Model for children's school travel mode choice

Numerous programs aimed at enhancing the choice of bicycling and walking as modes of choice for children's trips to and from school are being implemented by public agencies around the world. Disaggregate models that can account for the myriad of factors that influence the school mode choice of children are needed to forecast the potential impacts of such programs and policies. This paper presents a model for school mode choice that can capture the unobserved spatial interaction effects that may influence household decision making in choosing a mode of transportation for children's trips to and from school. For example, households that are geographically close together in a neighborhood may interact or observe one another and be influenced by each other's actions. To overcome the computational intractability associated with estimating a discrete choice model with spatial interaction effects, the paper proposes a maximum approximated composite marginal likelihood approach for estimating model parameters. The model is applied to a sample of children in Southern California whose households responded to the 2009 National Household Travel Survey in the United States. Spatial correlation effects are statistically significant, and they arise from interactions among households that are geographically close to one another. The findings suggest that public policy programs aimed at enhancing the use of bicycle and walk modes may have a greater impact if directed toward the local neighborhood level as opposed to a more diffuse regional level.