The adoption behaviours of freeway electronic toll collection: A latent class modelling approach

This study develops an electronic toll collection (ETC) disaggregate choice model based on a large-scale questionnaire survey of car drivers in Taiwan. To acknowledge the difference in preferences among car drivers, the latent class logit model is used to classify respondents into different groups without subjective segmentation. The estimation results show that six groups of car drivers are optimally distinguished. The price of an e-pass and the discount for ETC tolls are identified as the two most important factors affecting ETC adoption. The study also finds that significant differences in adoption behaviours exist among groups. Effective marketing strategies for different groups are then proposed accordingly.

► A latent class logit model was used to investigate ETC adoption behaviors. ► A large-scale nationwide questionnaire survey on car drivers was conducted. ► Six groups were identified with significantly different ETC adoption behaviors. ► Effective marketing strategies for different groups are then proposed accordingly.