Measuring autonomy in hybrid work: scale development

衡量混合工作模式下的自主性:量表开发

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Abstract

BACKGROUND: Autonomy is a core element in many established management theories, consistently linked to positive employee outcomes. However, the COVID-19 pandemic and rapid technological advancements have transformed workplace dynamics, particularly in the information technology (IT) sector in India, where hybrid work models have gained prominence. Despite this shift, no standardized measure exists to assess the autonomy experienced by employees in hybrid work environments, hindering deeper analysis and understanding. OBJECTIVE: This study aims to contextualize, develop, and validate the Autonomy in Hybrid Work Scale (AHWS) for the Indian context, providing a tool for researchers and practitioners to systematically examine the impact of autonomy in hybrid work. METHODS: A descriptive two-phase study was conducted following DeVellis's scale development framework. Phase 1 focused on conceptualizing and developing the construct through a comprehensive literature review, item generation, and assessment of content and face validity by experts, followed by a pilot test. Phase 2 encompassed the scale validation process, which included Exploratory Factor Analysis (EFA) to identify the underlying factor structure and Confirmatory Factor Analysis (CFA) to validate the model and assess its fit. RESULTS: The data collected from 313 IT employees working in Bengaluru, India, was analyzed to confirm data normality (below ± 2.58). The items showed a strong and positive correlation (r = .734) with the Work Design Questionnaire which indicated convergent validity. Discriminant validity was confirmed through Fornell-Larcker and Heterotrait-Monotrait (HTMT) criteria, with HTMT values below 0.90. The final analysis yielded an 18-item scale with a Cronbach's alpha of 0.825, comprising four distinct dimensions: (a) work location autonomy, (b) work time autonomy, (c) work scheduling autonomy, and (d) work decision autonomy. IMPLICATIONS: The AHWS offers a valuable tool for both managers and academics to assess how different forms of autonomy influence employee well-being and productivity in hybrid work settings. It also addresses a gap in the literature, providing a foundation for further empirical research on autonomy in hybrid work models.

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