Moderating role of location autonomy on technostress and subjective wellbeing in information technology companies
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Author(s)Pallavi DattaLink to ORCID Index: https://orcid.org/0000-0003-3524-039X
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Sathiyaseelan BalasundaramLink to ORCID Index: https://orcid.org/0000-0001-9593-871X
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Sridevi NairLink to ORCID Index: https://orcid.org/0000-0002-1529-4297
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Rekha AranhaLink to ORCID Index: https://orcid.org/0000-0002-5853-6698
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DOIhttp://dx.doi.org/10.21511/ppm.22(2).2024.48
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Article InfoVolume 22 2024, Issue #2, pp. 615-626
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101 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
Integrating digital tools into day-to-day work activities has become an undeniable reality. However, the unprecedented reliance on technology has brought with it the escalating degrees of technostress evident through health concerns like chronic musculoskeletal problems and decreased job satisfaction. And the COVID-19 pandemic accelerated the negative impact, as IT industries adopted the hybrid workplace approach, especially in developing countries like India. This paper aims to find whether location autonomy moderates the effect of technostress on subjective wellbeing among IT employees working in a hybrid model. A purposive sampling method gathered 440 responses from IT professionals in Bengaluru tech parks. IBM SPSS and AMOS software were used to assess the constructs by SEM analysis, in line with the job demand-control theory. The results showed that location autonomy accounts for 31.6% of the variance in subjective wellbeing, while technostress explains 33.2% of the variance, with dimensions ranging from 21% to 46%. Additionally, location autonomy moderates and strengthens the link between technostress and subjective wellbeing. The study recommends that organizational leaders adopt HR policies that allow employees to choose their workplace rather than mandating a specific location for scheduled days in the week. This approach can potentially improve overall employee wellbeing, offering a favorable resolution to the challenges posed by technostress in the IT industry.
- Keywords
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JEL Classification (Paper profile tab)D23, M12, M14
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References65
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Tables7
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Figures1
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- Figure 1. Conceptual framework
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- Table 1. Demographic characteristics of the sample
- Table 2. Descriptive statistics
- Table 3. KMO and Bartlett’s test
- Table 4. Model fit (n = 440)
- Table 5. Construct validity measures
- Table 6. Reliability statistics
- Table 7. Analysis of hypothesized relationships with PLS path algorithm
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