1 Introduction

In India, the turnover rates have been reported as high as 80% in the IT services sector (Gupta 2001) and as high as 100% for Indian call centers (Mitchell 2005, 2007). For example, Wipro announced that it replaced 90% of its call enter and BPO workers in 2004 (McCue 2005). The lowest rates we found reported on turnover in Indian software services was 30% (Mitchell 2004). No matter which turnover number one considers—the low estimate of 30% or the high estimate of 100%, there is no denying that turnover is a major issue to Indian suppliers and their global clients. Supplier staff turnover delays the clients’ projects, reduces quality, and increases costs (Jiang and Klein 2002). Clearly, both clients and suppliers share the objective of high retention of the supplier’s most qualified workers.

One contribution academics can make is to develop and test a model of Turnover that is applicable to the Indian IS context. Although there are nearly 50 studies on Western IS professionals (Joseph et al. 2007), we are not aware of any research specifically addressing turnover among Indian IS professionals. The purposes of this paper are to propose a model of turnover based on interviews with Indian IS professionals and to identify implications for practice. Our hope is that by better understanding why Indian IS professionals want to leave or stay with their current organizations, suppliers (and perhaps clients) will be able to target practices to increase retention. We initially developed a model based on extensive research from the organizational behavior and information systems literatures and identified six hypotheses (see Section 2). We then interviewed 25 Indian IS professionals working for 13 different suppliers (see Section 3). We tested the initial hypotheses using nonparametric statistics and interpret these findings based on the interview data (see Section 4). Based on the results the hypothesis tests and the additional constructs that emerged from the interviews, we significantly revised the model (see Section 5). The revised model must be empirically assessed, but we believe we have made important progress towards understanding turnover intentions of Indian IS professionals. We discuss four implications for practice in Section 6.

2 Identifying an initial model of turnover intentions

Although researchers want to ideally understand turnover behavior, in reality, it is often difficult to empirically examine the behavior. Instead, researchers more typically survey current employees and ask them their turnover intentions. Turnover intentions are a reliable predictor of turnover behaviors (Ajzen and Fishbein 1980). Substantial empirical evidence supports the theory that attitude affects behavior more than behavior affects attitude. For example, a time sequenced meta-analysis of 49 studies on job attitudes (including Job SatisfactionFootnote 1 and Organizational Commitment) and work behavior (including Turnover) comprising over 10,000 individuals found that predictive correlations between attitude-to-behavior were stronger than predictive correlations between behavior-to-attitude (Harrison et al. 2006). They conclude: “The combined evidence from dozens of time-lagged studies tends to favor the attitude–behavior mechanism” (Harrison et al. 2006, p. 318).

2.1 Models of turnover/turnover intentions from organizational behavior literature

Within the Organizational Behavior literature, there are many well-tested models of Turnover Intention based on the following theories:

  • –The Two Factor Theory (motivation and hygiene factors) suggests that when factors are fulfilled, Turnover is lower (Herzberg 1968).

  • –Theory of Needs (affiliation, achievement and power needs) suggests that when an individual’s needs are met at an organization, Turnover is lower (McClelland 1961).

  • –Turnover Theory posits that Job Satisfaction, Organizational Alternatives, and Search Intention are antecedents to Quit Intention (Mobley et al. 1978; Hom et al. 1992).

  • –Person-to-Organization Fit Theory posits that high compatibility between an individual and an organization is negatively related to Turnover (Argyris 1957; Pervin 1989; Arthur et al. 2006; Hoffman and Woehr 2006).

  • –Turnover models suggest that job characteristics (Skill Variety, Task Significance, Task Identity, Autonomy, and Feedback) determine Job Satisfaction which in turn determines Turnover (Hackman and Oldham 1976, 1980).

  • –The Job Investment Model posits that Job Rewards and Job Costs determine Job Satisfaction, that Organizational Alternatives and Investment in the organization determine Organizational Commitment, and that both Job Satisfaction and Organizational Commitment determine Turnover (Farrell and Rusbult 1981).

We found thousands of tests of these models within the organizational behavior literature. The rich research base from organizational behavior has significantly informed the IS turnover research.

2.2 Models of turnover/turnover intentions from information systems literature

Within the IS literature, the basic model of Turnover Intentions shows that Job Satisfaction and Organizational Commitment directly affect Turnover Intentions among Western (mostly US) IS professionals (see Fig. 1). Joseph et al. (2007) conducted a meta analysis of IS turnover research among IS professionals and found that Job Satisfaction was the most frequently studied determinant of Turnover. In the 16 IS studies that used this construct, all 16 found a negative relationship between Job Satisfaction and Turnover. The second most frequently studied construct was Organizational Commitment. Eleven IS studies found a negative relationship between Organizational Commitment and Turnover among IS professionals (Ahuja et al. 2007; Baroudi 1985; Igbaria and Greenhaus 1992).

Fig. 1
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Basic turnover model found among Western IS professionals

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IS academics have also extended the basic model in Fig. 1 by testing many antecedents of Job Satisfaction and/or Organizational Commitment for IS professionals. These constructs have included Boundary Spanning Activities, Burnout, Career Expectations, Career Orientation, Career Satisfaction, Gender, Internal Labor Market Strategies, IT Human Resource Management configurations, Job Autonomy, Job Involvement, Job Tasks, Management Policy, Role Ambiguity, Role Conflict, Salary, Shocks, Turnover Culture, Work Exhaustion, Work Experiences, and Work Family Conflict (Ahuja et al. 2007; Baroudi 1985; Ferratt et al. 2005; Gupta and Gupta 1990; Igbaria and Greenhaus 1992; Igbaria et al. 1994; McMurtrey et al. 2002; Moore 2000; Moore and Burke 2002; Niederman and Sumner 2004; Rouse 2001; Sethi et al. 1999). Furthermore, many of these higher level constructs have multiple dimensions, such as the five dimensions of HR configuration (1) work environment, (2) community building, (3) incentives, (4) employment and security, and (5) non-technical skill recruitment (Ferratt et al. 2005).

2.3 Our initial model of turnover intentions

Because we did not know a priori which antecedents of Job Satisfaction and Organizational Commitment from the study of Western IS professionals might be the most relevant to Indian IS professionals, we sought a general but comprehensive model that would allow the Indian IS professionals to suggest the most important antecedents. We selected the investment model initially proposed by Kelley and Thibaut (1978) and applied to Turnover Intentions by Farrell and Rusbult (1981) and Van Dam (2005). This model is comprehensive because it includes job factors (Job Satisfaction and Job Attraction), organizational factors (Organizational Commitment and Investment in Current Organization), and environmental factors (Organizational Alternatives). This model also appealed to us because it generically defines the determinants of Job Satisfaction as the individual’s overall subjective estimation of job rewards versus job costs. Thus, we could ask Indian IS Professionals generic questions about the rewards and costs of the current job without limiting the scope to a few specific constructs. We were very interested in specifically including Organizational Alternatives because the vibrant job market in India is likely to be a driving force behind high turnover. Our initial research model is thus found in Fig. 2.

Fig. 2
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Initial research model

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The initial research model includes six constructs. These constructs are defined in Table 1 based on the literature.

Table 1 Construct definitions used in the initial research model
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The most widely cited theorists of Organizational Commitment include Porter et al. (1974), Steers (1977), Meyer and Allen (1997). Over 300 studies have used the construct Organizational Commitment as defined by these scholars. As evident by several meta analyses, a strong general finding is that Organizational Commitment is negatively correlated with Turnover (Mathieu and Zajac 1990; Tett and Meyer 1993). As previously indicated by the basic model of Turnover Intentions among IS professionals, Organizational Commitment has been found to be a major determinant of Turnover Intentions among Western IS professionals (Gallivan 2004; Joseph et al. 2007). Based on this vast empirical support, the first hypothesis is:

  1. H1:

    Organizational Commitment is negatively related to Turnover Intentions

    Job Satisfaction has been extensively studied since the 1930s, with more than 12,400 studies published on the topic by 1991. Substantial evidence from several meta analyses found that Job Satisfaction is negatively related to Turnover Intentions (Cotton and Tuttle 1986; Hom et al. 1992; Tett and Meyer 1993). As previously indicated by the basic model of Turnover Intentions among IS professionals (Gallivan 2004; Joseph et al. 2007) Job Satisfaction is negatively related to Turnover Intentions among Western IS professionals. Our second hypothesis is:

  2. H2:

    Job Satisfaction is negatively related to Turnover Intentions

    Job Satisfaction has also been found to have a direct relationship with Organizational Commitment. In the Job Investment Model of Intentions to Leave, Job Satisfaction is one of the three major determinants of Organizational Commitment, along with Organizational Alternatives and Investment (Farrell and Rusbult 1981). Empirical research supports this model. Two studies tested all three antecedents to Organizational Commitment. In Rusbult and Farrell’s (1983) test of the Investment model with 88 employees in professional service organizations, they found that Organizational Commitment was determined by high Job Satisfaction, poor Alternative quality, and large Investment size. Van Dam (2005) tested these relationships with a survey of 953 employees from three hospitals. She found that Job Satisfaction was positively related to Organizational Commitment, Organizational Alternatives were negatively related to Organizational Commitment, and Investments were positively related to Organizational Commitment. Several other meta-analyses also support that Job Satisfaction is an antecedent to Organizational Commitment (Mathieu and Zajac’s 1990; Tett and Meyer 1993). Because Organizational Commitment takes longer to develop and is more stable than Job Satisfaction, turnover models suggest Job Satisfaction directly affects Organizational Commitment rather than the other way around (Tett and Meyer 1993). Based on this research, we hypothesize:

  3. H3:

    Job Satisfaction is positively related to Organizational Commitment

    In Rusbult and Farrell’s 1983 test of the Job Investment Model, they found that Organizational Commitment was significantly determined by poor Organizational Alternatives. Van Dam (2005) found that Organizational Alternatives were negatively related to Organizational Commitment. In addition to these studies, a meta-analysis of seven empirical studies comprising 2,657 individuals found that Perceived Job Alternatives was negatively related to Organizational Commitment (Mathieu and Zajac’s 1990). It is also interesting that a meta-analysis of 21 studies found that Organizational Alternatives is only weakly directly related to Turnover Intentions (Steel and Griffeth 1989). Thus, the evidence suggests that Organizational Alternatives affects Turnover Intentions through the mediating variable, Organizational Commitment. Based on this research, we hypothesize:

  4. H4:

    Organizational Alternatives is negatively related to Organizational Commitment

    Investment in Current Organization includes acquisition of non-portable skills, non-transferable retirement programs, and length of service. Although early research suggests that Organizational Investment is what the individual puts into the organization, it is clear that organizations also invest in the individual. Expensive training programs, for example, may make the employee feel obligated to the organization and thus increase their Organizational Commitment (Cole and Bruch 2006). Previously cited research has empirically found a significant relationship between Organizational Investment and Organizational Commitment (Rusbult and Farrell 1983; Van Dam 2005). Our hypothesis is:

  5. H5:

    Investment in Current Organization is positively related to Organizational Commitment

    Job Attraction is derived from the Job Investment Model of Intentions to Leave. In this model, Job Attraction comprises the overall assessment of job rewards and job costs. Job rewards and costs may include compensation such as salary, bonuses, benefits and job characteristics such as task variety, task identity, task significance, task autonomy, role ambiguity, role complexity, and job stress (Kelley and Thibault 1978; Farrell and Rusbult 1981; Rusbult and Farrell 1983; Van Dam 2005). Job rewards and job costs are considered isomorphic. Any of the components may either be a job reward or a job cost, depending on the individual’s perception. For example, if an individual is highly satisfied with their salary, salary would be considered a job reward. Conversely, if an individual was highly dissatisfied with their salary, salary would be considered a job cost.

    In Rusbult and Farrell’s 1983 test of the Investment model, they found that greater Job Satisfaction resulted from higher job rewards and lower job costs. They conclude: “The results of this study provide good support for the investment model predictions. In general, greater job rewards and lower job costs induce greater employee satisfaction.” (p. 436). Van Dam (2005) found the overall assessment of Job Attraction (Job Rewards versus Job Costs) was positively related to Job Satisfaction. In her study, Job Attraction captures Job Rewards versus Job Costs by asking respondents to assess nine job reward items. She followed Rusbult and Farrell’s argument that the absence of a reward implies the presence of a cost. She concludes: “Consistent with predictions, employees who perceived a more favorable jobs rewards–costs ratio reported great satisfaction” (p. 265). Based on this research, our hypothesis is:

  6. H6:

    Job Attraction is positively related to Job Satisfaction

3 Research method

3.1 The interview method

To assess to the applicability of our initial model, we used interviews. The primary purpose for the interviews was to assess whether the initial model, which was developed primarily by Western academics and tested with Western workers, is applicable to the context of Indian IS professionals. Interviews are an appropriate method when researchers:

  1. a)

    seek to understand themes of the lived daily world from the subject’s own perspectives (Kvale 1996)

  2. b)

    do not want to limit the study to predefined constructs or predefined categories within constructs (Glaser and Strauss 1967)

  3. c)

    seek participation from busy or high-status respondents (Mahoney 1997)

  4. d)

    seek answers to questions in which the subject matter is sensitive (Mahoney 1997)

  5. e)

    are concerned with the quality, not quantity of responses (Fontana and Frey 1994);

  6. f)

    are concerned with the participants’ values (Bourne and Jenkins 2005; Gummesson 2000)

  7. g)

    seek to answer a why or how questions about contemporary events over which the researcher has little or no control (Fontana and Frey 1994; Yin 2003)

We believe that interviews were the best research method to assess the applicability of our initial model and hypotheses. First, we wanted a method that would allow additional constructs beyond the initial model to emerge from the interviews (and indeed they did). The interview method, therefore, allowed us to expand the research model. Second, we believed that busy IS professionals, who hold a significant position of status within the Indian culture, would be more likely to respond to a personal interview than to an anonymous survey. Third, many people would likely perceive intentions to leave an organization as a sensitive subject. Thus, we selected an interview method because it allows researchers to clearly communicate the purpose of the research, to ensure confidentiality, and to build trust during a personal interview. Once trust is established, research participants would be more likely to answer sensitive questions about their current job satisfaction, job commitment, and turnover intentions (and indeed they did).

We selected semi-structured interviews because we wanted to leave the method fluid enough to explore constructs that may be missing from the model, but rigid enough to assess whether the six constructs were applicable. Interviews were conducted by telephone because the authors are located in the US and Indian IS professionals are located in India.

The interview guide

The Interview Guide (see Appendix) is designed to capture the six constructs in the initial model, to allow participants to freely explain their reasoning and values, and to explore uncharted constructs. Concerning the six constructs, the interview guide clearly prompted participants to respond to the model’s constructs so that we could later code their answers. This proved an effective method because we were able to code the constructs and identify new constructs, except for our initial questions to capture Organizational Commitment. Our first set of questions were: “How do you feel about your company?” and “Does the organization mean a lot to you?” These questions did not prompt participants to discuss their emotional bond to the organization. After interview seven, we added the question “Do you feel emotionally attached to your company?” As we later discuss, this additional question yielded some fascinating results.

The open-ended questions gave the participants the latitude to explain their responses and to identify constructs that were not previously identified in the model. Indeed, we added three new constructs to the model based on the interviews.

Research participants

Twenty-five Indian IS professionals were interviewed. The interviews were conducted by the two Indian co-authors. We believed that they would elicit more trust than the American co-author due to higher homophile with Indian participants (Rogers 2006). In addition, the IS professionals were selected based on mutual acquaintances of the Indian co-authors, which further served to elicit trust from the respondents. Although the sample is opportunistic, we believe it is better to ensure the trust and cooperation from an opportunistic sample than to attempt to solicit cooperation from an anonymous random sample because the topic is sensitive.

The interviews were conducted between November 2006 and March 2007. The demographic information of the 25 Indian IS professionals is summarized in Table 2. The 25 Indian IS professionals worked for 13 different supplier firms. (In embedded quotes, the 13 supplier names have been replaced with S1 through S13.) Nineteen participants work in Bangalore, three in Pune, one in Hyderabad, and one in Delhi. The sample contained 13 different job titles, including senior software engineer, assistant project manager, project manager, analyst, developer, team lead, process lead, quality engineer, and quality lead.

Table 2 Demographics of 25 participants
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3.2 Coding the transcriptions

The 25 interviews were transcribed. Each participant was assigned an identifier labeled P1 to P25. For each participant, the three authors coded the six constructs independently as “high,” “moderate” or “low”. Table 3 shows examples of how five of the six constructs were coded from interview extracts. We independently agreed on the coding for Turnover Intentions, Job Satisfaction, Organizational Alternatives, and Job Attraction for all 25 participants. We initially could not code Organizational Commitment (discussed above) until we added another question after interview seven. We did not independently code three “Organizational Alternatives” and six “Investment in Current Organization” the same. Because responses were ambiguous in these cases, we left these as “unable to code.” Job Attraction required more consideration to code because we had to consider the participants’ responses to 12 questions on compensation and job characteristics. Responses to these questions could consume three pages of transcription, but we were easily able to code Job Attraction. Three patterns were readily evident:

  • –The participant was satisfied with nearly all their compensation and job characteristics (high Job Attraction)

  • –The participant reported satisfaction with some of the compensation and job characteristics and dissatisfaction with other compensation and job characteristics (moderate Job Attraction)

  • –The participant was dissatisfied with nearly all their compensation and job characteristics (low Job Attraction)

Table 3 Examples of coding five constructs based on participants’ responses
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Table 4 summarizes the coding for all six constructs.

Table 4 Code summaries
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4 Findings from the interviews

To investigate the hypotheses, we created a series of tables that mapped independent variables to dependent variables (Tables 5, 6, 7, 8, 9 and 10) and ran two nonparametric statistical tests. The tables illustrate the hypothesized relationships with dark gray shading. The light gray shading indicates somewhat of a relationship. The clear cells indicate observations that are counter to hypotheses. The clear cells, which are anomalies, provide important clues for modifying the model.

Table 5 H1: Organizational Commitment versus Turnover Intentions (n = 19)
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Table 6 H2: Job Satisfaction versus Turnover Intentions (n = 25)
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Table 7 H3: Job Satisfaction versus Organizational Commitment (n = 19)
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Table 8 H4: Organizational Alternatives versus Organizational Commitment (n = 17)
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Table 9 H5: Investment versus Organizational Commitment (n = 15)
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Table 10 H6: Job Attraction versus Job Satisfaction (n = 25)
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Because the sample data is ordinal, small, and opportunistic, we ran two non parametric tests. Kendall’s tau-c is a symmetrical test of association between X and Y. Somers’ d is asymmetrical, testing the directional association of X on Y. Both tests generate values ranging from −1 for a perfectly negative relationship to +1 for a perfectly positive relationship. For the six tests, we applied p < 0.01 as the required level of significance.

4.1 H1 not supported

Table 5 maps Turnover Intentions to Organizational Commitment. We hypothesized that Organizational Commitment is negatively related to Turnover Intentions. The evidence does not support the hypothesis as evidenced by the two statistical tests. Twenty-six percent of the observations fall within the clear cells, representing five anomalies. The anomalies are discussed below.

Three participants (P15, P19, and P25) had low Turnover Intentions and low Organizational Commitment. P15 is a male who wants to stay in his current organization because of the career opportunities, but reports no emotional bond with the company. P19 has only been working for S9 for 5 months, so he reports that he does not have an emotional bond to the company even though he intends to remain with the organization. P25 is a female who wants to stay with the current organization because of the career development opportunities and because her organization is close to her family. But she does not feel emotionally attached to her organization.

Two participants (P20 and P24) had high Turnover Intentions and high Organizational Commitment. P20 is a male who has high Turnover Intentions for the primary reason of locating closer to his family, even though he reports high Organizational Commitment. He states, “I do feel part of the company. I do feel a sense of belongingness. I feel proud to be working for S4, which has 80% market share in semi-conductors. The only reason I want to leave is to make sure I spend some time with my family.”

P24 is a female who intends to leave the organization to pursue an MBA even though she currently reports high Organizational Commitment. These anomalies suggest that emotional attachment to an organization is not a significant determinant of Turnover Intention for these participants.

4.2 H2 supported

We hypothesized that Job Satisfaction is negatively related to Turnover Intentions. Table 6 maps Turnover Intentions to Job Satisfaction. The evidence supports the hypothesis as evidenced by the two statistical tests. There are no anomalies within the clear cells to examine. We keep this hypothesis unaltered in the final model.

4.3 H3 not supported

We hypothesized that Job Satisfaction is positively related to Organizational Commitment. Table 7 maps Job Satisfaction to Organizational Commitment. The evidence does not support the hypothesis. Twenty-one percent of the observations, representing four participants (P15,P19, P25, and P24), fall within the clear cells.

Three participants (P15, P19, and P25) report low Organizational Commitment but high Job Satisfaction. These anomalies were previously discussed in conjunction with H1. They like the work they do, but they do not feel emotionally attached to their organizations. One participant, P24 again, reported high Organizational Commitment but low Job Satisfaction. She is female who intends to leave the organization to pursue an MBA. Her main issue with her current job is that she does not like IT work, even though she likes her current company.

4.4 H4 not supported

Hypothesis 4 posited that Organizational Alternatives is negatively related to Organizational Commitment. Table 8 maps Organizational Alternatives to Organizational Commitment. The evidence does not support the hypothesis as evidenced by the two statistical tests. Five participants (29% of observations) fall within the clear cells. One issue may be the fact that there is not much variability in Organizational Alternatives. Sixteen of the 25 IS professionals perceived a high availability of equal or better jobs in the market.

Five participants (P8, P9, P18, P21, and P24) perceived high Organizational Alternatives and high Organizational Commitment. P8, P9, P18, and P21 all had many positive things to say about their organizations. Although these four all perceived that Organizational Alternatives were plentiful, the opportunities do not tempt them to leave. P24 again surfaces as an anomaly—she is the one leaving to pursue her MBA.

4.5 H5 not supported

We hypothesized that Investment in the Current Organization is positively related to Organizational Commitment. Table 9 maps Investment to Organizational Commitment. The evidence does not support the hypothesis as evidenced by the two statistical tests.

There are a couple of noteworthy issues from this analysis. First, the only anomaly in the clear cell is once again P24. Second, there are no observations in which Investment in Current Organization is perceived as high. As a group, the participants thought that their IT skills were highly portable. The participants with moderate investments stated that although their IT skills were highly portable, other investments were not. Non-portable investments included benefits from tenure in the organization such as becoming vested, establishing a good reputation within the current organization, and understanding the organization’s idiosyncratic processes or domain-specific knowledge.

4.6 H6 supported

We hypothesized that Job Attraction is positively related to Job Satisfaction. Table 10 maps Job Attraction to Job Satisfaction. The evidence strongly support the hypothesis as evidenced by the two statistical tests. There are no anomalies within the clear cells to examine. Thus, we keep this hypothesis unaltered in the final model.

5 Revised model based on interview data

Based on the 25 interviews, there is reasonable evidence to support H2 and H6. However, the other hypotheses are not supported. In this section, we discuss three changes to the turnover model suggested by the interview data. The revised model is found in Fig. 3.

Fig. 3
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Revised model of turnover intentions among Indian IS professionals

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5.1 Replace organizational commitment with organizational satisfaction

Organizational Commitment was the one variable common in the four hypotheses that were not supported. A closer examination of this variable is warranted.

One possible explanation is a problem with the definition of Organizational Commitment, which IS academics define as emotional attachment to the organization. It was very difficult to get participants to discuss their emotional attachment to an organization. This construct resulted in the highest number of uncodable responses (n = 6) during our initial interviews when we only asked how they feel about the organization and whether the organization means a lot to them. Participants did not naturally reply to these questions by expressing emotional attachment to the organization.

After P7, we added the specific question, “Do you feel emotionally attached to the organization?” Responses were interesting because many hesitated and some even laughed at the notion that a human is bonded to an organization. For example, when we asked P13 how he feels about the organization he said, “Company as such is great. It is a number two company in the world. If I see the company on the whole, definitely one of the best companies to have every existed.” The follow-up question, “Do you feel emotionally attached to your company”? resulted in “No, no, no!”

For another example, consider the following dialog with P11:

Author: “How do you feel about your company?”

P11: “General feeling is satisfactory, not good.”

Author: “Does the organization mean a lot to you?”

P11: “Yeah, as I have worked here all these years, I must be loyal.”

Author: “Do you feel emotionally attached to your company?”

P11: “No, not at all….My responsibility is my personal life.”

P25 provides a third example of positive feelings about the organization, yet not feeling emotionally attached:

Author: “How do you feel about your company? What is the general feeling that you have?”

P25: “In general it is a good company where we can learn a lot of knowledge in the semiconductor industry and we get lot of opportunities to grow. Good for growth also.”

Author: “Do you feel emotionally attached to your company?”

P25: “Emotionally, not so.”

In some other interviews, individuals reported that they did not feel emotionally connected to the organization, but they did feel emotionally connected to their colleagues. When asked, “Do you feel emotionally attached to your company?” P10 said no, but clarified with: “But they are very good group. We are very close. I think if I leave this company, I will miss those people.” P23 had a similar response: “Not really. Not the company, but maybe with the people I work with.”

Thus, many Indian IS professionals we spoke to could not relate to the concept of emotional attachments to an organization. We highly suspect, based on the responses to the Organizational Commitment questions, that Organizational Satisfaction will better capture the sentiments of Indian IS professionals towards their organizations.

Organizational satisfaction

Organizational Satisfaction is defined as “the extent to which an employee is satisfied with their current organization”. We found that when we initially asked participants how they felt about their organizations, they frequently responded with the extent to which they were satisfied or dissatisfied with their organizations. Organizational Satisfaction is clearly different than Organizational Commitment (affectual). Indian IS professionals could be satisfied with their organization but not feel emotionally attached to it. In addition, Organizational Satisfaction is clearly a separate construct from Job Satisfaction, in that some participants were happy with their current jobs (job characteristics and compensation), yet dissatisfied with the overall organization. Conversely, a number of participants were dissatisfied with their current jobs, but were satisfied with their organizations. In these circumstances, the employees were seeking job changes within their organizations.

Within the OB literature, Organizational Satisfaction has been linked to Turnover Intention (Shore and Tetrick 1991; Kittiruengcharm 1997; Szamosi 2006). For example, Kittiruengcharm (1997) administered a survey to 408 public sector engineers in Thailand and found a significant negative correlation between Organizational Satisfaction and Turnover Intention. Therefore, one hypothesis developed from this replacement construct is:

  1. H1:

    Organizational Satisfaction is negatively related to Turnover Intention

    Kittiruengcharm’s path analysis of the survey data found that Job Satisfaction contributed to Organizational Satisfaction, and vice versa. However, the path was stronger from Job Satisfaction to Organizational Satisfaction than from Organizational Satisfaction to Job Satisfaction. The findings are consistent with the view that attitudes about jobs are formed quicker than attitudes about organizations (Tett and Meyer 1993). We therefore hypothesize:

  2. H3:

    Job Satisfaction is positively related to Organizational Satisfaction

5.2 Include perceived organizational support as a determinant of organizational satisfaction and job satisfaction

When we asked participants how they felt about the organization, we noted they frequently expressed their level of satisfaction with the organization. They also justified the reasons for their level of satisfaction by discussing management support, supervisor support, career development opportunities, organizational culture, and company policies. Table 11 summaries the number of participants who mentioned these reasons. The three authors coded these responses as “participants spoke only unfavorably,” “participant spoke unfavorably and favorably,” and “participant spoke only favorably”.

Table 11 Participants’ reasons for explaining organizational satisfaction
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Management support

Twenty participants discussed Management Support as a justification for their feelings about the organization. Fourteen participants spoke only favorably about their managers. Participants discussed that they could bring problems to their managers, ask for help, seek resources, and talk about career opportunities. Only three participants spoke only unfavorably about Management Support. Below are representative quotes of the three classifications of Management Support:

P8 (favorably): “Managers are very nice. They give enough time to the people who are not up to the work by trying to bring them up to the mark. It’s a very good, friendly company.”

P13 (favorably/unfavorably): “Management is supportive of our endeavors but management does not have proper control of the people sitting in the US and Europe.”

P11 (unfavorably): “Management is not supportive.”

Organizational culture

Eighteen participants discussed Organizational Culture as a justification for their feelings about the organization. Thirteen spoke only positively about the culture. Some examples of favorable descriptions include:

P11 (favorably): “The company culture is very good.”

P21 (favorably): “The work culture is good. Every individual shares his or her knowledge with everyone else in the company.”

P24 (favorably): “The work culture is amongst the best that I have seen. It’s a great place to work in.”

Only four participants spoke only unfavorably about the Organizational Culture. For example, P13 did not like the relaxed culture in his company. He said, “What does not give you fulfillment is the kind of environment that we have in the business. People not applying proper processes, people not working in a structured format that is disappointing with the organization.”

Career development

Seventeen participants discussed Career Development as a justification for their feelings about the organization. Eight spoke only favorably about Career Development. For example, P9 discussed the career paths as a clear “roadmap” at his company. Six participants spoke only unfavorably about Career Development. For example, P1 believes management placates employees with the rhetoric of Career Development, but that in reality they assign employees where the company needs them. She stated, “To be very frank they talk a lot about career development. They call you and ask you what your career objectives are, but they want you to adjust according to their requirements. That’s how it happens. They try to pacify you.”

Supervisor support

Sixteen participants discussed Supervisor Support as a justification for their feelings about the organization. These responses were bipolar. Like Management Support, most participants spoke favorably about their direct supervisors:

P18 (favorably):“My manager [direct supervisor] is like a guide to me. I go to him for guidance.”

P7 (favorably): “He is encouraging actually.”

Four spoke only unfavorably about their direct supervisor. For example, P1 stated, “My manager [direct supervisor] is very bossy and sometimes I feel like quitting the job just because of him.”

Company policies

Nine participants discussed company policies as a justification for their feelings about the organization. These responses were also bipolar. Five spoke only favorably about company policies such as the company’s “open door policy” and the policy at one supplier that allows employees to request a new position every 18 months. Four participants talked only unfavorably about company policies. P3, for example, was very frustrated with her company’s HR recruiting policies. She felt that the company hired “freshers” and assigned them to projects without proper training. She said: “Sometimes we end up with really dumb recruits. They don’t have any aptitude for the kind of job they have to do…sometimes you end up doing their work.”

To summarize, five constructs emerged from the interviews concerning participants’ feelings about their organizations: Management Support, Organizational Culture, Career Development, Supervisor Support, and Company Policies. Rather than add five new constructs to the model, we searched the literature to identify a construct rich enough to encompass all these factors. We selected Perceived Organizational Support as the umbrella construct.

Perceived organizational support

This construct is formally defined in the literature (Rhodes and Eisenberger 2002) as follows:

Perceived Organizational Support: The employees’ beliefs concerning the extent to which the organization values their contributions and cares about their well-being and socioemotional needs.

Whereas Organizational Commitment is about the employees’ commitment to the organization, Perceived Organizational Support is about the employee’s perceptions about the organization’s commitment, support, and care to the employee. A meta-analysis of 70 empirical studies of Perceived Organizational Support found that the major antecedents included supervisor support, fair policies, and organizational rewards (Rhodes and Eisenberger 2002). Joiner and Bakalis (2006) also found that supervisor support is a major antecedent of Organizational Commitment. Perceived Organizational Support thus captures much of what our participants cited as reasons for their feelings about the organization. The meta-analysis also looked at the consequences of Perceived Organizational Support. The authors found that Perceived Organizational Support had a large, positive, overall effect on Organizational Commitment (aggregate) and Job Satisfaction. Our resulting hypotheses are:

  1. H4:

    Perceived Organizational Support is positively related to Organizational Satisfaction

  2. H5:

    Perceived Organizational Support is positively related to Job Satisfaction

5.3 Include social norms as a determinant of turnover intentions

One construct that was missing from the initial model but may be important is Social Norms. Ajzen and Fishbein (1980) define norms as “an individual’s perceptions of the social pressures put on him to perform or not to perform the behavior in question.” Among our interviews, nine Indian IS professionals mentioned pressure to reside in the same city as the family. We did not ask this question directly, yet it became a prominent theme during these nine interviews. This frequently trumped all other reasons for intending to stay or leave an organization. Four participants mentioned the importance of family/work life balance. Both types of family pressures are discussed below.

Family pressure to reside in the same city as the family

The participants did not claim that their family pressured them to remain or leave a particular organization, only to remain or leave a particular location. If the current organization was located near the family, the pressure was to remain. If the current organization was remotely located, the pressure was to relocate to the family. Below are some excerpts from the interviews to illustrate family location pressures:

  • –P2 (male) feels pressured to remain in Bangalore. While his family does not care which organization he works for, he states, “I am not willing to relocate to any other city. We generally live with our parents and it would be generally difficult to relocate to another part of the country.”

  • –P3 (female, married) does not like living in Delhi, but she moved back to Delhi to be near her husband’s family. “I have adjusted here but it was not my choice of place.”

  • –P10 (male) said, “My parents are dependent upon me. So I can’t go long distance because I have to go home every 15 to 20 days.”

  • –P20 (male) is working in Bangalore. Despite his high Organizational Commitment and medium Job Satisfaction, he intends to leave his organization within 6 months to move back home to Belgaum. He stated, “On a personal front, I am not happy. I want to spend more time with my friends and family in Belgaum... The only reason I want to leave is to make sure I spend more time with my family.”

Family pressure to balance work and family life

Four participants said that family pressures to better balance work and family life affected their turnover intentions. For example, P23 is a married female. She likes most aspects of her job, but the commute across Bangalore consumes too much time and she feels work/family conflict: “The days when your family needs you, I mean, lots of times, both [work and family] need you at the same time and it’s difficult to balance the two—work life and professional life. You can’t guarantee that you can leave work at 5:00. You could be late, it could extend for long hours.”

Given the strong family orientation of Indian culture, we believe that the inclusion of Social Norms is important to our study of Turnover Intentions among Indian IS professionals. In addition, Social Norms may include peer pressure in addition to family pressure. For example, P8 said: “When I talk to my friends and ex-colleagues they are saying S2 is a wonderful place to work, the culture, the atmosphere, the facilities and all these kind of things, we can’t match with any other company.” For the revised model, the construct is defined as follows:

Social Norms: The employee’s beliefs that family and peers think that he/she should remain with their current employer

And we hypothesize:

  1. H7:

    Social Norms is negatively related to Turnover Intention

6 Additional findings: Implications for practice

What do our participants’ 25 voices suggest for offshore outsourcing? For offshore outsourcing suppliers, the interviews reveal a number of interesting findings about the factors that affect intentions to leave an organization. For offshore clients, the interviews reveal some serious concerns.

  1. 1.

    Offer Indian IS professionals more interesting work rather than more money to increase Job Satisfaction and to reduce Turnover.

    Given the rising salaries among Indian IS professionals, we were interested to know how their perceptions of their current compensation affected their Job Satisfaction and ultimately Turnover Intentions. We asked four compensation questions pertaining to base salary, egalitarian bonuses (bonuses distributed equally among employees), performance based bonuses, and benefits such as healthcare. Among the 25 participants, seven felt they were underpaid, but only two of these seven had low Job Satisfaction. Fifteen participants were satisfied with their salaries even though they said they could increase their base salary if they left their current organization. Furthermore, all but one participant said they could easily get a job in another organization because of the strong demand for IS talent. It is clear that salary is not the main reason for changing organizations among our interviewees.

    Beyond compensation, a strong theme throughout the interviews was that Indian IS professionals want challenging jobs, just like their US/Western counterparts. Among the five professionals who were very dissatisfied with their jobs, four were mostly upset about the lack of task variety and low skill set utilization. For example, P1 complained:

    I have been put into testing and coding and now it is kind of maintenance phase. Now I am not able to use my skill set much. I am not satisfied with the kind of work I am doing. Every alternate day I go to my manager and I tell him that I am not satisfied with the kind of work I am getting and I need more challenging work so I can improve my skills.

    P2 complained about merely maintaining a client’s application. He says he just, “fixes errors in the application and monitors the jobs…I utilize only 20% of my knowledge.”

    Among the 14 professionals who were highly satisfied with their jobs, 12 mentioned task variety or skill set utilization as the major reasons for their satisfaction. In contrast to the previous participants, these participants talked enthusiastically about their jobs. For example, P15 reported high Job Satisfaction and mentioned direct contact with customers as a reason for his satisfaction: “Every software release or every major target, we are getting feedback from the customer as well as our managers.”

    P21 is a male working as software engineer. He stated: “My job is completely fulfilling. The challenges they throw at me. The challenges I get in my job. Like the technology with which I am working is really good and you get so many challenges each day. I do get a lot of variety. Like I send the proposal document, talk to the clients, and I even do development and testing.”

    Thus, while compensation matters, the type of work was a more important component of Job Attraction. Indian IS professionals preferred client-facing activities, design, and development work over application maintenance and support. This finding is troubling because many US clients justify offshore outsourcing by arguing that their internal IS staff should do more challenging work while offshore supplier employees can do more routine work. Clients might experience higher supplier turnover if they only offshore routine tasks such as monitoring and maintenance of existing systems or just outsource the coding or testing phases of new development.

  2. 2.

    Rotate Indian IS professionals from routine jobs within 18 months. What can suppliers do if routine tasks are the bulk of their clients’ work?

    Most of our Indian respondents were willing to tolerate routine work provided the supplier had a reliable career path that promised more interesting work in the future. We stress reliable because some respondents indicated that their managers made false promises about career opportunities. In contrast, employees from one major global supplier were very happy with an HR policy that allowed employees to get a job transfer every 18 months. They were more willing to execute routine tasks because they knew it was a stepping stone to more challenging jobs. Clients might also investigate supplier’s HR policies to determine the extent to which the supplier can motivate and retain their IS staff.

  3. 3.

    Caring HR policies can increase Job Satisfaction and Organizational Satisfaction among Indian IS professionals.

    While Indian IS professionals did not feel emotionally attached to their organizations, the extent to which they were satisfied with their organizations determined their Turnover Intentions. The good news is that suppliers have much control over the practices that affect employee Turnover Intentions. Indian IS employees want to remain with organizations that have supportive senior managers, supportive direct supervisors, fun and open cultures, and company policies such as flextime and the ability to occasionally work from home. This latter policy was particularly stressed by six participants who suffered long work commutes.

    Within the US IS literature, there are two important studies that suggest that collections of HR IS practices influence IS employee turnover (Ang and Slaughter 2004; Ferratt et al. 2005; Agarwal et al. 2006, 2007; Igbaria et al. 1994). Two studies identified five different IS HR configurations and found that the “Human Capital Focused Profile” was associated with the lowest turnover rates (10.3%) and that the “Incented Technician Profile” was associated with the highest IS turnover rates (19.9%; Ferratt et al. 2005; Agarwal et al. 2006). Organizations with a Human Capital Focused Profile implemented the most number of HR practices for work environment, career development, community-building initiatives, monetary incentives, and employment incentives.

  4. 4.

    Involve the family. Concerning Social Norms, what emerged from these interviews was a strong sense of family obligations.

    Primarily, Indian IS employees are obliged to live near their parents. This may suggest that suppliers are better off recruiting talent locally or relocating entire families for exceptional talent that currently resides afar. One small supplier moves entire families to his corporate campus in Hyderabad. While this practice is costly, the CEO said that family pressure to remain at his company is so strong, he can offer lower than market salaries and still retain most of his employees (Willcocks and Lacity 2006). Another Indian supplier involves the family in all corporate social functions such as bowling night and parties.

    Within the US literature, there has been some evidence that “family friendly HR policies” reduce turnover (Kopelman et al. 2006). Although these HR practices have not been tested in the Indian context, they might be of interest. These 21 practices are sick child days off, part time work, family leaves, flexible benefits, flexible time, flexible spending account, compensatory time, family picnic, family resource center, childcare subsidy, sick/emergency childcare, flexible place, compressed work week, work/family seminars, job sharing, onsite childcare, work/family support group, caregiver fair, after school program, summer camp, and adoption assistance (Mesmer-Magnus and Viswesvaran 2006).

7 Conclusions

Our research suggests a model of Turnover Intentions for Indian IS Professionals that differs from models that have been developed and tested on Western workers in general, and on Western IS professionals specifically. Models of Western IS professionals have generally found that Job Satisfaction, Organizational Commitment, and Work Exhaustion are the main determinants of Turnover Intentions. Among our Indian IS professionals, the concept of Organizational Commitment was troublesome. Many did not relate to the idea of an emotional bond with an organization. Instead, what emerged from these interviews was a strong sense of Social Norms from families and feelings of Organizational Satisfaction rather than Organizational Commitment. Some of these differences may be cultural. Prior research has shown, for example, that the Indian culture has much greater power distance and long term orientation and much lower individualism than say, the USA and Great Britain (Hofstede 2001). Although we are naturally cautious to extrapolate too much based on 25 interviews, we believe we have identified a solid model of turnover intentions of Indian IS professionals. Our ambition is to test our model with a large sample survey in the near future.