Model for Children's School Travel Mode Choice: Accounting for Effects of Spatial and Social Interaction
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Numerous programs aimed at enhancing the choice of bicycle and walk as modes of choice for children's trips to and from school are being implemented by public agencies around the world. Disaggregate choice models capable of accounting for the myriad of factors that influence child school mode choice are needed to accurately forecast the potential impacts of such programs and policies. This paper aims to present a school mode choice model that is capable of capturing the unobserved spatial interaction effects that may potentially influence household decision-making processes when choosing a mode of transportation for children's trips to and from school. For example, households that are geographically clustered close together in a neighborhood may interact or observe one another, and be influenced by each other's actions. In order to overcome the computational intractability associated with estimating a discrete choice model with spatial interaction effects, the paper proposes the use of a maximum approximated composite marginal likelihood (MACML) approach for estimating model parameters. The model is applied to a sample of children residing in Southern California whose households responded to the 2009 National Household Travel Survey in the United States. It is found that spatial correlation effects are statistically significant, and that these effects 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 among children may see greater impact if targeted at the local neighborhood level as opposed to a more diffuse regional scale.
At the time of publication R. Sidharthan and C.R. Bhat were at the University of Texas at Austin; R.M. Pendyala was at Arizona State University; and K.G. Goulias was at the University of California Santa Barbara.