Empirical Analysis of Commuter Stop-Making Behavior Based on Ordered Porbit Model

Understanding the stop-making behavior of commuters is important for planners and policy makers in their efforts to improve travel demand models. This paper describes a set of stop frequency models used to predict the number of non-work activity stops made by individual adult workers in five different time periods. Using the travel daily data from the third comprehensive transport survey of Beijing, this study examines commute stop-making behavior for individual workers residing in Beijing. The ordered probit model was used to account for the ordered classification scale of the dependent variable (in this case, number of stops- zero stop, one stop, and two or more stops). The empirical results provide useful insights into the effects of socio-demographics, land use density, transportation service, and work schedule on commute stop-making propensity in a highly urbanized environment.