Remote Work admist the Covid-19 outbreak: Insights from an Ensemble Community-Based Keyword Network Analysis

COVID-19's rapid shift to remote working has sparked interest in synthetizing the growing body of research in order to gain a comprehensive understanding into the scholarship structure of the field. This study explores the issue of pandemic-induced remote working from a multidisciplinary perspective, paving the way for further investigation and effective decision-making. A co-occurrence network analysis of keywords in scientific articles is employed to comprehensively analyze the international literature on pandemic-induced remote working. We use bibliometric analysis, network centrality measures, and community detection algorithms to identify key concepts, trends, and interconnections within the pandemic-induced research landscape. As a result of our literature review, several prominent themes and topics were identified, emphasizing distinct keyword communities. These communities address essential aspects of remote working, such as human resource management, well-being, technology adoption, leadership, and socioeconomic implications. Based on the extracted concepts, we propose directions for future research focusing on the prospects of remote work in the post-pandemic era. Additionally, we recommend policy implications for organizations and policymakers.