Abstract:This paper investigates the impact of several factors on the adoption of telecommuting, using empirical data collected from 1,864 commuters in Northern California. We distinguish three types of telecommuting – full-day, part-day, and overtime – as they might affect travel behavior in very different ways. We develop binary logit models and a trivariate probit model of the adoption of each form of telecommuting, using non-centered factor scores to identify pro-high- vs. pro-low-density workers. We test the hypothesis that the impact of the built environment on the decision to adopt telecommuting differs between those two segments. The results support the hypothesis, with numerous variables significant to one of those segments but not the other; in the case of the binary logit model for overtime telecommuting, employment density in the home area even has opposite influences for pro-high-density (positive) compared to pro-low-density people (negative). Other groups of variables, including personal attitudes and demographic traits, also significantly affect individuals’ decisions on whether and how to telecommute, if at all. For example (consistent with other studies), education and household income are strong (positive) predictors of the decision to telecommute. Compared to the separate binary logit models, the trivariate probit model better predicts the joint probabilities of adopting the various forms of telecommuting, and better models the correlated adoption of the three types of telecommuting.