satisfaction, organisational commitment and turnover intention, International Review of Management and Marketing, vol 1(3), 43–53.
  • Foon Y, Leong L et al. (2010). An exploratory on turnover intention among private sector employees, International Journal of Business and Management, vol 5(8), 57–64.
  • Baroudi J J (1985). The impact of role variables on information systems personnel work attitudes and intentions, MIS Quarterly, vol 9(4), 341–356.
  • Grandey A A, and Cropenzano R (1999). The conservation of resources model applied to work–family conflict and strain, Journal of Vocational Behaviour, vol 54(2), 350–370.
  • Lee K, Carswell J et al. (2000). A meta–analytic review of occupational commitment: relation with person-and work related variables, Journal of Applied Psychology, vol 85(5), 799–811.
  • Mathis R L, and Jackson J H (2004). Talent management, Human Resource Management, Chapter 9, Thompson South Western, Australia, 290–323.
  • Dixon A L, Susan M et al. (2003). Attributions and behavioural ntentions of inexperienced sales persons to failure: an empirical investigation, Journal of the Academy of Marketing Science, vol 31(4), 459–467.
  • Kumar V (2000). Multivariate analysis, International Marketing Research, Chapter 15, Prentice–Hall Inc, Upper Saddle River NJ.
  • Singh J (1995). Measurement issues in cross–national research, Journal of International Business Studies, vol 26(3), 597–619.
  • George D, and Mallery P (2003). Reliability test, SPSS for Windows step by step: A Simple Guide and Reference, 4th Edn., Chapter 18, Allyn & Bacon, Boston, 52–56.
  • Anderson T M, and Herbertson T T (2003). Measuring Globalization, IZA Discussion Paper (817) Available from: http://ssrn.com/abstract=434540
  • Kaiser F G (1974). An index of factoral simplicity, Psychometrika, vol 39(1), 31–36.
  • Marjorie P A, Lackey N R et al. (2003). An overview of factor analysis, Making Sense of Factor Analysis: the use of Factor Analysis for Instrument Development in Health Care Research, Chapter 5, Sage Publication, Inc, Thousand Oaks, CA, 131–164.
  • Field A (2005). Discovering Statistics using SPSS for Windows: Advanced Techniques for Beginners, Introducing Statistical Methods Series, 2nd Edition, Chapter 15, Sage, 619–675.
  • Carmines G, McIver E G et al. (1981). Analyzing models with unobserved variables: analysis of covariance struc-tures, In Bonstedt W G, and Borgatta F E (Eds), Social Measurement: Current Issues, 65–115.
  • Marsh H W, and Hocewar D (1985). Application of confirmatory factor analysis to the study of self concept: first and higher order factor models and their invariance across groups, Psychology Bulletin, vol 97(3), 562–582.
  • Byrne B M (1994). Application 6, Structural Equation Modeling with EQS and EQS/Window: Basic concepts, applications and programming, Chapter 8, Sage, 159–176.
  • Straub D W (1989). Validating instruments in MIS research, MIS Quarterly, vol 13(2), 147–169.
  • Bentler P M, and Bonnet D G (1980). Significance tests and goodness of fit in the analysis of convenience structure, Psychological Bulletin, vol 88(3), 588–606.
  • Marsh H W, Hau K T et al. (1988). Is more ever too much? the number of indicatiors per factor in confirmatiory factor analysis, Multivativariate Behavioural Research, vol 33(2), 181–220.
  • Browne M, and Cudeck R (1993). Alternative ways of assessing model fit, In Bollen K A, and Long J S (Eds), Testing Structural Equation Models, 136–162.
  • Bentler P (1990). Comparative fit indexes in structural models, Psychological Bulletin, vol 107(2), 238–246.

Abstract Views: 544

PDF Views: 0




  • Use of Structural Equation Modeling to Empirically Study the Turnover Intentions of Information Technology Professionals in Pune City

Abstract Views: 544  |  PDF Views: 0

Authors

R. Raman
Symbiosis International University, Symbiosis Centre for Information Technology, Pune, Maharashtra, India
S. Vijayakumar Bharathi
Symbiosis International University, Symbiosis Centre for Information Technology, Pune, Maharashtra, India
V. Sesha
Freelance Management Consultant, Chennai, Tamil Nadu, India
Shaji Joseph
Symbiosis International University, Symbiosis Centre for Information Technology, Pune, Maharashtra, India

Abstract


Organizations are still finding strategies to retain good workforce, and understand the turnover intentions of employees. Software companies in India are providing good salary packages, excellent performance based bonus and incentives, but all this does not prevent employees from quitting. This paper provides an indepth understanding on the effect of various factors like work–family life conflict, work stress, role ambiguity, job satisfaction and organizational commitment, on the turnover intentions of an IT employee. This study was carried out in Pune, Maharashtra. The study 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.

Keywords


Organizational Commitment, Job Satisfaction, Turnover Intentions, Work–Family Conflict, Work Stress, Role Ambiguity, Information Technology

References





DOI: https://doi.org/10.17485/ijst%2F2013%2Fv6i12%2F43627