Park‐and‐ride choice behaviour under multimodal travel information—Analysis based on panel mixed logit model

Abstract

Abstract Understanding the impact of smartphone‐based multimodal information (SMMI) on travellers' P&R (park‐and‐ride) choice behaviour is very limited so far. The purpose of this study is to better understand how SMMI, social network information, and individual characteristics influence travellers' mode choices. A stated preference experiment consisting of one P&R option and two auto‐driving routes was conducted to collect car commuters’ P&R choice data in Shanghai, China. The panel mixed logit model was utilized to determine the influencing factors. It was found that the panel mixed logit model, accounting for correlations among repeated observations of the same respondent and random taste, significantly outperforms the cross‐sectional multinomial logit model in terms of goodness‐of‐fit. Specifically, travellers are highly sensitive to the information offered by SMMI on travel time, parking fare, and crowding level in subway cars, and heterogeneities do exist in travellers' preferences for these factors. In terms of social network information, the positive propensity of online reviews and information about P&R play a positive role in P&R promotion. In addition, individual characteristics including gender, age, occupation, years of driving, and P&R experience all contribute to explaining the choice of P&R. Finally, the elasticity analysis reveals that commuters are more satisfied with P&R time than with car time, and the cross elasticity of P&R time demonstrates a limited substitution effect of P&R on private cars.

Keywords

• behavioural sciences
• driver information systems
• drives
• traveller information