Abstract

This study empirically analyzes the impact of working from home (WFH) on travel behavior in the Tokyo metropolitan area. We use a large survey sample divided by the usual travel mode for commuting and quantify the impact of WFH on the number of rail, car, and walking and cycling trips made on a weekday. Two types of trip frequency models are examined: (1) a multivariate Poisson-lognormal (MVPLN) regression model that simultaneously explains the number of trips made by multiple modes and (2) a negative binomial regression (NBR) model. Explanatory variables comprise the place of work, the built environment of the place of residence, and individual and household attributes. The estimation results of the MVPLN model show that the error correlation between the number of trips made by a commuting mode and that by other/non-commuting modes is low for both rail and car commuters, which could justify the application of an NBR model. The estimation results of the NBR model show that the average effect of WFH for the full day (compared with working only outside the home) is a reduction of 1.9 rail trips per day for rail commuters and 1.6 car trips per day for car commuters, with car commuters who live in low-density areas tending to reduce car trips to a lesser extent. Meanwhile, few differences are observed in the reduction in rail trips for rail commuters by population density. Rail commuters tend to walk and cycle more if they work from home for the full day.

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