The impact of the residential built environment on work at home adoption frequency: An example from Northern California

Abstract

Working at home is widely viewed as a useful travel-reduction strategy, and it is partly for that reason that considerable research related to telecommuting and home-based work has been conducted in the last two decades. is study examines the effect of residential neighborhood built environment (BE) factors on working at home. A er systematically presenting and categorizing various relevant elements of the BE and reviewing related studies, we develop a multinomial logit (MNL) model of work-at-home (WAH) frequency using data from a survey of eight neighborhoods in Northern California. Potential explanatory variables include sociodemographic traits, neighborhood preferences and perceptions, objective neighborhood characteristics, and travel attitudes and behavior. e results clearly demonstrate the contribution of built environment variables to WAH choices, in addition to previously-identi ed in uences such as sociodemographic predictors and commute time. BE factors associated with (neo)traditional neighborhoods were associated both positively and negatively with working at home.e ndings suggest that land use and transportation strategies that are desirable from some perspectives will tend to weaken the motivation to work at home, and conversely, some factors that seem to increase the motivation to work at home are widely viewed as less sustainable. Accordingly, this research points to the complexity of trying to nd the right balance among demand management strategies that sometimes act in competition rather than in synergy.

Preferences and Expectations of Japanese Employees toward Telecommuting Frequency in the Post-Pandemic Era

“…The empirical results identified a relationship between several demographic and work-related variables and telecommuting frequency. In addition to explanatory variables such as sociodemographic characteristics and commuting time, which have been explored in previous studies, Tang et al [20] focused primarily on examining the impact of residential neighborhood-built environment (BE) factors on telecommuting frequency. The study developed a multinomial logit (MNL) model to estimate telecommuting frequency using data from a survey of eight neighborhoods in Northern California and pointed out the associations between built environment variables and the frequency of working at home.…”

Commuting at the University of Michigan

“…However, recent research has suggested that telecommuting may paradoxically increase rather than decrease carbon emissions among telecommuters, a so-called rebound effect stemming from three sources: telecommuters' nonwork trips on telecommuting days, 23 telecommuters' willingness to live farther from work, 24 and telecommuters' high use of low-carbon transportation modes, which sharply reduces their savings on telecommuting days. 25 For these reasons, the jury is still out on the carbon reduction potential of U-M telecommuting. Available data show that the average one-way commuting distance of 14 telecommuting employees at U-M's Dearborn campus was 24.1 miles, and among the 248 telecommuting staff at the College of Engineering (Ann Arbor), the distance was 16.8 miles, suggesting that telecommuting was replacing at least some driving to work on telecommuting days (see Appendix K).…”