Exploring the remote work challenges in the era of COVID-19 pandemic: review and application model

Abstract

Purpose

Remote work (RW) literature is a megatrend in HRM literature, and the COVID-19 pandemic has highlighted the importance of RW as a concept and an organisational practice. Given the large number of papers being published on remote work, there is a need for a critical review of the extant literature using bibliometric analysis. This paper examines the literature on remote working to identify the factors crucial for managing a remote workforce. This study uses the complex adaptive systems theory as a foundation to build a framework that organisations can use to manage their remote workforce, focusing on three outcomes: employee engagement, collaboration and organisational agility.

Design/methodology/approach

Bibliometric analysis was conducted on the research published in Scopus journal in the area of remote work, followed by critical literature analysis.

Findings

The bibliometric analysis identified five clusters that reflect five organisational factors which the management can align to achieve the desired outcomes of engagement, collaboration and agility: technology orientation, leadership, HRM practices, external processes and organisational culture. The present findings have important implications for managing the remote workforce.

Originality/value

The five factors were mapped to propose a conceptual model on engaging individual employees, fostering team collaboration and building organisational agility while working remotely. We also propose an application model for using technology to achieve the outcomes of engagement, collaboration and agility in the organisation. Practitioners could use this framework to focus on the factors that can create a conducive environment to improve work efficiency in a remote workforce.

Citation

Arunprasad, P., Dey, C., Jebli, F., Manimuthu, A. and El Hathat, Z. (2022), "Exploring the remote work challenges in the era of COVID-19 pandemic: review and application model", Benchmarking: An International Journal, Vol. 29 No. 10, pp. 3333-3355. https://doi.org/10.1108/BIJ-07-2021-0421