In today’s fast-changing IT landscape, keeping talented employees engaged and committed is more critical than ever. This research sets out to understand how work–family integration, the atmosphere within organizations, and cognitive–emotional resources influence employees’ commitment to their companies in Tamil Nadu’s IT sector. Organizational commitment reflects how much employees connect with and support their employer’s values and objectives. By examining these factors, this study offers insights for IT organizations that want to build supportive cultures—helping people feel dedicated to their work and secure in their roles, which, in turn, boosts both productivity and organizational stability.

REVIEW OF LITERATURE

A large body of research has demonstrated how important thoughtful HR practices—like nurturing career growth, providing opportunities for learning, and designing effective compensation systems—are for positive employee outcomes. Within India’s highly competitive IT sector, there is increasing awareness that programs supporting employee wellbeing and smart talent management strategies are just as crucial as monetary rewards. These approaches help organizations keep their best talent, especially when the demand for skilled professionals remains high.

Previous research demonstrates that both psychological and organizational resources are fundamental drivers of employee commitment. For instance, self-efficacy (Bandura, 1997) empowers individuals to believe in their capacity to fulfill job tasks, which in turn promotes persistence and loyalty. Resilience enhances an employee’s ability to adapt to occupational stressors, thus supporting sustained organizational commitment (Luthans, 2002; Luthans et al., 2007). Wellbeing initiatives targeting health and happiness have been linked to enhanced productivity and reduced intent to leave (Robertson & Cooper, 2011). Moreover, organizational culture—shaped by collective values, traditions, and shared behaviors—has a direct impact on employee engagement and loyalty (Lok & Crawford, 2004).

Overall, these findings indicate that psychological resources and cultural dimensions are vital for organizational success, though most studies are based in Western organizational contexts. There is limited research specifically examining these interrelations in the Indian IT sector. This present investigation seeks to bridge that gap by empirically assessing the influence of work-life balance, organizational culture, self-efficacy, resilience, and wellbeing on the organizational commitment of IT employees in Tamil Nadu, utilizing structural equation modeling for validation.

Theory Integration

These findings become even more meaningful when seen through the lens of well-known organizational behavior theories. Social Exchange Theory (Blau, 1964) suggests that when employees feel their organization genuinely supports them—with things like work-life balance, a positive workplace culture, and wellbeing programs—they are more inclined to respond with loyalty and commitment. This kind of give-and-take relationship shows how psychological and organizational resources encourage people to stay dedicated to their work.

The study’s results also align with the Job Demands–Resources (JD-R) Model (Bakker & Demerouti, 2007). According to this framework, having strong job resources—like a supportive company culture, resilience, and self-efficacy—helps employees handle job pressures and boosts their engagement and commitment. Here, resilience and self-efficacy empower individuals to tackle everyday challenges, while wellbeing programs and a positive culture from the organization’s side help build a lasting sense of belonging.

By weaving together these established theories, this research not only affirms what previous models suggest but also expands their relevance in the context of the Indian IT industry. These insights contribute to a deeper, more practical understanding of what drives organizational commitment for today’s workforce.

Conceptual Framework Diagram

Participants and Procedure

The study’s sample comprised 150 employees from ten IT companies in Chennai, Tamil Nadu, selected through convenience sampling. Data collection utilized structured questionnaires encompassing demographics and key constructs including Work–family integration, Organizational climate, and Cognitive–emotional assets. Analysis involved SPSS and AMOS software for confirmatory factor analysis and path modeling to validate the relationships among variables.

DATA ANALYSIS

Table 1 Demographic profile of the respondent

The demographics of participants are presented in Table 1. The sample comprised 66.7% male and 33.3% female respondents. The largest age group was 31–40 years, representing 36.7% of the participants, followed by 41–50 years at 30%. In terms of work experience, 30% of respondents had less than 5 years of experience, another 30% had 10–20 years, while 20% each reported 6–10 years and above 20 years of work experience.

Figure 1 Conceptual framework – Measurement model

A confirmatory factor analysis (CFA) was conducted using AMOS to assess the measurement model. Factor loadings for all items exceeded the recommended threshold of 0.50, indicating acceptable construct validity. The overall model fit was evaluated using indices such as CMIN/df, GFI, CFI, TLI, SRMR, and RMSEA. All values fell within the acceptable ranges (e.g., CFI > 0.90, RMSEA < 0.08), confirming that the five constructs were well represented in the model.

Table 2 Model Fit measures

Figure 2 regression analysis

Path analysis in SPSS AMOS examines both direct and indirect relationships among variables within a model. Once the model is specified and data are provided, the program estimates parameters using algorithms such as Maximum Likelihood. Model fit is assessed through indices, and modifications can be applied when necessary. The output generates path coefficients that indicate the strength and direction of relationships. Commonly used fit measures include the Chi-square test, Comparative Fit Index (CFI), and Root Mean Square Error of Approximation (RMSEA). This approach enables researchers to capture complex variable interactions and draw inferences about their effects within a given context.

Table 3 Hypothesis Testing

Note: **p < 0.05. Only Work Culture showed a statistically significant effect on Organizational Commitment.

Path analysis indicated that, of the five proposed predictor variables, only organizational climate showed a statistically significant positive association with organizational commitment (β = 0.216, p = 0.011). This suggests that employees who perceive a supportive, values-oriented workplace culture are more likely to demonstrate loyalty and commitment to their organization. In contrast, the results did not find statistically significant effects for work–family integration or for cognitive–emotional assets (resilience, self-efficacy, and employee wellbeing) in this dataset, although theory suggests these may be important in other contexts. Their comparatively low critical ratio (C.R.) values imply that while such factors can be influential in the broader literature, their direct effects were insufficient within this sample to attain statistical significance.

Findings:

The analysis identifies organizational climate as the only predictor with a significant positive effect on organizational commitment. This supports the idea that a value-driven and supportive organizational atmosphere encourages employee loyalty. Although work–family integration and cognitive–emotional resources yielded positive coefficients, they did not reach statistical significance in this analysis. This outcome indicates that, despite their established theoretical relevance, the immediate impact of these factors on organizational commitment may be contingent upon additional, context-specific variables.

Path analysis confirmed the significant role of Organizational climate in enhancing Organizational Commitment (β = 0.216, p = 0.011). Other variables—Work–family integration and Cognitive–emotional assets (Resilience, Self-Efficacy, and Employee Wellbeing)—showed positive but statistically non-significant relationships with commitment. This highlights the centrality of cultural factors in the US based Tamil Nadu IT sector, where shared values, supportive practices, and organizational norms strongly influence employee dedication.

CONCLUSION

This study contributes to literature by highlighting that, in the US based Tamil Nadu IT sector, organizational climate & culture is the primary driver of employee commitment. For practice, the study guides HR managers to prioritize cultural development over individual psychological resources.

While factors such as Work–family integration and Cognitive–emotional assets (Resilience, Self-Efficacy, and Employee Wellbeing) are widely discussed in the literature, they did not emerge as statistically significant in this study. For HR managers, this emphasizes the importance of cultivating a positive organizational culture through transparent communication, supportive leadership, and value alignment. Future research with larger and more diverse samples could further explore whether psychological factors like resilience and self-efficacy play stronger roles in different organizational contexts.

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