Technology-Enabled Remote Work and Employee Engagement: Challenges for Human Resource Management During the COVID-19 Era
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Abstract
The COVID-19 pandemic forced an abrupt and near-universal shift to technology-enabled remote work, converting an arrangement that had been gradual, voluntary, and selective into one that was sudden, mandatory, and total. This paper examines what that shift meant for employee engagement and the challenges it created for human resource management, synthesizing the pre-pandemic telework literature with the first wave of scholarship on remote work during COVID-19. It argues that pandemic remote work differed from the telework that research had previously studied in ways that limit the applicability of earlier findings: it was involuntary, comprehensive, conducted under conditions of crisis and blurred boundaries between work and home, and unaccompanied by the choice and preparation that had characterized telework as an optional benefit. Drawing on the job demands–resources and work-design perspectives, the paper analyzes how pandemic remote work affected the psychological conditions on which engagement depends—reshaping autonomy, social connection, boundary management, and the experience of meaning and support—and it identifies the mechanisms through which engagement was both sustained and eroded. The paper then examines the challenges the shift posed for HRM, including sustaining connection and culture at a distance, supporting well-being under crisis conditions, adapting performance management to unobserved work, and preserving equity across employees whose circumstances differed sharply. It develops an integrative account of remote-work engagement under crisis and draws implications for how HR functions can support engagement when work is mediated by technology and separated from a shared physical setting. Building on this account, the paper advances a proposed digital employee experience analytics framework that combines natural language processing of employee voice, process mining of HR service workflows, and machine-learning prediction—including temporal models—to detect burnout, disengagement, and productivity risk early and to compare experience across office, hybrid, and remote employees. An illustrative evaluation is reported to demonstrate the design and is clearly labeled as hypothetical pending empirical validation. It concludes that technology enabled remote work but did not by itself sustain engagement, which depended on deliberate human and managerial support that the crisis made both harder and more necessary—support that a well-governed analytics capability can inform but not replace.