A statistical assessment of work-from-home participation during different stages of the COVID-19 pandemic

Natalia Barbour, Nikhil Menon*, Fred Mannering

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
13 Downloads (Pure)

Abstract

Responses to the COVID-19 pandemic have dramatically transformed industry, healthcare, mobility, and education. Many workers have been forced to shift to work-from-home, adjust their commute patterns, and/or adopt new behaviors. Particularly important in the context of mitigating transportation-related emissions is the shift to work-from-home. This paper focuses on two major shifts along different stages of the pandemic. First, it investigates switching to work-from-home during the pandemic, followed by assessing the likelihood of continuing to work-from-home as opposed to returning to the workplace. This second assessment, being conditioned on workers having experienced work-from-home as the result of the pandemic, allows important insights into the factors affecting work-from-home probabilities. Using a survey collected in July and August of 2020, it is found that nearly 50 percent of the respondents who did not work-from-home before but started to work-from-home during the COVID-19 pandemic, indicated the willingness to continue work-from-home. A total of 1,275 observations collected using the survey questionnaire, that was administered through a U.S. nationwide panel (Prime Panels), were used in the model estimation. The methodological approach used to study work-from-home probabilities in this paper captures the complexities of human behavior by considering the effects of unobserved heterogeneity in a multivariate context, which allows for new insights into the effect of explanatory variables on the likelihood of working from home. Random parameters logit model estimations (with heterogeneity in the means and variances of random parameters) revealed additional insights into factors affecting work-from-home probabilities. It was found that gender, age, income, the presence of children, education, residential location, or job sectors including marketing, information technologies, business, or administration/administrative support all played significant roles in explaining these behavioral shifts and post-pandemic preferences.
Original languageEnglish
Article number100441
Number of pages9
JournalTransportation Research Interdisciplinary Perspectives
Volume11
DOIs
Publication statusPublished - 2021

Keywords

  • Random parameters model with heterogeneity in the means
  • Telecommute
  • Travel behavior and COVID-19
  • Work-from-home

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