Research on parking app choice behavior based on MNL. (October 2021)
- Record Type:
- Journal Article
- Title:
- Research on parking app choice behavior based on MNL. (October 2021)
- Main Title:
- Research on parking app choice behavior based on MNL
- Authors:
- Ye, Xiaofei
Yang, Chang
Wang, Tao
Yan, Xingchen
Li, Song
Chen, Jun - Abstract:
- Highlights: The logit model was established to analyze the parking app choice behavior. The function of parking apps based on the overall characteristics of parking apps in Ningbo was discussed, which is more universal. The model results show that individual heterogeneity exists in drivers with different attributes and has rules to follow, which provides reference for further research or comparative analysis of different segmentation users. The results put forward suggestions on the information release form of parking app, which is helpful to guide parking behavior. Abstract: As a kind of intelligent parking mode, shared parking mode has been widely promoted, and parking app, as a product of the development of sharing economy in the field of transportation, is also being vigorously advocated. However, there are not many people who use parking app to find and reserve parking space in practice, which is largely caused by insufficient information provided by the parking apps. In order to better explain, predict and improve drivers' choice of parking apps, a multinomial logit model was established to analyze the relationship between drivers' parking app choice behavior and the influential factors. The influential factors include drivers' individual characteristics and parking app's attributes, which were extracted from a questionnaire and typical parking apps currently in operation. The results show that the reservation and shared parking spaces, available parking spaces,Highlights: The logit model was established to analyze the parking app choice behavior. The function of parking apps based on the overall characteristics of parking apps in Ningbo was discussed, which is more universal. The model results show that individual heterogeneity exists in drivers with different attributes and has rules to follow, which provides reference for further research or comparative analysis of different segmentation users. The results put forward suggestions on the information release form of parking app, which is helpful to guide parking behavior. Abstract: As a kind of intelligent parking mode, shared parking mode has been widely promoted, and parking app, as a product of the development of sharing economy in the field of transportation, is also being vigorously advocated. However, there are not many people who use parking app to find and reserve parking space in practice, which is largely caused by insufficient information provided by the parking apps. In order to better explain, predict and improve drivers' choice of parking apps, a multinomial logit model was established to analyze the relationship between drivers' parking app choice behavior and the influential factors. The influential factors include drivers' individual characteristics and parking app's attributes, which were extracted from a questionnaire and typical parking apps currently in operation. The results show that the reservation and shared parking spaces, available parking spaces, parking charges and distance to the destination are the main factors that determine the drivers' choice of parking app. This paper provides a reference for the development of Ningbo parking apps. … (more)
- Is Part Of:
- Travel behaviour and society. Volume 25(2021)
- Journal:
- Travel behaviour and society
- Issue:
- Volume 25(2021)
- Issue Display:
- Volume 25, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 25
- Issue:
- 2021
- Issue Sort Value:
- 2021-0025-2021-0000
- Page Start:
- 174
- Page End:
- 182
- Publication Date:
- 2021-10
- Subjects:
- Parking app -- Multinomial logit model -- Choice behavior -- Influential factors
Transportation -- Periodicals
Population geography -- Periodicals
303.48305 - Journal URLs:
- http://www.sciencedirect.com/science/journal/2214367X ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.tbs.2021.07.007 ↗
- Languages:
- English
- ISSNs:
- 2214-367X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
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