Traveling Mode Choice Modeling from Cross-Sectional Survey and Panel Data: The Inclusion of Initial Nonresponse
Decision-making in transport planning, as in other planning activities, requires prediction of the impacts of proposed policies on mode choice behavior. To develop models of transport mode choice to be used in prediction, mobility cross-sectional survey or panel data can be used. However, the extend to which data from these sources yield accurate parameter values and probabilities is influenced by non-response possibly leading to a non-response bias. The main research objective of the current study is to assess whether the inclusion of non-response in a nested logit mode choice model leads to changes in parameter values and more adequate estimated probabilities. In the model a latent variable was included which represents the willingness to participate in a cross-sectional survey or panel which is in turn influenced by personal characteristics of the respondents. The results show that not taking account of non-response may lead to a negligibly small overestimation of the choice for car as passenger and bicycle along with an underestimation of the choice for car as driver and e-bike of the same magnitude.Based on the models in this paper, it is not possible to conclude that including the willingness to participate in a mode choice model leads to substantial improvements, but more research is needed to fully assess the value of including willingness.