Joint Econometric Model Framework for Transportation Network Company Users’ Trip Fare and Destination Choice Analysis

Abstract

In this study, we examine the factors affecting Chicago, U.S., transportation network companies (TNCs) users’ trip fare and destination choice behavior. While trip fare has been examined from various perspectives, earlier fare models have not considered an exhaustive set of independent variables. Further, trip fare decisions are significantly influenced by trip destination. Therefore, in our study a joint model of trip fare and destination choice is proposed. The joint model system—linear regression for fare and multinomial logit model for destination—is developed based on Chicago TNC weekday trip data from January 2019 to December 2019. A wide range of origin- and destination-specific land use and built environment factors, transportation infrastructure attributes, and weather attributes were found to be significant in the model system. Based on log-likelihood and Bayesian information criterion measures, the model performance of the proposed joint model is found to be superior compared with independent fare and destination models. The applicability of our proposed fare and destination choice model is illustrated through fare prediction and destination elasticity analysis. The framework can potentially be employed to generate TNC fare for inclusion in level of service measures for TNC models in the mode choice model.