Private parking space owners’ choice behavior of different sharing modes: hybrid choice model using justified latent variables

ABSTRACT

Private parking spaces account for a large proportion of potential parking resources, whose utilization rate could be raised by sharing them. To investigate private parking space owners’ sharing choice behavior, this paper applies a framework of Combined Technology Acceptance Model and the Theory of Planned Behavior for a more comprehensive consideration of psychological attitudes on these suppliers in urban residential areas. A web-based survey was conducted to collect data. The justified factors are then incorporated in hybrid choice model (HCM) as latent variables. HCM results showed that incorporation of latent variables such as perceived risk provides better fitting effect than traditional multinominal models, and that revenues and community participance are influential factors for sharing choice. Our findings indicate behavioral intention framework could serve as argumentation of rational selection of latent variables. These findings could also support better implementation of shared parking from managerial and operational perspectives.

KEYWORDS:

• Private parking space
• supplier’s willingness
• sharing choice
• latent variable
• hybrid choice model
• C-TAM-TPB theory

Disclosure statement

No potential conflict of interest was reported by the author(s).

CRediT authorship contribution statement

The authors confirm contribution to the paper as follows: study conception, design: Zengrui Wang, Yiyuan Zhang; validation and supervision: Xia Luo (corresponding author); data collection: Zengrui Wang, Qixin Mai; analysis and interpretation of results: Zengrui Wang, Yiyuan Zhang; draft manuscript preparation: Zengrui Wang; review and editing: Zengrui Wang, Yiyuan Zhang, Qixin Mai. All authors reviewed the results and approved the final version of the manuscript.

Additional information

Funding

This work was supported by the Science & Technology Project of Sichuan Province under Grant No. 2020YJ0255; and Science Project of Chengdu under Grant No. 2019-RK00-00016-ZF.