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Personal attributes and job resources as determinants of amount of work done under work-from-home: empirical study of Indian white-collar employees
International Journal of Manpower ; : 20, 2022.
Article in English | English Web of Science | ID: covidwho-1883095
ABSTRACT
Purpose Even after COVID-19 pandemic, several organizations intend extending work-from-home (WFH), to the extent of making it permanent for many. However, WFH's impact on productivity remains uncertain. Therefore, this paper aims to study personal and job factors determining the likelihood of amount of work done at home being same/more vis-a-vis office. Design/methodology/approach Employees' basic psychological needs and job crafting tendencies;job-related aspects of task independence, technology resources and supervisory support;and several demographic factors are examined as determinants. Firth logistic regression analysis of data from 301 Indian white-collar employees is performed. Findings Demographically, longer exposure to WFH, greater work experience and being a support function worker increased the likelihood of same/greater amount of work done at home. Being a woman or married reduced the likelihood, while being a manufacturing/services worker was non-significant. Among psychological needs, greater needs for autonomy and relatedness decreased and increased the likelihood of same/greater amount of work done at home, respectively. Regarding personal and job resources, job crafting to increase structural job resources and supervisor support increased the likelihood of same/greater amount of work done at home versus office. Originality/value This paper adds to the limited India-centric literature on WFH;uniquely examining influences of individual personal attributes on amount of work done by combining job demands-resources (JD-R) model and basic psychological needs theory.
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Full text: Available Collection: Databases of international organizations Database: English Web of Science Language: English Journal: International Journal of Manpower Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: English Web of Science Language: English Journal: International Journal of Manpower Year: 2022 Document Type: Article