A Revisit on Impact of Job attitudes on Employee Turnover: An Empirical Study in
Indian IT Industry
Dr. Niharika Gaan1
This study reexamines the relationship between the job satisfaction, organizational
commitment and turnover empirically with sample size of 308 information system
professionals from giant companies of Indian software and BPO sectors. It views
turnover from attitudinal perspective. Results reveal that the relationship between
organizational commitment and turnover is inconsistent with the earlier literature.
However, job satisfaction seems to be explaining significant amount of incremental
variance in turnover intention. Further, it is suggested for future study that the
turnover model should try to investigate the precursors to turnover intention by
taking occupational commitment, job satisfaction and non-attitudinal aspects of it as
Key words: Employee turnover, Organizational commitment, Job satisfaction,
Information system professionals
Turnover has been a major issue pertaining to IT personnel since the very early days of
computing and continuing to the present. It has been noted frequently that IT personnel
have a stronger than average tendency to leave a current employer to work for another
organization. Therefore, high turnover is a general trend found especially in IT industry
1. Dr. Niharika Gaan is working as an Assistant Professor in Center for Management studies, which is
affiliated to Biju Pattnaik University of Technology.
which has also been subject of considerable research. It is so because turnover of highly
skilled employees can be very expensive and disruptive for firms (Reichheld, 1996).
Losing highly skilled staff members may incur substantial costs associated with
recruiting, re-skilling, and hidden costs associated with difficulties completing projects
and disruptions in team-based work environments. Information technology (IT) personnel
exemplify highly skilled professionals and called as knowledge worker (Reed, 1996;
Frenkel & Korezgynski, 2002).
India’s abundant, high quality and cost effective services and its vast resource of skilled
software human power have made it an attractive location for global software clients.
There has been a steady growth in the number of India’s IT professionals over the last
decade. From a base of 6,800 knowledge workers in 1985-86, the number increased to
522,000 software and services professionals by the end of 2001-02. It is estimated that
out of these 522,000 knowledge workers, almost 170,000 are working in the IT software
and services export industry; nearly 106,000 are working in the IT enabled services and
over 220,000 in user organizations. According to NASSCOM-McKinsey Report 2005 the
offshore IT and BPO industries directly employ around 700,000 professionals and
provide indirect employment to approximately 2.5 million workers. With the steady gains
of females at both software companies prompting NASSCOM to believe that women’s
involvement in IT services will climb a further 10% per cent by 2007.
The critical issue is also revolving around procuring an adequate pool of well trained
applicants from which to hire new employees from. Yet, while the number of qualified
employees is dwindling, there is an increasing need to retain well-trained employees and
to lower search, hire, training and general turnover costs, to boost employee loyalty and
morale, and to maintain a highly productive and creative workforce.
Thus objective of the study is to reconsider the employee turnover model from
psychological perspectives. This is investigated by examining the relationship between
the job satisfaction, organizational commitment and turnover intention. It also tries to
redefine the relationship between the job satisfaction, organizational commitment and
turnover intention. This is examined by finding the mediating effect of organizational
commitment on the relationship between the job satisfaction and turnover intention.
2.0 Background and hypotheses:
Researchers have extensively studied precursors to employee turnover in an effort to
develop understanding of the attitudes that stimulate employees to leave employment
with a specific organization. In an attempt to clarify the relationships among various
attitudinal antecedents of turnover, Tett and Meyer (1993) performed meta-analysis on
178 independent samples from 135 studies. They estimated the relationships among job
satisfaction, organizational commitment, turnover intention, and actual turnover (Tett and
Meyer, 1993). Their examination concluded that job satisfaction and organizational
commitment each contribute independently to the prediction of intention to turnover, and
that such intentions are predicted more strongly by job satisfaction than by organizational
commitment. Lee, Mitchell, Holtom, McDaniel, and Hill (1999) argue strongly that
attitudinal findings alone are not sufficient to explain the full range of issues involved
with turnover. Lee and Mitchell (1994) go so far as to state: .In short, over 17 years of
research on the traditional turnover models suggests that many employees may leave
organizations in ways not specified by traditional models.. Supporting this position, Hom,
Caranikas-Walker, Prussia, and Griffeth (1992) found in a meta-analysis of turnover
studies that the effects of precursors to turnover, such as job satisfaction, are moderated
by external economic issues, such as employment rates. While existing theory generally
ties turnover to low job satisfaction, Lee et al. (1999) argues that new theories are needed
to explain the varied conditions under which people leave organizations.
Jiang and Klein (1999), for example, report a 25- 35% turnover rate for IT employees in
Fortune 500 firms. Moreover, a series of studies of the key issues facing senior IT
practitioners have consistently listed human resource management as a leading key issue
(e.g. Niederman, Brancheau, and Wetherbe, 1991). Prior research on turnover among IT
employees has focused on attitudes leading to intent to turnover with much the same
findings as those reported by Tett and Meyer (1993) (e.g. Guimaraes and Igbaria, 1992;
Igbaria, and Baroudi, 1995; Igbaria, Greenhaus, and Parasuraman, 1991; Igbaria, and
Guimaraes, 1999; Igbaria, Parasuraman, and Badawy, 1994; and Igbaria, and Wormley,
From this psychological perspective, intent to turnover is a result of individual factors
such as employee demography, job dissatisfaction, or lack of organizational commitment
(e.g., Ryan, 1989; Discenza & Gardner, 1992; Igbaria & Siegel, 1992; Igbaria &
Greenhaus, 1992; Igbaria, Meredith, & Smith, 1994; Joseph & Ang, 2003). This research
has provided valuable insights into why IT professionals intend to leave their jobs.
However, it does not explain actual turnover patterns. Longitudinal studies of turnover in
non-IT contexts (Farkas & Tetrick, 1989; Johnston et al., 1993; Kirschenbaum &
Weisberg, 1990; Vandenberg & Nelson, 1999) suggest that intent to turnover does not
always predict actual turnover behavior. Recent research in psychology and
organizational behavior implies that actual turnover is strongly influenced by internal
labor market attributes such as promotability, wage levels, skills demand, and external
labor market attributes such as mobility, and availability of jobs (Hom & Kinicki, 2001;
Trevor, 2001; Kirschenbaum & Mano- Negrin, 1999).
Retaining information technology (IT) professionals is important for organizations, given
the challenges in sourcing for IT talent. Prior research has largely focused on
understanding employee turnover from an intra-individual perspective. In the “Turnover
of information technology professionals: the effects of internal labor market strategies”
by Slaughter and Ang (2004) study, the researchers have examined employee turnover
from a structural perspective. They investigate the impact of Internal Labor Market
(ILM) strategies IT turnover of organizations. ILM strategies include human resource
rules, practices, and policies including hiring an employee.
The research study on “Job turnover among MIS professionals: an exploratory study of
employee turnover” by Neiderman and Summer (2001) addresses the issue of IT worker
turnover. It reports on a survey IT workers who graduated over the past decade (1990-
1999) from Saint Louis University. Research questions target IT worker demographics,
such as age and gender and Job satisfaction, salary, job tasks, and opportunity factors for
both prior and current employment. Results included ranking of different factors
comprising Job satisfaction (satisfaction with financial compensation was high and with
fringe benefits was low).
Further there is another research study where they have identified a multidimensional set
of HR practices likely to increase retention among IT employees and considered
citizenship behaviors as well as two distinct types of organizational commitment as key
antecedents of turnover intentions. Thus the authors Pare, Tremblay, and Lalonde (2001)
in their research study “Workforce retention: what do IT employees really want?” have
presented and tested an integrated model of turnover intentions that addresses the unique
nature of the IT profession.
This study “IT Retention: The social context of turnover among information technology
professionals Lee (2002)” focuses on the role played by social support from supervisors
and colleagues in helping to minimize turnover intentions among computer professionals.
Although the concept of social support has been widely used in the occupational stress
literature, it has rarely been applied in turnover research. This study explains why social
support is particularly salient to computer professionals' turnover. It develops a model
that posits that (i) social support is positively related to job satisfaction and negatively
related to turnover intention.
Career plateau is a popular construct that has been associated with a number of work
outcomes. This study introduced a related construct called professional plateau. It is
defined as the point where employees find their job unchallenging and it provides few
opportunities for professional development and future employability. The research study
by Lee (2002) “Career plateau and professional plateau: impact on work outcomes of
information technology professionals” have proposed that career plateau and professional
plateau are related to three work outcomes: namely, career satisfaction, Job satisfaction,
and turnover intentions.
The aforementioned literature survey provides a complete picture of turnover intention
being studied from diverse perspective: psychological perspectives, intra-individual
perspectives and structural perspectives. Due to scanty availability of research on
employee turnover in Indian context, buzzing and growing issue of turnover in Indian IT
organizations, this study makes an attempt to reconsider employee turnover from
attitudinal perspectives. Thus looking at the background the hypothesis framed are as
H1: Job satisfaction is positively related to organizational commitment.
H2: Job satisfaction is negatively related to turnover intention.
H3: Organizational commitment will be negatively related to turnover intention. In other
words organizational commitment mediates the relationship between job satisfaction and
A pilot study was undertaken in local IT companies in Ahmedabad before undertaking
the final survey. The purpose to undertake pilot study was to understand the set up both
holistically and to collect preliminary data about the Software and BPO organizations. An
open-ended interview was taken to find out the effect of attitudinal aspects of job
satisfaction on turnover intention. The open-ended questionnaire contained eight
questions which involve all the three variables and their effect on each other. About 25
interviews were conducted in four IT companies of Ahmedabad to confirm the objectives
of the study.
After undertaking pilot study, the final survey was decided and the author immediately
went to places which were considered to be hub of It industry. Bangalore is considered to
be the Silicon Valley of India and home of the corporate giants in IT namely, Infosys,
Wipro, Satyam, IBM, Compaq and so on. So to get an easy access to different IT
companies and captures the sample size of 300 respondents, it was advised to choose
Bangalore for the field study. Out of 308 sample size of IS professionals, data of 68 in
number was collected from IT division of BPO companies. The rest 240 respondents
were covered in software companies and categorically 60 respondents from each group of
professionals like programmers, system analysts, test engineers, and system
administrator. Thus sample represented wide range of roles performed by information
system professionals and also involved diversity in terms of gender and educational
The initial stage of data collection involved briefing about the study to Vice President
(HR) and also its impacts on the respondents and organization in terms of benefits. This
was the prerequisites to get access to the organization they belong to. These authorized
persons were either personally approached or requested through mail.
After getting permission from the Vice President (HR) of the companies like Satyam,
Wipro, Honeywell, and Seimens, the survey was conducted with the help of
questionnaire accompanied by the covering letter carrying the explanation of the purpose
of the study. The structured questionnaire was used for survey purpose, which was
running for 2 pages, consisting of items measuring job satisfaction, organizational
commitment and turnover intention. The respondents were assured the confidentiality of
information. Towards the end of the April 2004, the questionnaires were distributed in all
software companies. The questionnaires were returned on an average after 6 weeks of the
administration. Some of the respondents had returned the filled questionnaire within four
days or a week. The total number of usable questionnaires received was 69, 55, 54, and
62 from Wipro Technology, Seimens, Satyam and Honeywell, respectively. Two hundred
and forty usable questionnaires were returned out of 458 respondents approached from
software companies, representing a return rate of 52.4%. Similarly the response rate in
BPO was much higher. The total number of questionnaires returned was 17, 21, 15 and
15 from Wipro Spectramind, Daksh, Exl services and Nipuna services, respectively. Out
of 90 respondent approached, 68 usable questionnaires were returned in BPO companies
representing a return rate of 75.6%. Demographic characteristics like age, gender, total
experience, experience with the current organization, education and finally designation
was gathered along with the questionnaire. The full time employers with a tenure
experience of 2 years and more than that were considered. The descriptive statistics on
frequency and percentage of sex by different groups has been depicted in the Table 1 and
2 respectably. The returned responses 68 in number from BPO represent BPO IT
professionals. Out of 240 respondents 62 are females and rest 178 respondents are males
in software sector. Similarly, 11 females respondents from BPO IT professionals had
returned the filled questionnaire and rest 57 were males. The trainees and those who were
holding post above project manager in hierarchy were excluded from the present study as
they do more of generalist role than the specialist role like programming, analyst, test
engineer or system administrator job. The average age of the respondents after
calculation showed 27 years and 4 months carrying standard deviation 2.3713. About
38.6% of IS professionals are carrying educational background of B.E in computer
science. Majority of them have been in this occupation for 3 to 4 years. The distribution
in terms of company tenure is slightly skewed towards employees serving for 2-3 years.
The percentage of such employees has come out to be 87% having standard deviation of
Table 1: Frequency and Percentage of Sex by Different Groups (N=308)
Total Male 246 79.87
Female 62 20.13
Software Male (Software) 189 78.75
Female (Software) 51 21.25
BPO Male (BPO) 57 83.8
Female (BPO) 11 16.2
Total 308 100
The established scales for all the variables were taken for the present study. The
Cronbanch Alpha reliability measures were computed to test their internal consistency.
The internal consistency reliability has been evaluated by computing the Cronbach’s
alpha coefficients for each scale which has been shown in Table 5.
Job satisfaction: Overall job satisfaction was measured using items drawn from Job
satisfaction Survey developed by Specter (facet- specific level job satisfaction, 1997).
The reliability and validity of the scales as demonstrated by Spector (1985) ranges from
.60 to .91. Cronbach’s alpha of the scale in this study is .87. Different items were
measured using a 5-point Likert type scale.
Organizational Commitment: There were four items to measure the above variable and
were taken from the scales developed by Mowday & Porter (1982) showing reliability of
.82. Cronbach’s alpha of the scale in this study is.70. Items were measured using a 5-
point Likert type scale.
Turnover intention: This was measured by 3 items developed by Thatcher (2002)
showing .99 reliability. Cronbach’s alpha of the scale in this study is.86. Items were
measured using a 5-point Likert type scale.
The Cronbach’s alpha ranges from .63 onwards indicating that each measure
demonstrated acceptable internal consistency.
Table 2: Cronbach’s Alpha Reliability Coefficients
for Different Scales (N=308)
Sl.No Variables No. of Cronbanch
1 Organizational Commitment 4 .70
2 Turnover Intention 3 .86
3 Job Satisfaction 36 .87
4.0 Data analysis
The author tested the hypotheses using regression analysis and Baron and Kenny’s (1986)
procedures for testing mediation. According to Baron and Kenny, to demonstrate
mediation, it was first necessary to show that the independent variable is related to both
the proposed mediator and dependent variable. Next, a link between the proposed
mediator and dependent variable must be established. Finally, the effect of the
independent variable on the dependent variable must be shown to be eliminated or
significantly reduced after controlling the potential mediator.
Table 3 presents the means, standard deviations, zero-order correlations, and reliability
coefficients (Cronbach α) of the study variables. Respondents reported a mean level of
job satisfaction of ( 3.2 ) and a mean intention to quit score of ( 2.7 ) (3 is the midpoint
on the 5 point scale used).
As expected, organizational commitment was negatively and significantly related to
intention to quit (r = - .35 ; p < .000 ). Job satisfaction is positively and significantly
related to Organizational commitment ( r= .42 ; p<. 000) and negatively and significantly
related to turnover intention (r= -.52; p<.000 ). Recall that Baron and Kenny’s (1986)
procedures for demonstrating mediation require first showing that the independent
variable be related to both the proposed mediator and dependent variable. Therefore
further analyses were conducted by adopting Baron and Kenny’s procedures of
Table3: Descriptive statistics, reliabilities and intercorrelations for study variables
Variable Mean SD 1 2 3
1 Job Satisfaction 3.20 4.19 (.87 )
2 Organizational Commitment 3..88 2.68 .42** (.70 )
3 Turnover Intention 2..70 3.51 - .52** -.35 * (.86 )
Notes: N=308, α reliabilities for multiple measure are in parentheses, p< .001-.005
H1 predicted a positive relationship between job satisfaction and organizational
commitment, H2 predicted a negative relationship between organizational commitment
and turnover intention and H3 predicted that organizational commitment mediates the
relationship between job satisfaction and turnover intention. Applying the procedures
outlined by Baron and Kenny (1986), organizational commitment was regressed on job
satisfaction variable. As depicted by Table 4 the results indicated that this variable
significantly and positively predicted organizational commitment, β= .42, t (308)= 8.13,
p<.01. Job Satisfaction is predicting 18% of the variance in Organizational Commitment
as indicated in Table2. It also presents that job satisfaction is positively and significantly
related to organizational commitment. Therefore, H1 was accepted. Next with the use of
Hierarchical regression, turnover intention was regressed first on job satisfaction
followed by organizational commitment. The results indicated in Table5 shows that a
significant and negative relationship between job satisfaction and turnover intention, β= .-
.52, t (308)=-8.55 , p< .001, thereby supporting H2. Organizational commitment was
found to explain only 11% of variance in turnover intention which is less than explained
by Job satisfaction. Finally to test mediation turnover intention was regressed on
organizational commitment followed by job satisfaction. The results as indicated in Table
3 show that when the organizational commitment was partialled out the effect of job
satisfaction on turnover intention was significant. Job satisfaction was found to explain a
significant amount of incremental variance in turnover intention. Thus organizational
commitment cannot be said to mediate the relationship between job satisfaction and
turnover intention, thereby resulting in rejection of H3.
Table4: Results of Regression Analysis of Organizational Commitment on Job
Variable R2 R2 change t β
Job Satisfaction .18 8.13** .42
Note: * *p< 0.01
Table5: Results of regression analysis on Intention to Quit (N=308)
Variable R2 R2 change t β
Effect of Job satisfaction before partialling out Organizational commitment
Step1: Job Satisfaction .27 -8.55** -.52
Step2: Organizational Commitment .11 -.16 -3.13* -.31
Effect of job satisfaction after partialling out organizational commitment
Step 1: Organizational Commitment .10 -6.70* -.16
Step2: Job Satisfaction .30 .20 -8.55** -.45
Note: * *p< 0.01, *p< 0.02
5.0 Discussion on the findings:
Job Satisfaction and Organizational Commitment:
The findings of the present study show that Job satisfaction is positively related to
organizational commitment, it confirms the established findings (Baroudi, 1985; Bartol,
1983; Dougherty, et.al., 1985; Michaeles & Spector, 1982; Griffeth, et. al., 2000; Lee, et.
al. 2000; Joseph and Ang, 2003). Organizational commitment is commonly viewed as
intervening variables in the turnover process (e.g., Hom & Griffeth, 1995; Mowday et al.,
1982; Price & Mueller, 1986). Those two variables are viewed as an essential component
of turnover models because their empirical relationship with voluntary turnover has been
firmly established through numerous meta-analyses (e.g., Cohen, 1993; Cohen &
Hudecek, 1993; Cotton & Tuttle, 1986; Hom & Griffeth, 1995; Hom, Caranikas-Walker,
Prussia, & Griffeth, 1992; Steel & Ovalle, 1984; Tett & Meyer, 1993).
Organizational Commitment and Turnover Intention:
This study attempted to examine the effects of job satisfaction on organizational
commitment and turnover intention. Further it also investigated the former empirical
study which advocated that the relationship between job satisfaction and intention to quit
is mediated by Organizational commitment. Consistent with the expectations the results
of the study show that organizational commitment is inversely related to the Intention to
leave. The findings confirm the earlier studies (Baroudi, 1985; Bartol, 1983; Dougherty,
et.al., 1985; Michaeles & Spector, 1982; Griffeth, et. al., 2000; Lee, et. al. 2000; Joseph
and Ang, 2003). But the power of explaining the turnover intention in this study is less
that of job satisfaction. The underlying thesis posits that organizational commitment
impact on turnover intention is conspicuously missing out from IT turnover research. The
impetus provided by organizational commitment for IT professionals to leave the
organization has diminished and it is very closely related to the findings of Joseph and
Ang ( 2003). On the contrary, the weak relationship between Job satisfaction and
Turnover intention in the earlier research is not supported in these findings. The pattern,
which emerges from these particular findings, states implicitly that Organizational
commitment is mediating the relationship between the job satisfaction and turnover
intention. The results probably would have been different if all three dimensions
(affective, continuance and normative components), as discovered by Meyers and Allen
(1990), were considered to measure the organizational commitment and its impact on the
organization. Probably Job satisfaction is the intervening variable between organizational
commitment and turnover intention. Researchers often propose Job satisfaction and
organizational commitment as intervening variables between other determinants (e.g.,
structural and individual variables) and outcomes like stay intentions and employee
turnover (Iverson, 1992; Mueller et al., 1992; Price & Mueller, 1986a). A substantial
body of empirical evidence links greater commitment to greater intent to stay and,
consequently, lower turnover (DeCotiis & Summers, 1987; Hom & Griffeth, 1995;
Kalleberg, 1987; Lee et al., 1992; Lincoln & Kalleberg, 1996; Mathieu & Zajac, 1990;
Mowday et al., 1982; Mueller et al., 1992; Price & Mueller, 1986a; Randall, 1990;
Somers, 1995). Fewer studies support a direct link between Job satisfaction and turnover
(Mueller et al., 1994), yet several support an indirect influence through commitment
(Lincoln & Kalleberg, 1985, 1990; Mowday et al., 1982; Mueller et al., 1994; Price &
Mueller, 1986a; Wallace, 1995). This particular study has been able to produce a direct
link between Job satisfaction and turnover intention and confirming some earlier studies (
Agarwal & Ferrat, 1999, Gomolski, 2000; Schwochau et al., 1997; Tsui et. al., 1995).
Probably the concept of the organizational commitment is less relevant to Indian IT
industry. The findings support and confirm the earlier studies on knowledge worker by
Reed (1996) and Frenkel &Korezgynski (2002). They stated that as organizations when
move towards adopting flat structure neither employees nor management expect long-
term relationship. So it depends upon the marketability of knowledge worker on skill and
knowledge in the external labour market. Secondly the occupational commitment is more
important to knowledge worker than the organizational commitment (Reed, 1996;
Frenkel & Korezgynski, 2002). Therefore, the management should try to satisfy them by
keeping up their job expectations.
6.0 Limitation of the study:
The data collection was restricted to a major city and two cosmopolitan cities in India
where talent is abundant. The replication of the study at different geographical locations
and culture would throw a light on this study. The sample drawn for the present study
consisted of 308 IS professionals working in various Software and ITES throughout India
cannot generalize the results. Hence, the research involving additional samples may be
needed to ensure appropriate generalization of the results and calls for greater research to
confirm the pattern seen in these results. The firm size should be controlled here so that
the results represent a certain class of firm of specific size. Though the organizations
were larger in size the findings cannot be generalized to medium and small size
organizations. Most of the successful large size organizations are either foreign or Indian
based multinational companies. The work culture generally differs depending upon the
type of IT industry: Indian based or foreign based multinational companies. The study
should be careful while making selection of either of the multinational companies for
data collection. This study has not taken this specific issue while collecting data.
7.0 Future research:
The greatest contribution of the present study to the theoretical world has come from the
explanatory power of job satisfaction towards turnover intention as observed from the
findings. The correlation between the job satisfaction and turnover intention is higher
than the correlation between the organizational commitment and turnover intention. It is
suggested that occupational preferences tap the rationalized outcome of the individual
decision making (Long et al, 1988). Understanding how occupational preferences affect
turnover decisions will clarify the link between the job satisfaction and turnover
intention. As per the contemporary literature studied by Reed (1996) and Frenkel &
Korezgynski (2002), the important proposition can be made here that
Proposition1: IS professional are more committed to the occupation than to the
organization in Indian context.
Proposition2: IS professional occupational commitment mediates the relationship
between their job satisfaction and intention to quit in Indian context.
Further the study should also try to investigate the precursors to occupational
commitment and turnover intention. This would provide remedies to reduce mobility and
job shifting of the knowledge worker in the organization. The study also indicates future
effort towards investigating the non-attitudinal dimensions and determinates to job
outcomes. This is a clue which can be interpreted from the present finding stating that the
attitudinal dimension exhibits only 30%of variance in Job satisfaction. Henceforth, the
future study should also consider the effects of non-attitudinal dimensions of turnover
intention which can provide better insight to turnover model.
Baroudi, J.J. (1985).The impact of role variables on IS personnel work attitudes and
intentions. MIS Quarterly, 9, 4, 341-356.
Baroudi, Jack J and Magid Igbaria. “The impact of job performance evaluations on career
advancement prospects: an examination of gender differences in the IS workplace.” MIS
Quarterly, 19:1, (March 1995).
Bartol, K.M. (1982) “Managing Information Systems Personnel: A review of the
literature and Managerial Implications” MIS Quarterly, pp: 49-70.
Damien Joseph , Soon Ang , Sandra Slaughter, Identifying the prototypical career paths
of IT professionals: a sequence and cluster analysis, Proceedings of the 2005 ACM
SIGMIS CPR conference on Computer personnel research, April 14-16, 2005, Atlanta,
DeCotiis, T. A., and Summers, T. P. (1987). A path analysis model of the antecedents
and consequences of organizational commitment. Human Relations, 40, 445-470.
Dougherty, T.W., Bluedorn, A.C., & Keon, T.L. (1985). Precursors of employee
turnover: A multiple-sample causal analysis. Journal of Occupational Behaviour, 6, 259-
Farkas, Arthur, J. & Lois. E. Tetrick. 1989. A three-wave longitudinal analysis of the
causal ordering of satisfaction and commitment on turnover decisions. Journal of Applied
Psychology, 74 (6). 855 – 68.
Frederick F. Reichheld. 1996. The Loyalty Effect: The Hidden Force Behind Growth,
Profits, and Lasting Value. Harvard Business School Press, Bain & Company Inc.
Gardner, Donald G., Dukes, Richard L. and Discenza, Richard. (1993). Computer Use,
Self-Confidence and Attitudes: A Causal Analysis. Computers in Human Behavior. Vol.
9, Number 3. pp 427-440.
Griffeth, 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, No. 3, 463-488 (2000).
Guimaraes, T., and Igbaria, M. The determinants of turnover intentions: Comparing IC
and IS personnel. Information Systems Research, 3, 3 (September 1992), 273–303.
Hom, P. W., & Kinicki, A. J. (2001). Toward a greater understanding of how
dissatisfaction drives employee turnover. The Academy of Management Journal, 44(5),
Hom, P.W., Caranilas- Walker, F., Prussia, G.E., & Griffeth, R.W (1992). A meta-
analytical structural equations analysis of a model of employee turnover. Journal of
Applied Psychology, 77, 890-909.
Igbaria, , M., & Siegel, S.R (1992). The reasons for turnover of information systems
personnel. Information and Management, 23, 321-330.
Igbaria, Greenhaus, and Parasuraman, 1991, Career orientations of MIS employees: an
empirical analysis, MIS Quarterly Volume 15 , Issue 2 (June 1991) Pages: 151 – 169.
Igbaria, M. & Greenhaus, J.H. (1992) Determinants of MIS employees' turnover
intentions: A structural equation model. Communications of the ACM, 35(2), 34-51.
Igbaria, M., and Wormley, W. Race differences in job performance and career success
among IS people. Communications of the ACM, 38, 3 (March 1995), 82–92.
Igbaria, M., Parasuraman, S., and Badawy, M. K. 1994. “Work Experiences, Job
Involvement, and Quality of Working Life among Information System Professionals.”
MIS Quarterly 18(2): 175–199.
Igbaria, Magid, Meredith, Guy, and Smith, Derek C. 1994. Predictors of intention of IS
professionals to stay with the organization in South Africa. Information & Management,
26(5), pp. 245-256.
Iverson, R. D. (1992), Employee intent to stay: An empirical test of a revision of the
Price and Mueller model, Unpublished doctoral dissertation, The University of Iowa.
Iverson, R. D. and Roy, P. (1994), A causal model of behavioral commitment: Evidence
from a study of Australian blue-collar employees, Journal of Management, 20, 15-26.
James J. Jiang, Gary Klein: User evaluation of information systems: by system typology.
IEEE Transactions on Systems, Man, and Cybernetics, Part A 29(1): 111-116 (1999).
Kirschenbaum, A. and Mano-Negrin, R. (1999).Underlying Labor Market Dimensions of
“Opportunities”: The Case of Employee Turnover, Human Relations, 52: 1233-1255.
Lee T. W., Ashford S. J., Walsh J. P. and Mowday R. T. (1992). Commitment
Propensity, Organizational Commitment, and Voluntary Turnover A Longitudinal Study
of Organizational Entry Processes, Journal of Management, 18: 15-32.
Lee, T.W. & Mitchell, T. R. (1994). An alternative approach: The unfolding model of
voluntary employee turnover. Academy of Management Review, 19, 51-89.
Lee, T.W., Mitchell, T.R., Holtom, B. C., McDaniel, L. S., & Hill, J. W. (1999). The
unfolding model of voluntary turnover: A replication and extension. Academy of
Management Journal, 42(4), 450-462.
Lee, T.W., Mitchell, T.R., Holtom, B.C., McDaniel, L.S. & Hill, J.W. (1999). The
unfolding model of voluntary turnover: A replication and extension. Academy of
Management Journal, 42, 450-462.
Mathieu, J.E. & Zajac, D.M. (1990). A review and meta-analysis of the antecedents,
correlates, and consequences of organizational commitment. Psychological Bulletin, 108:
May,T.Y., Korczynski, M., & Frenkel, S. Organizational and Occupational Commitment:
Knowledge Workers in Large Corporations, Journal of Management Studies, Vol. 39,
pp. 775-801, 2002
Meyers and Allen (1990), The measurement and antecedents of affective, continuance,
and normative commitment to the organization, Journal of occupational psychology, 63 ,
1 - 8.
Michaels, CE and Spector, P E, (1982), Causes of employee turnover: A test of the
Mobley, Griffith, Hand, and Meglino Model, Journal of Applied Psychology, 67, 53-59.
Mueller, C.W. and Price, J.L. (1990). Economic, Psychological and Sociological
Determinants of Voluntary Turnover, Journal of Behavioural Economics, 19: 321-335.
Niederman, Brancheau, and Wetherbe, 1991, Information system issues for 1990s,
Management information systems Quarterly, December, 15 (4): 475-500.
Pare, Guy, Tremblay, Michel and Lalonde, Patrick, Workforce Retention: what do IT
employees really want. Proceedings of the 2001 ACM SIGCPR Conference, pp. 1-10, San
Diego, CA, April 2001.
Reed MI. Expert power and control in late modernity: an empirical review and theoretical
synthesis. Organization Studies 1996;17(4):573–97.
Reichheld, F.F. (1996). The Loyalty Effect: The Hidden Force Behind Growth, Profits
and Lasting Value Harvard Business School Publications, Boston
See “Information Security Manpower Demand Estimation” NASSCOM REPORT, 2005
See “Extending India’s leadership in the global IT and BPO industries” NASSCOM
See “The Indian IT industry taking the hr road to success!”, NASSCOM REPORT, 2005
See “KNOWLEDGE PROFESSIONALS in India” NASSCOM REPORT, 2005
Slaughter , Soon Ang, Internal labor market strategies and turnover of information
technology professionals, Proceedings of the 2002 ACM SIGCPR conference on
Computer personnel research, May 14-16, 2002.
Somers M. J. (1995). Organizational commitment, turnover and absenteeism: an
examination of direct and interaction effects, Journal of Organizational Behavior, 16: 49-
Tett and Meyer (1993), Job satisfaction, organizational commitment, turnover intention:
Path analyses based on meta-analytic findings, Personnel Psychology, 46, 259 - 293.
Vandenberg, R.J. and Nelson, J.B. (1999).Disaggregating the Motives Underlying
Turnover Intentions: When Do Intentions Predict Turnover Behavior?, Human Relations,