Influence Mechanism of Urban Staggered Shared Parking Policy on Behavioral Intentions of Users and Providers Based on Extended Planned Behavior Theory

Abstract

Shared parking has been widely accepted as an effective way to deal with the mismatch between parking demand and supply. Especially for adjacent construction areas with mixed residential and commercial land, staggered shared parking has broad application prospects. From the previous practice, the public welfare from the government, the commercial interests of parking enterprises, and the individual income of residents will be the key elements to promote a staggered parking policy in adjacent construction areas. However, the current research on shared parking mainly focused on the commercial factors to improve the operating efficiency and operating benefit for parking enterprises; there is a lack of research on the implementation process of staggered parking policies which will solve residential areas’ parking problem with the interests of residents as the core. Here, this paper focuses on exploring residents’ and businesses’ intention to participate in the process of a staggered shared parking policy, where businesses have certain location and condition qualifications. Firstly, this study used two extended theoretical models of planned behavior to explore the behavioral intentions of users and providers in this staggered shared parking event, respectively. Secondly, the research hypothesis was examined using a structural equation approach, and a questionnaire was designed to survey 323 residents and 282 enterprises in the core urban area of Beijing. Ultimately, the study indicated that, for residents, perceptual behavior control has the greatest impact on the perceived intention, while the perceived ease of use and perceived usefulness play a crucial influential role in the willingness to use staggered shared parking. For companies, attitude has the strongest impact on the perceived intention. Our findings reveal the intrinsic impact mechanism of the policies in the decision-making process, contributing to the precise policy implementation to alleviate the problem of difficult parking for residents, thus improving the city’s parking management.

Investigating Factors for Travelers’ Parking Behavior Intentions in Changchun, China, under the Influence of Smart Parking Systems

“…To capture the intricate relationships between factors and parking intentions, researchers have utilized various data collection and analytical methods, including questionnaires, surveys, interviews, observational studies, choice experiments, revealed preference studies, and agent-based simulations [9,12,14,15,45,46]. Statistical analyses, such as regression models, SEM, and cluster analyses, have been employed to determine the associations between these factors and parking intentions [18,47,48].…”