Park‐and‐ride choice behaviour under multimodal travel information—Analysis based on panel mixed logit model
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 tr...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-10-01
|
| Series: | IET Intelligent Transport Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/itr2.12396 |
| _version_ | 1797659546828668928 |
|---|---|
| author | Yue Huang Hongcheng Gan Huan Lu Xinyu Wang Wenjing Wang |
| author_facet | Yue Huang Hongcheng Gan Huan Lu Xinyu Wang Wenjing Wang |
| author_sort | Yue Huang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T18:16:40Z |
| format | Article |
| id | doaj.art-e916b6b1df8e47b999499071f9c4e339 |
| institution | Directory Open Access Journal |
| issn | 1751-956X 1751-9578 |
| language | English |
| last_indexed | 2024-03-11T18:16:40Z |
| publishDate | 2023-10-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Intelligent Transport Systems |
| spelling | doaj.art-e916b6b1df8e47b999499071f9c4e3392023-10-16T07:25:49ZengWileyIET Intelligent Transport Systems1751-956X1751-95782023-10-0117102063207410.1049/itr2.12396Park‐and‐ride choice behaviour under multimodal travel information—Analysis based on panel mixed logit modelYue Huang0Hongcheng Gan1Huan Lu2Xinyu Wang3Wenjing Wang4Business School University of Shanghai for Science and Technology ShanghaiPeople's Republic of ChinaBusiness School University of Shanghai for Science and Technology ShanghaiPeople's Republic of ChinaBusiness School University of Shanghai for Science and Technology ShanghaiPeople's Republic of ChinaBusiness School University of Shanghai for Science and Technology ShanghaiPeople's Republic of ChinaBusiness School University of Shanghai for Science and Technology ShanghaiPeople's Republic of ChinaAbstract 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.https://doi.org/10.1049/itr2.12396behavioural sciencesdriver information systemsdrivestraveller information |
| spellingShingle | Yue Huang Hongcheng Gan Huan Lu Xinyu Wang Wenjing Wang Park‐and‐ride choice behaviour under multimodal travel information—Analysis based on panel mixed logit model IET Intelligent Transport Systems behavioural sciences driver information systems drives traveller information |
| title | Park‐and‐ride choice behaviour under multimodal travel information—Analysis based on panel mixed logit model |
| title_full | Park‐and‐ride choice behaviour under multimodal travel information—Analysis based on panel mixed logit model |
| title_fullStr | Park‐and‐ride choice behaviour under multimodal travel information—Analysis based on panel mixed logit model |
| title_full_unstemmed | Park‐and‐ride choice behaviour under multimodal travel information—Analysis based on panel mixed logit model |
| title_short | Park‐and‐ride choice behaviour under multimodal travel information—Analysis based on panel mixed logit model |
| title_sort | park and ride choice behaviour under multimodal travel information analysis based on panel mixed logit model |
| topic | behavioural sciences driver information systems drives traveller information |
| url | https://doi.org/10.1049/itr2.12396 |
| work_keys_str_mv | AT yuehuang parkandridechoicebehaviourundermultimodaltravelinformationanalysisbasedonpanelmixedlogitmodel AT hongchenggan parkandridechoicebehaviourundermultimodaltravelinformationanalysisbasedonpanelmixedlogitmodel AT huanlu parkandridechoicebehaviourundermultimodaltravelinformationanalysisbasedonpanelmixedlogitmodel AT xinyuwang parkandridechoicebehaviourundermultimodaltravelinformationanalysisbasedonpanelmixedlogitmodel AT wenjingwang parkandridechoicebehaviourundermultimodaltravelinformationanalysisbasedonpanelmixedlogitmodel |