Capturing behavioral differences between frequent and seldom users of ride-pooling in a cross-nested logit model

Abstract

Within this study, we estimate a Cross-Nested Logit (CNL) model incorporating ride-pooling and other shared modes using combined revealed and stated preference data. The CNL allows to captures complex substitution patterns that cannot be represented by simpler MNL or NL models. Results show that ride-pooling correlates with multiple nests and that behavior differs significantly between frequent and seldom users. Frequent users (using ride-pooling at least once a month) would rather replace public transport and cycling, while seldom users would shift to other shared modes. This could provide evidence that frequent users already incorporated ride-pooling in daily travel routines while seldom users are still in the exploring phase. Overall, the study highlights the importance of accounting for behavioral heterogeneity and target-group specific analysis, when investigating new modes or setting up models to support decision-makers with scenario analyses.