Impact of employee satisfaction, work flexibility and organisational support on employee productivity in a hybrid work model: a post-pandemic study among IT professionals in Kerala

The COVID-19 pandemic has fundamentally transformed the world of work, compelling organisations to rapidly adapt to unprecedented challenges (Kniffin et al., 2021; Kamis, Abd. Rahim, Yusoff, Azilah Husin, & Yuliviona, 2023). Among the most significant changes is the widespread adoption of the hybrid work model, a flexible approach that blends remote and on-site work to offer resilience and adaptability (Smite, Moe, Hildrum, Huerta, & Mendez, 2023). Even before the pandemic, some companies had begun to explore flexible work arrangements as a means to attract talent, boost productivity, and enhance work-life balance. However, the shift to remote work was gradual, with many organisations hesitant to fully embrace it due to concerns about productivity and management. The pandemic's onset in early 2020 forced millions of employees worldwide into remote work, accelerating this transition and highlighting the potential benefits of hybrid work models.

This shift towards hybrid work has brought about a profound transformation in productivity dynamics, a topic extensively explored by researchers (Morikawa, 2023; Andrade, Andrews, & Sato, 2024). The productivity dynamics of hybrid work can be understood through several key aspects. The hybrid work model has become increasingly prominent due to its ability to provide employees with greater flexibility, allowing them to manage their work-life balance more effectively. This model enables employees to create work environments that align with their preferences, reducing distractions and fostering focused work (Kumari, 2023). Moreover, the autonomy and trust embedded in hybrid work can increase employee engagement, motivation, and overall performance, ultimately benefiting organisations. As a result, the hybrid work model is increasingly seen as a compelling vision for the future of work, offering enhanced productivity and access to a diverse talent pool (Chafi, Hultberg, & Yams, 2022; Mildawani & Wonte, 2024).

However, the impact of hybrid work is not uniform across all industries and roles. Andrade et al. (2024) found that job sector and employee position significantly influence how hybrid work affects productivity. Their research highlights the need for tailored strategies that consider the unique demands of each industry and role. To fully harness the potential of hybrid work, organisations must move beyond a one-size- fits-all approach and develop customised frameworks that align with the specific needs of their workforce. Wang, Liu, Qian, and Parker (2021) suggested that organisations must intentionally redesign tasks and provide socio-technical support to sustain high performance in hybrid and remote environments. According to Choudhury, Foroughi, and Larson (2021), work from anywhere (WFA), a version of traditional work from home (WFH), offers both temporal and geographical flexibility that leads to measurable productivity gains.

Despite the growing acceptance and implementation of hybrid work models, a critical gap remains in understanding how key factors such as employee satisfaction, organisational support, and work flexibility directly influence productivity in this new work paradigm. While the advantages of hybrid work are well-documented, limited empirical research explores the specific dynamics of how these elements interact to shape productivity within hybrid settings. This gap is particularly significant as organisations seek to optimise strategies for employee engagement, retention, and overall well-being in a post-pandemic world.

The current research addresses this gap by thoroughly analyzing the relationships between employee satisfaction, organisational support, work flexibility, and productivity in hybrid work environments. By investigating these factors, this study seeks to provide insights that will help organisations develop tailored policies and practices that promote a healthier work-life balance and enhance overall productivity. To achieve the objective, the study selected the IT sector in Kerala, where hybrid work models are increasingly adopted during the post-pandemic period, as the study context. The expected contribution of this study is twofold: it will advance academic understanding of the hybrid work model's impact on productivity and offer practical guidance for organisations striving to create sustainable and fulfilling work environments in a rapidly changing world.

With the increased use of hybrid work settings, knowing how employee satisfaction, organisational support, and work flexibility affect employee productivity in hybrid settings is crucial. Such research can shed light on how employees manage their time, tasks, and responsibilities in blended work employment, hence influencing their overall well-being and happiness. Furthermore, researching the aftereffects of this blended work on productivity among employees helps organisations optimise strategies, employee engagement, and retention. By identifying the influence of employee satisfaction, organisational support, and work flexibility on employee productivity associated with hybrid work, organisations can develop tailored policies and practices that promote a healthier work-life balance for their workforce, eventually contributing to a more sustainable and fulfilling work environment.

In this post-pandemic world, employees have voiced a clear preference for flexible work hours and the ability to choose their work location, signalling a shift in priorities. This growing emphasis on flexibility reflects not just a desire for convenience, but a deeper understanding of the link between work conditions and overall well-being (Krajčík et al., 2023). Organisations, recognising the direct connection between employee productivity and well-being, have responded by increasingly adopting hybrid work models. These models aim to balance the benefits of remote work with the need for in-person collaboration, emphasising mental health, engagement, and organisational support (Suhariadi et al., 2023).

The hybrid work model, however, is not without its challenges. In Karnataka, a study focused on IT professionals revealed the complexities of flexible work arrangements. While the model supports productivity and commitment, it also requires significant adjustments in both working styles and physical workplaces to meet the evolving demands of employees (Vanitha & Shailashri, 2023; Kamis et al., 2023). Yet, even as employees enjoy the perks of flexibility, some report stress due to reduced job clarity and social isolation, underscoring the need for thoughtful implementation. In the education sector, the shift to online hybrid teaching has introduced complex challenges, particularly regarding the development of graduate attributes. Thoughtful course design and faculty development are now crucial in harnessing the potential of blended learning environments while preserving the strengths of traditional face-to-face instruction (Castaneda, Japos, & Templonuevo, 2022; Gamage, Jeyachandran, Dehideniya, Lambert, & Rennie, 2023). The corporate world, too, finds itself at a crossroads. The hybrid work model, while promising enhanced productivity and team spirit, raises concerns about efficiency, company culture, and career progression. It demands a renewed focus on employee mental well-being, clear boundaries, personal time, and individual motivation to prevent mental health struggles (Muskan & Trivedi, 2023; Kumari, 2023). Key ingredients for a thriving hybrid work environment include work-life balance, flow experiences, and strong organisational support—all of which significantly impact perceived productivity and long-term commitment (Aprilina & Martdianty, 2023).

As remote work becomes increasingly viewed as a right rather than a privilege, a paradigm shift in the employer-employee dynamic is underway (Setiyono, Rahmita, & Fuzail, 2024; Solihah, Intan, Sugiarto, Marini, & Setiawan, 2025). This transformative shift is reshaping the corporate landscape, with more companies embracing hybrid and remote work models. However, some organisations may revert to traditional setups if the new models fail to meet expectations (Smite et al., 2023; Barrero, Bloom, & Davis, 2023).

The pandemic's rise of remote work has led to fragmented and diverse understandings of the phenomenon. To bridge this gap, recent studies have employed AI and machine learning to analyze existing research, revealing that balanced hybrid structures are associated with improved flexibility and innovation. However, these structures must also address potential concerns about social isolation (Aleem, Sufyan, Ameer, & Mustak, 2023; Choudhury, Khanna, Makridis, & Schirmann, 2022). Further, hybrid work's impact extends beyond the workplace, influencing non-work-related activities during work hours, which requires careful consideration of individual and company-specific influences (Caros, Guo, Zheng, & Zhao, 2023). For instance, in the nursing profession, the importance of enhancing work flexibility through hybrid schedules became evident during the pandemic, improving both quality of life and work-life balance (Farber, Payton, Dorney, & Colancecco, 2023).

In emerging markets like the UAE, remote work during the pandemic significantly affected employee relations, highlighting the importance of prioritising flexible work arrangements to foster positive relationships between employees and their organisations (Kurdy, Al-Malkawi, & Rizwan, 2023). The hybrid work environment also impacts employee performance, with digital tools playing a crucial role in bridging the gap between traditional office tasks and flexible schedules (Chellam, 2022). As employees are given the freedom to choose their preferred work environments—whether at home, a coffee shop, or the office—a seamless blend of work locations has emerged, offering numerous benefits. However, traditional work styles and physical offices persist alongside these new models, particularly in roles requiring manual labour (Vidhyaa & Ravichandran, 2022; Vyas, 2022). The nature of work flexibility, evolving in response to the pandemic, has become increasingly relevant. Research suggests that allowing individuals to personalise their work arrangements based on “core” hours and preferred locations enhances flexibility and employee satisfaction (Shirmohammadi, Au, & Beigi, 2022; Kossek & Kelliher, 2023).

However, hybrid work also demands strategies to support emotional, spiritual, financial, and mental health, which are more critical when working outside the office (Bolisetty, Sharma, & Bhattacharya, 2023). The experience of working from home has significantly influenced employees' perceptions of fairness and trust towards their supervisors, shaping their emotional connection to the organisation (Lott & Abendroth, 2023). In the broader context of planning and workplace design, the concept of “hybridization” is deeply analyzed, focussing on how spatial, functional, social, and digital elements interact in the evolving work environment (Di Marino, Tabrizi, Chavoshi, & Sinitsyna, 2023). Flexibility within the gig economy, for instance, varies across platforms, significantly impacting workers' control over their work (Dunn, Munoz, & Jarrahi, 2023). As organisations explore the potential ramifications of increased remote work and the acceptance of satellite offices, the demand for traditional office spaces post-pandemic remains a key area of interest (Hensher, Wei, & Beck, 2023). The pandemic prompted a reassessment of work life, revealing the significant impact of work-from-home arrangements on various facets of work (Kagerl & Starzetz, 2023). Yet, remote work can also be a source of anxiety and stress due to limited social interaction, blurred work-life boundaries, and a lack of workplace motivation (Prasad, Vaidya, & Rani, 2023). On the flip side, sustained “problem-oriented discussions” have proven more effective in cultivating long-term collaborative research in hybrid work settings (Xu, Sarkar, & Rintel, 2023). Leadership in virtual environments is evolving, with traditional functions being complemented by a new emphasis on supporting technology utilisation (Bell, McAlpine, & Hill, 2022). While flexible work arrangements are linked to slight positive impacts on employee mental well-being, more studies are needed to assess these health outcomes accurately (Shiri et al., 2022). As hybrid workers navigate significant fluctuations in their lives, the model highlights both its advantages and challenges. Non-remote workers, however, show higher disengagement levels, a critical factor in job burnout (Stasiła-Sieradzka, Sanecka, & Turska, 2023).

In European nations, work-life balance during the COVID-19 pandemic was influenced by individual resilience and perceived organisational support, underscoring the importance of remote work in maintaining well-being (Ferreira & Gomes, 2023). Leaders' core self-evaluations and work autonomy significantly impact the relationship between telework and work-life balance, with those possessing low resources benefiting most from remote work (Neidlinger, Felfe, & Schübbe, 2023). The effects of work-from-home arrangements on productivity in Dubai's consulting sector reveal both challenges and benefits, with notable progress in employee performance observed (Rañeses, Nisa, Bacason, & Martir, 2022). The type of work significantly influences employee behaviour, with role definition and control being crucial factors for onsite workers (Wontorczyk & Rożnowski, 2022). As the pandemic permanently alters work practices, giving employees more autonomy over where and when they work, the importance of regular remote meetings and maintaining team cohesion becomes evident (Brooks, Hall, Patel, & Greenberg, 2022; Krishnan, Neha, Samsudeen, & Ummah, 2025). Flexible work environments, incentives, and work-life balance are increasingly significant in enhancing organisational appeal and job pursuit intention, with work-life flexibility playing a crucial role (Bauer, Nadler, Bartels, & Berkley, 2017). Finally, the perception of working from home, particularly in terms of parenthood and gender-specific discourses, is analyzed across different stages in countries like the United Kingdom and Germany, offering insights into the evolving landscape of work (Homberg, Lükemann, & Abendroth, 2023).

In India, the HR implications of hybrid work settings are explored through a proposed HRM framework, offering guidance for smooth implementation in the workplace (Verma, Venkatesan, Kumar, & Verma, 2023). The future of sustainable work environments will depend on balancing the benefits and challenges of hybrid and remote work models, with rising autonomy, performance, and work-life balance being key benefits, while social isolation remains a significant drawback (Chafi et al., 2022). As industries continue to adapt, the strengths and weaknesses of work flexibility are increasingly recognised. This ongoing evolution in work settings highlights the need for reorienting training practices and extending key performance indicators to protect employees (Januszkiewicz, 2019; Pillai & Prasad, 2023). Post-pandemic studies emphasise the changing perceptions of knowledge workers towards physical work settings and remote work practices, with significant shifts observed during the pandemic (Yang, Kim, & Hong, 2023). The banking sector, for example, is experiencing a blended work approach, with the implementation of e-culture highlighting the need for digital transformation and corporate change (Ainurrofiq & Amir, 2023). Work motivation and work-family conflict play a mediating role in the relationship between work flexibility and remote work, with family conflict acting as a significant link (Al Riyami, Razzak, Al-Busaidi, & Palalic, 2023). Gender disparities in research outputs during the pandemic also underscore the importance of flexible policies, particularly valued by female researchers (Zvavahera & Chirima, 2023).

Despite growing scholarly attention to hybrid work models, the literature remains fragmented in explaining the specific antecedents of productivity in post-COVID contexts. Prior studies have predominantly examined remote work and telecommuting (Bloom, Liang, Roberts, & Ying, 2021; Waizenegger, McKenna, Cai, & Bendz, 2020), with limited focus on the hybrid model as a distinct arrangement. Moreover, while organisational support, work flexibility, and employee satisfaction have individually been linked to employee outcomes such as engagement, retention, and well-being (Bakker & Demerouti, 2007; Judge, Thoresen, Bono, & Patton, 2001), their combined influence on productivity has not been systematically investigated. In particular, empirical research in emerging economies such as India—where hybrid work adoption has accelerated after COVID-19—remains scarce. This study addresses this gap by developing and testing a conceptual model that integrates these three antecedents to explain productivity in hybrid work environments within the Indian IT sector.

This study deliberately focuses on three key antecedents – organisational support, work flexibility and employee satisfaction - as they represent the most critical and contextually relevant drivers of productivity in hybrid work settings. Organisational support is vital in mitigating the demands of remote and hybrid work (Bakker & Demerouti, 2007). Work flexibility reflects the autonomy to structure work schedules and environments, a defining feature of the hybrid work model that directly influences engagement and efficiency (Bloom et al., 2021). Employee satisfaction represents an attitudinal factor linked to motivation and retention, offering insights into the long-term sustainability of hybrid work arrangements (Judge et al., 2001). By restricting the model to these three antecedents, the study maintains conceptual clarity and empirical focus while addressing the Indian IT sector's urgent need to identify practical levers of productivity in the post - COVID period.

The extensive literature revealed the bonds between organisational support, work flexibility, employee satisfaction and employee productivity. Based on this information, a conceptual model (Figure 1) is developed to test the statistical significance in the Indian context. The model is anchored in the Job Demands–Resources (JD-R) framework (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001; Bakker & Demerouti, 2007), which asserts that employee outcomes, including productivity, are shaped by the balance between job demands and the availability of job resources. Within hybrid work arrangements, organisational support and work flexibility function as essential job resources that help employees manage demands, alleviate strain, and sustain performance. Simultaneously, employee satisfaction represents a positive attitudinal state that can enhance productivity by strengthening motivation, commitment, and engagement (Judge et al., 2001). Given the study's deductive approach, grounded in existing theory and prior empirical findings, a quantitative research design was adopted to test the proposed hypotheses. This approach enables the systematic measurement of variables and statistical analysis of their relationships, providing objective evidence to evaluate the propositions.

Employee productivity indicates a measure of how well employees get things done. It considers both the quantity of work (how much) and the quality of work (how well) about the time and resources they have. Contrary to initial concerns about productivity in remote work settings, many studies have shown that employees can be as productive as on -site or more productive when working remotely (Aprilina & Martdianty, 2023). Employees who have work flexibility can be more productive (Yang et al., 2023). While working from home, employees can balance their professional and personal lives by managing time, which leads to the enhancement of their level of productivity (Bolisetty et al., 2023). Access to a broader talent pool can enhance innovation and creativity, driving organisational growth and competitiveness in an increasingly globalised world.

Organisational support refers to the assistance, motivation, and resources provided by an organisation to help employees succeed in their roles and achieve organisational goals. It encompasses various forms of support, including financial, technical, and psychological assistance, all of which are particularly critical in facilitating effective work-from-home arrangements (Montreuil & Lippel, 2003). Key elements of support in remote work contexts include access to appropriate technology, clear work pattern guidelines, and ergonomic furniture resources that collectively enhance employee performance and productivity (Yang et al., 2023). Given these factors, organisational support plays a pivotal role in shaping both employee satisfaction and productivity in hybrid or remote work settings. Specifically, perceived organisational support significantly influences employee satisfaction, which in turn affects productivity. However, financial support, while positively associated with increased productivity, does not appear to have a direct impact on employee satisfaction (Bakker & Demerouti, 2007). These findings underscore the multifaceted nature of organisational support in remote work environments.

Employee satisfaction is the outcome of the experience of employees who feel that they are happy at their job. The work-from-home (WFH) program enhanced satisfaction among employees by minimising the stress of the employees, which in turn led to a reduction in the number of employees who were fired (Gajendran & Harrison, 2007). The more comfortably an employee can work, the easier it is to do the job (Golden & Veiga, 2005). The autonomy to choose the work location and time leads to the satisfaction of employees (Yang et al., 2023)

Work flexibility refers to a circumstance in which an employee has a choice of where, when and how many hours they can spend on work-related tasks (Hill et al., 2008). It seeks to enhance the degree to which employees can surpass their limits. The flexibility of work leads to the productivity of employees and their job satisfaction when engaging in remote work (Yang et al., 2023). Flexible work settings can also increase the worker's motivation and involvement in work (Setiyani, Djumarno, Riyanto, & Nawangsari, 2019). Productivity among workers is positively influenced by flexible work settings (Onyekwelu, Monyei, & Muogbo, 2022).

Research design is a comprehensive way that researchers use to conduct research systematically and logically by adopting the right methodological tools and procedures. This includes developing appropriate sampling plans, collecting data, and analyzing data using the most suitable statistical tools. An explanatory research design is used, including an extensive literature review intended to formulate an appropriate hypothesis describing the relationship between variables. The scales for measuring the variables are adopted from previous studies (Yang et al., 2023; Gremler & Gwinner, 2000).

The study focuses on IT professionals working in the state of Kerala, India, representing a wide range of functional roles and experience levels within the sector. Kerala was deliberately selected due to its well-established IT ecosystem, which includes major technology hubs such as Technopark (Thiruvananthapuram), Infopark (Kochi), and Cyberpark (Kozhikode), and its early and widespread adoption of hybrid work practices during and after the COVID-19 pandemic. The state exhibits a high level of digital infrastructure, workforce literacy, and organisational readiness, making it a suitable and information-rich context for examining hybrid work dynamics in an emerging economy. Moreover, the IT sector in Kerala mirrors many structural and operational characteristics of the broader Indian IT industry. As such, insights derived from this setting offer meaningful implications for comparable IT-intensive regions across India, while also allowing for contextual sensitivity. Any IT professional in Kerala with experience in a hybrid work arrangement was therefore considered an appropriate sampling unit for this study.

The widely accepted guideline for determining an appropriate sample size in structural equation modelling suggests a minimum of five to ten observations per indicator variable (Bentler & Chou, 1987). Accordingly, the minimum sample size for this study is set at 210, which is ten times the number of indicator variables. Any additional participants beyond this threshold will enhance the precision of parameter estimates.

The study employed a purposive sampling strategy to identify and recruit participants, particularly suited for accessing the niche population within Kerala's Information Technology (IT) industry. The inclusion criteria encompassed individuals of all genders, various age groups, and a range of experience levels, ensuring a diverse and representative sample.

The study employed a structured questionnaire comprising two sections for data collection. The first section was designed to gather demographic information, including work experience, while the second section focused on capturing employees' perceptions of satisfaction, organisational support, work flexibility, and productivity. Perceived organisational support was measured using a six-item scale (Yang et al., 2023). Job satisfaction was assessed using five items (Gremler & Gwinner, 2000), while work flexibility was evaluated with a four-item scale (Yang et al., 2023). Productivity was measured using a seven-item scale (Yang et al., 2023).

The majority of responses were collected from major IT hubs across Kerala. To enhance the breadth and representativeness of the sample, online survey questionnaires were also distributed via email to IT professionals within the researchers' networks. A total of 268 completed questionnaires were received. Five incomplete responses with missing data were excluded from the statistical analysis.

Quantitative data obtained from the survey is analyzed using the statistical software IBM SPSS statistics and IBM Amos. Descriptive statistics is employed to summarise participant demographics and the mean scores of the study variables.

Table 1 shows that 51% of the sample is from the female category, while 39% belongs to the male category. More participants (51%) are within the age group 21–30 years. The majority of the participants have work experience below two years (38%). Only 12% of respondents have experience of more than 8 years. Fifty-nine percent belong to the non-executive category, while the rest (41) belong to the executive group.

IBM SPSS Statistics is used for conducting descriptive analysis. Mean values for the four variables are above 4 and less than 5. This shows that the majority of the participants are on the positive side and satisfied to a certain level with all the attributes. The kurtosis and skewness are examined through descriptive statistics. While using SEM, the values acceptable for skewness range from −2 to +2, and for kurtosis, from −7 to +7 (Kline, 2012; Byrne, 2010). Table 2 shows that the skewness and Kurtosis are within the acceptable levels, and it indicates the normality of the data. The bivariate correlation between the variables ranges from 0.549 to 0.721 and indicates the absence of multicollinearity across the variables.

Structural Equation Modelling (SEM) is a second-generation statistical technique that is applied to understand the linkage between multiple variables. This method helps researchers to know the complexity of theoretical models that depict how the variables are interconnected to each other. In this study, SEM is used to assess the impact of predictor variables on the predicted variable. SEM has 2 stages: measurement model assessment, which is also called CFA analysis, and structural model assessment. The CFA analysis checks the reliability and validity of the scale, which measures constructs. The Structural model assessment tests the significance of multiple relationships between variables.

The validity of the scale that measures the attributes is assessed through measurement model assessment (confirmatory factor analysis). A model which consists of 4 latent variables is correlated, and measurement model assessment is done with the help of IBM SPSS Amos. Two indicator variables, one each from employee productivity and work flexibility, are eliminated from the model to achieve the model fit as recommended. As given in Table 3, four out of seven fit measures have adequate fit, and the other three are very close to the fit measures recommended. (Hu & Bentler, 1999; Lomax, 2004). Therefore, the measurement model is good for statistical analysis since it has sufficient fitness with the data.

The reliability of items is assessed by thoroughly analyzing the factor loadings. The factor loadings above 0.7 and squared multiple correlation (SMC) greater than 0.5 are considered good for indicator reliability. All the items except three have factor loadings equal to or more than 0.7 which are shown in Table 4.

To ensure the construct reliability, composite reliability and Cronbach's alpha are used. A value greater than 0.7 is recommended for both these measures to ensure sufficient construct reliability. In this study, all constructs have CR and Cronbach's alpha greater than 0.8, which confirms a good level of internal consistency reliability of measurement scales for all constructs.

The validity is assessed by evaluating two subset validity measures called discriminant and convergent validities. The average variance extracted (AVE) above 0.5 is recommended to ensure a sufficient level of convergent validity for the measurement scale. In this research AVE values for all the four constructs are above 0.5. To ensure discriminant validity, the method recommended is to compare the square root of the AVE of each construct with the intercorrelations of that construct with the other constructs. Where the square root of AVE is greater than the intercorrelations, it satisfies the presence of sufficient discriminant validity of the construct. Here, as Table 5 shows, the square roots of AVE (the diagonal italic values) of each construct are greater than the below-provided intercorrelations. This confirms the presence of adequate discriminant validity.

In structural model (Figure 2) assessment, researchers assess the magnitude and direction of the path coefficients. The joint explaining power of the predictor variables is also assessed to decide on the fitness of the proposed model with the data. In this study, the R² value that shows the explaining power of the predictor variables is found to be excellent. Eighty per cent variation of the dependent variable could be explained by the three predictor variables. Hence, it is assumed that the study model has an excellent fit with the data and is good for further analysis.

Table 6 reports the structural model estimates, including unstandardised (B) and standardised coefficients (β), critical ratios (CR), and significance levels (p-values). Rather than merely indicating statistical significance, the results reveal a clear hierarchy among the predictors of employee productivity in hybrid work settings. Specifically, perceived organisational support and work flexibility emerge as the primary drivers of productivity, while employee satisfaction plays a comparatively weaker - though still meaningful - direct role.

Perceived organisational support emerges as the strongest predictor of employee productivity (β = 0.36, p < 0.001), providing robust support for Hypothesis H1. This finding highlights that productivity in hybrid work contexts is largely contingent upon the extent to which organisations offer adequate resources, effective managerial guidance, reliable technologicalinfrastructure, and psychological reassurance. Rather than being driven primarily by individual dispositions, employee performance in hybrid settings appears to be shaped by the broader organisational environment in which work is embedded. When employees perceive high levels of organisational support, they are better positioned to navigate coordination challenges, role ambiguity, and communication complexities that are inherent in hybrid work arrangements. These observations are consistent with prior empirical research highlighting the importance of organisational support in improving employee and organisational performance (Shirmohammadi et al., 2022; Yang et al., 2023; Toscano, González-Romá & Zappalà, 2024).

Work flexibility represents the second strongest predictor of productivity (β = 0.33, p < 0.01), lending support to Hypothesis H2. This result underscores the importance of autonomy over work location and scheduling in sustaining performance. Flexible work arrangements enable employees to align work demands with personal rhythms and non-work responsibilities, thereby reducing strain and conserving cognitive resources. In hybrid environments, where employees frequently transition between remote and on-site work modes, such autonomy becomes particularly salient in maintaining focus, creativity, and task efficiency (Bloom et al., 2021; Yadav & Bagri, 2025).

Although employee satisfaction exhibits a statistically significant relationship with productivity (β = 0.29, p < 0.001), it exerts the weakest direct effect, supporting Hypothesis H3. This pattern suggests that satisfaction alone does not automatically translate into enhanced performance unless it is reinforced by tangible organisational support and flexible work structures. From a theoretical perspective, this finding challenge traditional assumptions about the satisfaction–performance linkage by indicating that, in hybrid work contexts, employee satisfaction operates more as a psychological outcome of supportive and flexible working conditions than as an independent driver of productivity (Rajeswari & Venugopal, 2024; Kumari, Shukla, & Mishra, 2025).

These results can be coherently interpreted through the Job Demands–Resources (JD–R) model (Demerouti et al., 2001; Bakker & Demerouti, 2007). In hybrid work environments, organisational support and work flexibility operate as critical job resources that enable employees to cope with elevated job demands such as digital overload, coordination complexity, and blurred work–life boundaries. Organisational support mitigates these demands by providing structural and emotional resources, while work flexibility enhances autonomy, a key motivational resource within the JD–R framework. Employee satisfaction, in contrast, represents an outcome of this resource-rich environment rather than a direct driver of performance.

The dominance of organisational support as a predictor is particularly instructive in the Indian IT context, where hybrid work often coincides with high workload intensity, global client interactions, and extended working hours. In such settings, productivity gains are unlikely to materialise without explicit organisational investment in systems, leadership practices, and employee well-being. These findings are consistent with prior empirical evidence highlighting the centrality of organisational and job-level resources in shaping productivity under hybrid and flexible work arrangements (Rajeswari & Venugopal, 2024; Gibbs, Mengel, & Siemroth, 2024; Toscano et al., 2024).

Overall, the hypothesis-driven analysis demonstrates that productivity in hybrid work models is best explained by a resource-based perspective rather than by attitudinal factors alone. A balanced organisational strategy that integrates strong support systems, flexible work arrangements, and satisfaction-enhancing practices is therefore essential for optimising productivity and sustaining performance in hybrid work environment.

The findings of this study offer clear guidance for managers seeking to enhance employee productivity in hybrid work environments. First, the strong direct effect of perceived organisational support on productivity highlights the critical role of managerial actions in enabling performance. Managers should ensure that employees have consistent access to technological resources, clear work processes, and responsive supervisory support. Regular communication, timely feedback, and visible managerial availability are essential for reducing uncertainty and coordination challenges inherent in hybrid work. Investing in leadership training that strengthens managers' ability to support distributed teams can further improve productivity outcomes.

Second, the significant influence of work flexibility on productivity underscores the importance of granting employees autonomy over when and where they work. Managers should implement structured flexibility policies that balance autonomy with accountability by clearly defining performance expectations and deliverables. Shifting the focus from monitoring work hours to evaluating outcomes can help sustain productivity while preserving employee trust. Importantly, flexibility arrangements should be applied consistently across teams to avoid perceptions of unfairness that may undermine performance.

Third, the positive relationship between employee satisfaction and productivity suggests that managers cannot overlook employees' affective experiences, even in performance-driven hybrid settings. Practices such as recognition, career development opportunities, and regular feedback can enhance satisfaction and, in turn, support sustained productivity. Managers should actively monitor satisfaction levels and respond proactively to emerging concerns, particularly in hybrid teams where disengagement may be less visible.

In summary, the results indicate that productivity in hybrid work models can be strengthened through a coordinated managerial approach that combines strong organisational support, well-designed flexibility, and sustained attention to employee satisfaction. Managers who align these practices with organisational objectives are more likely to build a resilient, engaged, and high-performing hybrid workforce.

This study examined the direct effects of perceived organisational support, work flexibility, and employee satisfaction on employee productivity within hybrid work arrangements in the Indian IT sector. The findings provide clear empirical evidence that productivity in hybrid contexts is not driven by a single factor but is shaped by a combination of structural, behavioural, and attitudinal conditions embedded in the organisational environment.

Among the three predictors, perceived organisational support emerged as the strongest determinant of employee productivity. This underscores the central role of organisational resources, managerial guidance, and psychological reassurance in enabling employees to perform effectively in hybrid settings. When employees perceive that their organisation actively supports their work through adequate infrastructure, clear communication, and responsive leadership, they are better equipped to manage the coordination demands and role complexities associated with hybrid work. Work flexibility also demonstrated a significant and positive effect on productivity, highlighting the value of autonomy over work schedules and locations. Flexible work arrangements allow employees to align professional responsibilities with personal needs, reduce strain, and sustain focus and efficiency. In hybrid work environments, where employees alternate between remote and on-site modes, such flexibility appears particularly important for maintaining consistent performance. Employee satisfaction, while exhibiting a comparatively weaker direct effect, remained a significant predictor of productivity. This finding suggests that positive work attitudes contribute meaningfully to performance, even if their impact is less pronounced than structural and autonomy-related factors. Satisfaction enhances motivation and commitment, thereby supporting sustained productivity over time.

Overall, the study reinforces the view that employee productivity in hybrid work models is primarily shaped by organisational practices and managerial design choices. By strengthening organisational support, institutionalising meaningful flexibility, and fostering employee satisfaction, organisations can create hybrid work systems that sustain high levels of productivity in the evolving world of work.

This study focused on three predictor variables concerning productivity, which together explained 80% of the variation in the dependent variable. However, incorporating additional predictors could further enhance the explanatory power of the model. Future research should explore other potential determinants, such as leadership styles, technological adoption, and employee well-being, to provide a more comprehensive understanding of productivity drivers.

Additionally, the study was geographically confined to Kerala, limiting its generalisability to other regions. Expanding the research to include diverse samples from multiple states or different industry sectors would offer broader insights and improve the external validity of the findings. Furthermore, given the strong connection between the hybrid work model, work-life balance, and employee satisfaction, future studies could investigate gender and age differences in these dynamics. Such research would yield valuable insights for developing more inclusive organisational strategies that optimise performance while addressing diverse workforce needs.