Decoding the work-from-home phenomenon: insights from location-based service data

Ka Shing Cheung, I.-Ting Chuang and Chung Yim Yiu

Regional Studies, Regional Science, 2023, vol. 10, issue 1, 873-875

Abstract: The global pandemic has catalysed a shift in the job market, with remote work evolving from being an option to a widespread practice. This profound change goes beyond a temporary response to an extraordinary crisis; it could potentially mark the beginning of a new era in employment. In this featured graphic, we evaluate and visualise the work-from-home (WFH) trend in Auckland, the most populous metropolis in New Zealand. Applying a modified open-source machine learning algorithm on location-based service (LBS) data, we have created a visualisation to compare the individual work locations. The results reveal a significantly dispersed workplace distribution following the COVID-19 pandemic. Our visualisation, coupled with entropy analysis, provides prima facie evidence of the WFH trend. This finding holds implications for productivity and carries broader implications for the global workforce.

Date: 2023
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DOI: 10.1080/21681376.2023.2278577

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