Year: 2025
Type: article
Abstract: The COVID-19 pandemic has substantially increased remote and hybrid working rates, creating a large group of workers whose experiences differ from those in traditional workplace settings. While previous studies have compared remote and non-remote workers in relation to productivity, performance and well-being, less attention has been given to how their mobility patterns differ. Although researchers have suggested that the ability to work remotely affects workers’ mobilities, there remains limited empirical evidence comparing remote and non-remote workers’ mobilities. This paper presents the first study to compare the mobilities of these groups in the UK. It focuses on four types of mobility studied in relation to remote work: counterurbanisation, commuting, multi-local work and immobility. It is the first to integrate analysis of all four mobilities, offering a novel, integrated perspective on remote work and mobility. The paper examines regional differences in these mobilities across the UK, highlighting how workers’ mobility patterns vary between regions.This study draws on data from the UK Household Longitudinal Study and employs bivariate statistical tests and regression analyses. The results show that remote workers are more likely than non-remote workers to move to rural areas, own second homes and commute longer distances. These trends are pronounced in southern English regions. Remote work risks reinforcing existing inequalities between knowledge workers and manual workers and perpetuating traditional associations between mobility and urban areas in the UK. Furthermore, while remote work may generate new economic opportunities, it may also increase demand for accessible rural housing, particularly in regions surrounding London.
Author: Kirsten Clarke
Institutions: University of Gloucestershire, James Hutton Institute
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,165
OpenAlex ID: W4410519213