Examination of Clusters for Better Understanding Commuter Cyclists’ Travel Behavior: Insights from a Longitudinal Panel Survey

Abstract

This study examined commuter cyclists’ travel behavior, particularly in response to changes in weather conditions and situational factors. The motivators, deterrents, and preferences of commuter cycling were also examined. To reach greater understanding of commuter cyclists’ decision making, cyclists were clustered. Disaggregated travel data were collected from a longitudinal panel survey (sample size: 355) and analyzed to identify the influence of weather conditions and situational factors on commuters’ day-to-day cycling decisions. The baseline survey (a one-off survey) provided information about the work characteristics, travel characteristics, motivational factors, and sociodemographics of the participants. Generalized estimating equations were used to compare the responses between groups on the day-to-day influences of weather conditions and situational factors. Binary logistic regression was used to predict commuters’ cycling decisions (whether or not to cycle). Commuter cyclists’ average decision (over the longitudinal survey period) was modeled with work characteristics, travel characteristics, motivational factors, and sociodemographics as explanatory variables. The results indicate that parameter estimates vary significantly between groups. Part-time commuter cyclists and commuter cyclists who do not plan their travel behavior in advance were more affected by adverse weather conditions than were the comparison groups. Situational factors were larger deterrents for part-time commuter cyclists and cyclists who traveled longer distances to work. However, off-road paths encouraged long-distance commuters to cycle more often. The paper includes a discussion on how the implications of these results can influence government policies and strategies in an effort to increase commuter cycling.