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.

1. Introduction

Pursuing effective policy intervention approaches involving urban parking management is necessary as cities face the manifold challenges due to the mismatch between the increased private vehicles and limited parking sources, such as traffic accidents caused by occupying pedestrian and driving lanes and the low capacity of vehicle lands caused by unorderly parking. The rapid development of the economy steers a continuous increase in vehicle numbers that places huge pressure on urban parking. For example, the number of motor vehicles in China has reached 393 million up to November 2021, according to the Ministry of Public Security, which is 1.64 times that of ten years ago. However, the deficit in the parking berth was over 80 million in 2020, reported by People’s Daily [1]. The mismatch between parking supply and demand requires extra time for drivers to find a proper parking space, particularly in the urban core of a metropolis. Shoup et al. found that most people need to take eight minutes at least, and almost 30% of cars are cruising to find a parking space [2]. Meanwhile, the current studies argue that additional cruising causes serious carbon emissions and has a negative impact on both the operation of the urban network and the environment [3,4].

Shared parking, initiated in the USA, was considered and proved to be an effective approach to cope with the mismatch because it is hard for parking infrastructure to catch up with the increased demand for parking [5]. The concept of shared parking is also getting the bulk of attention from cities with limited parking resources. So, as to China, a national document of “Opinions on Promoting the Development of Urban Parking Facilities” was officially issued by the General Office of the State Council in May 2019, a parking resource for government agency departments in which enterprises and institutions were encouraged to open to the surrounding residential community so as to stimulate commercial facilities, office buildings, and other parking facilities to share parking resources in a staggered time way. The scientific and reasonable realization of the staggered shared parking policy will be an obvious concern for the city’s traffic management [6]. Following the advice of the higher authorities, Beijing has carried out practical work since 2019, and it has been four years of work up to now. The original intention of its work aimed to solve the problem of parking in residential areas, whereas in the process of implementation, the problem of chaos behavior emerged, such as the battle for parking spaces and the illegal occupation of parking, while waiting for a better solution to handle it. To explore the subject, our group has conducted a follow-up evaluation study on the implementation process of Beijing’s staggered shared parking policy.

Generally speaking, parking can be divided into two types of service, which are the trip part and the residential part. The trip aspect refers to the demand for parking at places where people visit for work, consumption, entertainment, medical, educational, etc. The residential aspect refers to the need to park vehicles in residential areas outside of travel, focusing on the residents parking their private vehicle for long periods of time at night. The scope of the review of our paper therefore focuses on the shared park on the trip side and residential side.

For the trip side of shared parking, many scholars focus on the combination of qualitative and quantitative methods. The existing studies focus on improving the efficiency of parking resource allocation, developing reasonable parking pricing schemes, and designing shared parking operation models, and a small quantity of the research is on the intention of shared parking use, among other aspects [7,8]. Scholars, led by Yao Enjian [9] and Duan Manzhen [10], found that urban parking resources are characterized by complementary relationships and have been devoted to researching many methods to optimize the matching of urban parking resources. Scholars [9,10,11,12,13] firstly proposed optimal allocation algorithms and matching strategies and subsequently [14,15,16,17] proposed multiple kinds of supply and demand matching optimization models based on different research targets. A number of scholars [11,18,19,20,21] studied the theoretical model of shared parking regarding the price cost, by reasonably allocating the revenue, developing the price mechanism, etc. Lai Minghui et al. [22] focused on the design of shared parking systems, attempting to promote the development of the shared parking field through technological enhancements. In recent years, scholars, such as Xie J [23], Yan Q [24], and Ange W [25], introduced psychological theoretical models to explore the usage intentions of shared parking users, providers, and managers, focusing on the intrinsic influencing elements of shared parking behavior.

In China, however, the residential portion of shared parking is typically characterized by its strong public interest, not just for commercial gain. A certain amount of research work gives us good inspiration, such as through the analysis of the current state of shared parking, to propose policy recommendations and price models to estimate benefits [25]. Through the construction of the demand prediction model, the sharing strategy was proposed [26], and psychological methods were used to detect the behavioral intentions of shared parking suppliers and demanders. Luo Qiuxia [27] analyzed the influencing factors of the shared parking choice using a combination of quantitative and qualitative methods (the LOGIT model and structural equation model). Jyun-Kai Liang et al. [28] explored the intention of parking space providers and demanders to participate in shared parking based on the C-TAM-TPB model; while using the same theoretical approach, Yu Ning et al. [29] investigated the acceptance of drivers. Subsequently, scholars, such as Jin Xie [23], explored the impact of other latent variables, expanding the TPB model on shared parking in residential areas. It can be seen that the scholars’ research on the acceptance of shared parking in residential areas plays a crucial role in government strategies. However, there is no direct study of the impact mechanisms for the advancement of shared parking policies in residential areas. And this existing research on residential shared parking cannot match the dual attribute of commonweal and profit. Often, for complex social issues of parking, policy recommendations should be explored more from the actual practice of policy advancement. Therefore, we synthesize the experiences of research authors and explore the relationship among the participating subjects, residents, enterprises, and government, based on experiments of actual staggered shared parking policies. We analyze the intrinsic potential influences on the advancement of policy by utilizing psychological models.

Given the positioning characteristics of China’s staggered shared parking policy, this paper is dedicated to complementing urban parking management issues under different social systems. In the Chinese institutional environment, most of the current staggered shared parking policy is led by the government. The core purpose is alleviating the problem of difficult nighttime parking for residents in residential areas. Specially, the establishment of China’s staggered shared parking policy has the characteristics of both market and livelihood attributes. Therefore, the successful implementation of the policy requires the joint efforts of multiple actors. Among them, the government is in an indispensable leading role, the active participation of enterprises is important, and residents accept and use the shared parking spaces. Considering the diversity of the interests of the different participants involved, it is crucial to explore the intentions of each participant in the decision of this behavior. These experiences and inspirations are also very helpful for other cities with limited parking resources to carry out urban traffic governance [30].

From examples of policy practice, our innovative objective in this study is to address the following two aims: (1) To deal with the problem of residents’ difficulty in parking at night and to explore the underlying mechanisms that influence residents’ participation in staggered shared parking policies. (2) To select companies that possess available parking resources within the surrounding residential areas and to explore the intrinsic mechanisms that influence the enterprises providing the staggered shared parking spaces. Thus, it helps to inform the government’s policy-making decisions and management.

Following these aims, this paper explores the influence mechanism of an urban staggered shared parking policy on the behavioral intentions of users and providers based on the existing expanded theory of planned behavior. On the one hand, it combines the technology acceptance theory and theory of planned behavior to explore residents’ willingness to use staggered shared parking. On the other hand, a benefit–risk analysis is combined with the theory of planned behavior to explore the willingness of companies to provide staggered shared parking. An analytical model is constructed to analyze the game relationship between the providers and users in the practice of staggered shared parking policies. Ultimately, the aim is to provide scientific and effective recommendations for the government to promote staggered shared parking policies.

This paper is organized as follows. In Section 2, we present the theory introduction and propose the theoretical framework and research hypothesis. In Section 3, the measurement instrument and survey data content are presented. The empirical analysis and results are given in Section 4. Finally, a discussion of the findings and the conclusions of the study are provided in Section 5.

2. Theoretical Integration and Research Hypotheses

2.1. Integration of Theory of Planned Behavior with TAM and BRA

The theory of planned behavior (TPB) is derived from the theory of rational behavior (TRA), originally proposed by Fishbein and Ajzen in 1975 [31]. The theory is founded on the assumption that people are rational and consider the meaning and consequences of a certain behavior by combining various information before performing it. Considering the practical situation, the degree of individual volitional control toward behavior is often influenced by many factors, such as time, money, ability, etc. Ajzen [32] added the key factor of perceptual behavioral control to the theory of rational behavior to make up for the shortcomings of the theory, which cannot reasonably predict and explain individual behavior.

The framework of the theory of planned behavior model is shown in Figure 1. Behavioral intentions are determined by a combination of attitudes, subjective norms, and perceived behavioral control. Meanwhile, it can be predicted with a high degree of accuracy in a particular situation. Ajzen further confirmed that intention and perceived behavioral control can account for variation among behaviors, and the theory gradually evolved into an effective means to deal with the complexities of human social behavior, which included the concept of social and behavior sciences.

The technology acceptance model (TAM) [33] is a well-known theory used to research the influence of individual behavior using IT. This theory is widely used to predict and explain behavioral intentions for the reception of technology and technological innovation. The TAM (Figure 2) is based on two main factors: perceived usefulness (PU) and perceived ease of use (PEOU). Defined, the former refers to the degree to which a person believes that using a new technology or a system will improve his performance; the latter refers to the degree to which a person believes it is easy to use a new technology or a system.

Talyor and Todd [34] proposed an extended model combining the technology acceptance theory (TAM) and the theory of planned behavior (TPB), as shown in Figure 3. Subsequently, the research work of many scholars confirmed the validity of this model in the transportation field. Chen [35] used the C-TPB-TAM to study the intention of public transportation transfer and the use of green smart mobility. Chang et al. [36] used the C-TPB-TAM to investigate the intention of the use of the telehealth system. Yu Ning [29] and Davis [33] used the C-TPB-TAM to analyze drivers’ perception and acceptance of shared parking. Regarding similarities, both models are derived from the TRA, one focusing on internal factors and the other on external factors. The integration of the two theories greatly improves the models’ ability to predict and explain human behavioral intentions in the background of modern technology. It is worth noting that this extended model has been applied more to the study of shared parking but not to the implementation of staggered shared parking policies in Chinese cities.

The benefit–risk assessment (BRA) model is commonly used in consumer behavior research. Perceived benefits and perceived risks are significant variables that influence users’ behavioral intentions. The user makes the behavioral choice deemed most appropriate, weighing the benefits and risks. The key reason for the integration of the BRA and TPB is that perceived benefits and perceived risks simultaneously affect individual behavioral attitudes and behavioral intentions. In purchasing behavior decisions, there is a psychology that consumers estimate the value and cost of products and services, which to some extent influences the outcome of the purchase [37,38]. Subsequent research literature within the field of traffic confirmed the effectiveness of that theory for researching the behavior of traffic. Tingru Zhang [39] used the extended TAM with new constructs, initial trust and two types of perceived risk, to explore factors affecting users’ acceptance of automated vehicles (AVs, Level 3). Di Zhu [40] used the C-TPB-TAM to explore the parking behavior of bike-sharing users. Jin Xie [23] explored the perception of shared parking risks, shared parking benefits, and management pressure on parking suppliers and managers toward using the shared parking. It is known that the variables of the BRA effectively enhance the ability of the theory of planned behavior to explain and predict behavioral intentions and behavior. During the implementation of the staggered shared parking policy, for providers participating in the shared parking, consumption behavior also exists. Therefore, the BRA can assist in studying that behavioral intention.

2.2. Theoretical Framework

The TPB is derived from the assumption that three main factors, namely the attitude toward the behavior, the subjective norm, and perceived behavioral control, affect one’s behavioral intention toward the actual behavior [29]. The TAM is widely applied to explain and predict the acceptance of information technology and information systems [33]. The TAM states that perceived usefulness and perceived ease of use work together to shape the user’s attitude toward using a technology, which further influences use intention [29]. The benefit–risk analysis (BRA) model is often used in behavior research. It points out that perceived benefits (PBs) and perceived risks (PRs) are important variables that affect the user’s behavioral intention and ultimately influence their decisions. Conversely, PBs and PRs will affect individual behavior attitude and behavior intention [25]. Considered in this paper is research as to which kind of factors influence the two roles, companies and residents, when choosing the urban staggered shared parking behavior. From the user and supplier aspects, the companies, including commercial enterprises and government departments, are regarded as the supplier, and they need to balance the costs and benefits, focusing more on the assessment of risks. The residents are regarded as the user, and they focus on the price and convenience of the shared parking using the technology (i.e., via a mobile application). Therefore, we combined the TPB and TAM to investigate the intention to use shared parking on the user, adopting the TAM merits elements in the technology perspective, which the hypothetical model is shown in Figure 4. Combining the TPB and BRA is deemed as an ideal base model to deal with the supplier to provide the amount of the shared parking, whereas the PB and PR concern the behavior bringing the hidden risk. The hypothetical model is shown in Figure 5.

2.3. Research Hypothesis

An attitude (ATT) refers solely to a person’s personal feeling with respect to some action or event, which usually is a bipolar evaluative that can be positive or negative [31]. It is proved that attitude has a positive effect on use intention (UI) [29,32,34]. Moreover, as individuals tend to be more positive toward a particular behavior, their behavioral intentions are higher. We believe that participants of staggered shared parking have a favorable attitude toward the mechanism, which is conducive to forming that intention to engage in the particular behavior. Thus, the following hypothesis is proposed.

Hypothesis 1.

The ATT toward the urban staggered shared parking system has a positive effect on the intention to use the urban staggered shared parking system.

Ajzen [32] posed that a subjective norm (SN) is concerned with the likelihood that important referent individuals or groups approve or disapprove of performing a given behavior. Liang also found that an SN has the strongest impact on the UI from the perspective of private parking suppliers. In our society, considering the collectivist culture [28], the relevant people’s influence can be derived from significant others (e.g., parents and spouse), groups (e.g., neighbors, co-workers, and friends), and others (e.g., the media and government). The group precedes the individual [36], as a group member’s decision is more easily swayed. Thus, the following hypothesis is proposed.

Hypothesis 2.

An SN has a positive effect on the intention to use the urban staggered shared parking system.

Ajzen’s research [32] emphasized that perceived behavioral control (PBC) plays an important role. The actual behavioral control is self-evident. In the prediction of the intentions and actions process, PBC is a latent variable, reflects the likelihood that a person will accomplish the behavior, and is influenced by resources and opportunities. Liang [28] found that PBC has a positive impact on the UI of the parking space demanders’ decision. Thus, the following hypothesis is proposed.

Hypothesis 3.

PBC has a positive effect on the intention to use the urban staggered shared parking system.

Davis [33] proposed that two sectors are theorized to be fundamental determinants of system use or IT usage. The two constructs, the perceived ease of use (PEOU) and perceived usefulness (PU), are used to predict how the urban staggered shared parking system is performed. In this research, the PU is defined here as “the degree to which a user believes that using the urban staggered shared parking system would address the parking issue”. In contrast, the PEOU refers to “the degree to which a user believes that using the particular system by technology tools would be free of effort”. Davis [33] and Taylor and Todd [34] posited that the PEOU and PU have a positive impact on an individual’s attitude toward the urban staggered shared parking system, respectively. Furthermore, Taylor and Todd pointed out that attitude is determined jointly by the PEOU and PU. Yu Ning [29] pointed out that the PU played an important mediate role in shared parking acceptance. In the context of this study, the PU pays more attention to the influence of the resources (e.g., the time of use, walking distance, price, etc.) on users to make decisions about the urban staggered shared parking system. We regard that the application is more likely to be accepted by users if easily operated. By analyzing the process of implementing a staggered shared parking policy, this paper argues that the use operation is to some extent strongly related to the ease with which individuals can complete the behavior. For example, being able to understand and perform the behavior is a manifestation of the person’s own ability. Thus, the following hypotheses are proposed.

Hypothesis 4.

The PEOU has a positive effect on attitudes toward the urban staggered shared parking system.

Hypothesis 5.

The PEOU has a positive effect on perceived usefulness.

Hypothesis 6.

The PU has a positive effect on attitudes toward the urban staggered shared parking system.

Hypothesis 7.

The PU has a positive effect on the intention to use the urban staggered shared parking system.

Hypothesis 8.

There exists a significant relationship between the PEOU and PBC.

A perceived benefit (PB) is an important factor for the provider. The potential income and social gain influence the intention of individuals to engage in a particular behavior to some extent [41,42,43]. The PB plays an intermediate role, indirectly influencing the forming of the intentions through attitudes. In this study, we believe that a PB promotes the intention of the participants to use the urban staggered shared parking system, considering the revenue generated by the parking spaces, the corporate reputation, and the social contribution. Thus, the following hypotheses are proposed.

Hypothesis 9.

A PB has a positive effect on attitudes toward the urban staggered shared parking system.

Hypothesis 10.

A PB has a positive effect on the intention to use the urban staggered shared parking system.

Bauer [37] posed a well-accepted and essential concept that there probably exists a negative influence of a perceived risk (PR) on consumer behavior. Wood and Scheer [28] noted in their study that perceived risk has a direct impact on attitudes toward use, and a PR can lead to people’s negative perception of behavior [27,29,43], which shows that there are some unavoidable risks derived from the use of a shared parking system, for instance, price costs (e.g., the equipment and management aspects), safety risks, and management pressure. As providers, they need to upgrade the existing parking equipment, and it is essential to purchase some intelligent electronic equipment. But this is a heavy burden for these kinds of commercial parking lots, especially those of the government or departments. At the same time, management pressure needs to be considered. For example, residents’ nighttime parking demand needs to extend parking lot operating hours, as well as the special regulation of shared parking spaces need to train. It is noted that improper management would lead to potential conflict. This means that the safety issues are the most important sector for suppliers. In the recent research on the shared parking system, such a phenomenon that the user does not leave after their reserved time slots leads directly to the parking reservation disturbance [44]. Through the previous investigation, the most mentioned concern is the safety of the company’s normal operation, which negatively affects suppliers’ willingness to supply the shared parking spaces [45]. Therefore, we can assume that if the PR of sharing is greater for residential parking space owners, the less willing they are to share. It is also linked to PBC, which has a negative correlation and contributes to the decision of the final behavior. Thus, the following hypotheses are proposed.

Hypothesis 11.

PR has a negative effect on attitudes toward the urban staggered shared parking system.

Hypothesis 12.

PR has a negative effect on the intention to use the urban staggered shared parking system.

Hypothesis 13.

There exists a significant relationship between PB and PR.

Hypothesis 14.

There exists a significant relationship between PR and PBC.

3. Methodology

3.1. Measurement Instrument

Our team previously investigated the factors influencing the implementation of Beijing’s staggered shared parking policy based on rooting theory. Based on the obtained impact spectrum of the implementation of the staggered shared parking policy and previous research [43], it can be seen that the three parties maintain the different interests. Among them, residents, as users, are more concerned about the price, convenience, and safety in the process of using staggered shared parking. Companies, as providers, consider more about the benefits (both social and economic), the costs [29] (including equipment upgrades, personnel management), the risks, and the pressure they bear by providing parking spaces. The government, as the leader of both, is responsible for the coordination and coherence. On the basis of the results obtained above, we designed the investigative content of this paper by drawing on the existing hypothesis model and expert design ideas. In this paper, two questionnaires were designed for different respondents from enterprises and residents. The questionnaire consists of two parts; the first part is an individual (business) information survey to investigate the attributes of individuals involved in the staggered shared parking policy. The other part is the engagement intention survey, which investigates the potential psychological factors that influence users to make decisions, as shown in

Table 1. Constructs and measurement items on resident.

Constructs	Items	Content	Source and References
Attitude (ATT)	ATT1	Staggered shared parking is good for me.	[28,29,32,34]
	ATT2	Staggered shared parking can address my daily parking problems.
	ATT3	Staggered parking is beneficial to the management of parking in the community.
	ATT4	Staggered shared parking can alleviate the conflicts among residents caused by conflicts over parking resources.
Subjective norms (SN)	SN1	I would be willing to participate in shared parking if I have encouragement from the people who are important to me (family/friends/colleagues).	[28,29,32,34]
	SN2	I would be willing to participate in shared parking if I have the support of someone who has influence with me (a fellow community shared parking participant).
	SN3	I would be willing to participate in Shared Parking if there are government and community organizations.
Perceived behavior control (PBC)	PBC1	I can understand the policy of staggered shared parking and the space selection mechanism.	[28,29,32,34,46]
	PBC2	I am eligible to enjoy the benefits of the Staggered Shared Parking Policy.
	PBC3	I can easily and quickly find the location of the staggered shared parking lot.
Perceived usefulness (PU)	PU1	Using staggered shared parking can reduce the time I spend looking for a parking space.	[28,33,34,46]
	PU2	Using staggered shared parking can shorten the distance I have to walk home after I finish parking.
	PU3	Using staggered shared parking can address my difficulty in finding a parking space.
	PU4	Staggered shared parking can save me the cost of parking.
	PU5	Staggered shared parking can provide me with high quality and comfortable parking service.
Perceived ease of use (PEOU)	PEOU1	I can easily understand how to participate in the staggered shared parking policy.	[28,33,34]
	PEOU2	It is easy for me to apply for registration as a user of the staggered shared parking policy.
Use intention (UI)	UI1	I am willing to try out staggered shared parking.	[28,29,32,34]
	UI2	I am willing to use staggered shared parking for a long time.
	UI3	I would be more willing to use staggered shared parking if the government subsidizes it.

and

Table 2. Constructs and measurement items on enterprise.

Constructs	Items	Content	Source and References
Attitude (ATT)	ATT1	Participation in staggered shared parking is beneficial to our company.	[28,29,32,34]
	ATT2	Participating in staggered shared parking can enhance our company’s corporate profile.
	ATT3	Staggered shared parking is a good way to deal with parking problems in residential areas.
Subjective norms (SN)	SN1	The positive participation of institutions and companies in the same field will encourage our company to share parking spaces.	[28,29,32,34]
	SN2	Encouragement from the government and streets will encourage our company to share parking spaces.
	SN3	Public approval and media advocacy will encourage our company to share parking spaces.
Perceived behavior control (PBC)	PBC1	The provision of staggered shared parking is within the management control of our company.	[28,29,32,34]
	PBC2	Our company has the conditions (parking resources) to provide the staggered shared parking spaces.
	PBC3	Our company has the ability (personnel, equipment, etc.) to offer staggered shared parking spaces.
Perceived risks (PR)	PR1	Our company considers that the provision of staggered shared parking will increase the cost of new parking equipment or improvements to existing equipment.	[43,45]
	PR2	Our company considers that the provision of staggered shared parking will increase our property management costs.
	PR3	Our company considers that uncontrollable intrusion by users of staggered shared parking will threaten the safety of our company’s operations.
	PR4	Our company considers that the privacy and security of users of staggered shared parking is in risk.
	PR5	Our company considers that it is difficult to guarantee the compensation of users in traffic accidents under staggered shared parking.
	PR6	Our company considers that participation in staggered shared parking will increase the pressure to resolve user parking conflicts.
	PR7	Our company considers that participation in staggered shared parking will raise the pressure on parking lot operations.
	PR8	Our company considers that participation in staggered shared parking increases the pressure to deal with traffic accidents.
Perceived benefits (PB)	PB1	Our company believes that participation in staggered shared parking will directly generate operational benefits.	[42,42,43]
	PB2	Our company believes that participation in shared parking will enhance our social reputation.
	PB3	Our company believes that participating in staggered shared parking is a good way to contribute to society.
Use intention (UI)	UI1	Our company is willing to try to provide shared parking spaces and participate in staggered shared parking.	[28,29,32,34]
	UI2	Our company is willing and plans to provide shared parking spaces and participate in staggered shared parking in the long term.
	UI3	With the government subsidy, our company is more willing to provide shared parking spaces.

. Five-point Likert-type scales, ranging from 1 (indicating “strongly disagree”) to 5 (indicating “strongly agree”), were used to rate the items. Experts and a few students were found to pre-research the questionnaire, adjust the content and the order of the questions to form the final release questionnaire. Based on the two hypothetical models designed in this paper, the latent variables of the research problem are addressed separately. Researching the demander impact factors using the combined TPB and TAM models, a total of 20 measures were designed; specific details are shown in Table 1. Provider studies, using a combined TPB and BRA model, with 23 measurement items, including latent variables ATT, SN, PBC, PR, PB, UI.

3.2. Survey and Data Collection

This research was approved by the institutional review board members and the questionnaires were obtained with the consent of the respondents. To ensure the validity of the questionnaire results, the questionnaire was guided by instructors and professors with relevant questionnaire design experience during the questionnaire design stage. Pre-research was also carried out, and more than 20 students and teachers were invited to pilot the questionnaire, with the purpose of finding errors in the questionnaire and the questions of items that expressed unclear meanings. After the deletion and modification of the questionnaire items, the questionnaire was ultimately formed for residents and enterprises, respectively. The questionnaires were both designed to include two parts, where the first part of the questionnaire for residents is the demographic information of the respondents (no private privacy questions), such as age group, education level, participation in shared parking status, parking usage time, etc. The second part is residents’ intention to use staggered shared parking, which covers the measurement of variables in C-TPB-TAM, including ATT, SN, PBC, PU, PEOU, UI. For companies, the first part of the questionnaire is the company attributes, company participation status, company parking status, etc. The second part is a survey on the company’s willingness to share staggered shared parking spaces, for which the C-TPB-BRA items cover 6 dimensions in terms of ATT, SN, PBC, PR, PB, UI.

Relying on the implementation project of Beijing’s staggered shared parking policy, during the interviews with enterprises and residents, this paper adopts an interview-type questionnaire to investigate the participation intention of enterprises and residents to achieve a more realistic survey result. The survey population is residents and corporate employees in the core urban area of Beijing. Because the implementation of staggered shared parking is already underway in the survey area, the survey population has some knowledge and awareness about that behavior to easily understand the original intent of the policy. Hence, respondents completing the self-administered questionnaire easily understood the short explanation and were less likely to have problems filling in the answers. The information of the questionnaires was collected and organized. Then, the acquired questionnaires were screened to exclude inauthentic (mainly data with all identical 5-level scale scores) and incomplete questionnaires to yield the valid data. A total of 323 and 240 questionnaires were obtained for enterprises and residents, respectively, with 282 and 211 valid questionnaires and yielding an effective rate of 87.3 and 87.9%.

3.3. Survey Data Statistics

When exploring factors that influence a certain behavioral decision, demographic characteristics information needs to be investigated prior to the willingness scale survey. Previous research indicated that the demographic variables show a consistent correlation with intention to evaluate to some extent [28,29]. This paper explores the factors influencing the implementation of staggered shared parking policies and investigates the opinions of both residents and businesses. For residents as demanders, the information on demographic characteristics and family parking demand were conducive to understanding the psychological activities of resident’s acceptance of policy specific operations and willingness to participate. Demographic variables of residents included gender, age, education level, the staggered shared parking participation, and family vehicle usage condition. The demographic information of the residents is listed in

Table 3. Demographic profile of residents (n = 211).

Group	Item	Frequency	Percentage
Gender	Male	137	64.9%
	Female	74	35.1%
Age group	Young people (18–30 years old)	105	49.8%
	Middle-aged people (31–45 years old)	70	33.2%
	Elderly people (46–60 years old and over 60 years old)	36	17.1%
Education level	College degree and below	27	12.8%
	Bachelor’s degree	87	41.2%
	Master’s degree and above	97	46.0%
Participation in the staggered shared parking system	Participated	41	19.4%
	Currently attending	29	13.7%
	Did not attend but intend to attend	114	54.0%
	Did not attend and not intend to attend	27	12.8%
Number of family vehicles	One car	184	87.2%
	Two or more cars	27	12.8%
Private car prices	Under 100,000 CNY	17	8.1%
	100,000–300,000 CNY	124	58.8%
	300,000–500,000 CNY	41	19.4%
	More than 500,000 CNY	29	13.7%
Workday parking demand	Less than 6 h	15	7.1%
	6–8 h	108	51.2%
	More than 8 h	88	41.7%
Holiday parking demand	Less than 6 h	15	7.1%
	6–8 h	17	8.1%
	More than 8 h	179	84.8%

.

Among these participants, 137 were male (64.9%) and 74 were female (35.1). Most of the participants were young people (age range from 18 to 30), 49.8 percent of investigators, followed by the middle-aged group (33.2%) and people over 46 years old (17.1%). Participants have a high level of education, 41.6 percent of them with bachelor’s degree and 46 percent of them over the bachelor’s degree. A total of 114 participants (54.0%) expressed one’s willingness to participate in the system although not involved, 70 (33.1%) had experience in the use of the staggered shared parking system, and the least number of them has no willingness. The survey on parking requirements of participants‘ families is as follows. None of the participants were non-car-owning household. Generally, the majority of them owed one car (87.2%), multi-car families (two or more cars) were a minority (12.8%). Their car price on the high side, the proportions of the vehicle prices from low to high is under 100,000 CNY 8.1%, 100,000–300,000 CNY 51.2%, 300,000–500,000 CNY 19.4%, and over 500,000 CNY 13.7%, respectively. Residents’ parking demand shows different characteristics during weekdays and holidays. During the working day, more than half of the respondents (n = 108; 51.2%) reported that it takes 6–8 h to park their vehicles at home, and 88 residents (41.7%) believe that parking time more than 8 h. During the holidays, almost all survey respondents (n = 179; 84.8%) felt that they parked their vehicles at home more than 8 h. And only a small number of participants (15.2%) have parking time less than 8 h.

For the enterprise as the supplier in the staggered shared system, the utilization of parking resources within the enterprise is an objective factor influencing behavioral decisions. The specific information is shown in

Table 4. Fundamental information of enterprise.

Group	Item	Frequency	Percentage
Enterprise type	Self-own parking property management companies	91	32.3%
	Non-property rights parking management companies	89	31.6%
	Authority enterprises and institutions	102	36.2%
Participation in the staggered shared parking system	Currently attending	89	31.6%
	Withdrawn after participation	104	36.9%
	Recent plans to attend	89	31.6%
Unused parking spaces on weekday daytime	None	80	28.4%
	Within 20%	156	55.3%
	20–50%	38	13.5%
	Above 50%	8	2.8%
Unused parking spaces on weekday nights	None	-	-
	Within 20%	4	1.4%
	20–50%	121	42.9%
	Above 50%	157	55.7%
Unused parking spaces on holiday daytime	None	55	19.5%
	Within 20%	99	35.1%
	20–50%	106	37.6%
	Above 50%	22	7.8%
Unused parking spaces on holiday nights	None	-	-
	Within 20%	-	-
	20–50%	41	14.5%
	Above 50%	241	85.5%

. It is considered that different types of parking lot operation models have different interests in this policy implementation process. In the questionnaire survey, the existing parking lot operation management types are divided into self-own parking property management companies, non-property rights parking management companies, and authorities’ enterprises and institutions, respectively, the proportion is 32.3, 31.6, and 36.2%. Among the respondents, most of the enterprises (n = 193; 68.5%) have participated in the policy, while more than half of them (n = 104; 36.9%) indicate that they have withdrawn. A total of 89 participants (31.6%) intend to supply their parking resources for residents’ use. Due to the working properties of the enterprise, the enterprises’ internal parking resources are dedicated to addressing the parking needs of employees during the workday. The core purpose of the policy is to make use of the unused resources of corporate parking at night to compensate for the demand of residents for night parking. The survey data confirmed the feasibility of the study in this paper. The usage of company parking is tight during the day on weekdays, with 156 respondents (55.3%) indicating that parking lot vacancy rate is between 20 and 50, and 80 respondents (28.4%) indicating that there are no available parking spaces. On the contrary, the night parking idle rate exceeds 50 and accounted for 20%; 20–50% accounted for 42.9%. During the daytime of the holiday, the parking lot idle situation is, respectively, 20–50% (37.6%), within 20% (35.1%); while parking resources are extremely abundant at night, nearly all participants (n = 241; 85.5%) reported parking availability was above 50 percent.

Subsequently, this paper uses SPSS 26.0 (IBM, Armonk, NY, USA) to analyze the reliability of the scale questionnaire. And structural equation modeling was constructed by used AMOS 26.0 (IBM, Armonk, NY, USA) to test the hypothesis model fitness and ultimately analyze the association among the potential variables of the model.

4. Empirical Analysis and Results

4.1. Measurement Model Testing

In this paper, the reliability analysis of the two questionnaire scale sections, respectively, was conducted using SPSS 26.0. The internal consistency results of the questionnaire were measured by Cronbach’s alpha coefficient. Generally speaking, when the value of Cronbach’s alpha coefficient is above 0.8, the reliability is good; when the value of Cronbach’s alpha is between 0.6 and 0.8, the reliability is acceptable [47]. The reliability of the two questionnaires showed good agreement, with Cronbach’s alpha values all above 0.6 (the lowest value was PB of 0.758) and generally above the 0.8 level. The specific data are shown in

Table 5. Residents’ measure results.

Variable	Mean	Cronbach’s Alpha	FL	CR	AVE
ATT1	3.8009	0.876	0.788	0.887	0.662
ATT2	3.7630		0.801
ATT3	4.1090		0.831
ATT4	4.3128		0.833
SN1	3.6540	0.844	0.838	0.868	0.687
SN2	3.6682		0.862
SN3	4.2749		0.784
PBC1	4.5308	0.866	0.740	0.798	0.569
PBC2	4.3175		0.828
PBC3	4.4502		0.689
PU1	4.2512	0.871	0.718	0.851	0.535
PU2	3.7867		0.733
PU3	4.1469		0.814
PU4	4.1232		0.637
PU5	3.4360		0.745
PEOU1	4.2986	0.784	0.761	0.726	0.569
PEOU2	4.1043		0.748
UI1	4.0900	0.940	0.928	0.935	0.828
UI2	3.9005		0.924
UI3	4.5355		0.877

and

Table 6. Enterprise measure results.

Variable	Mean	Cronbach’s Alpha	FL	AVE	CR
ATT1	3.5035	0.801	0.675	0.478	0.733
ATT2	3.5638		0.679
ATT3	3.9326		0.719
SN1	4.1206	0.897	0.885	0.685	0.867
SN2	4.2943		0.845
SN3	4.3688		0.747
PBC1	4.1667	0.962	0.901	0.852	0.945
PBC2	4.0993		0.935
PBC3	4.1560		0.933
PR1	4.1135	0.922	0.829	0.573	0.915
PR2	4.1915		0.822
PR3	4.0248		0.693
PR4	3.7872		0.700
PR5	4.0709		0.757
PR6	4.0284		0.685
PR7	4.1738		0.779
PR8	4.0426		0.778
PB1	3.5674	0.758	0.691	0.544	0.781
PB2	3.5957		0.756
PB3	3.9220		0.764
UI1	3.3936	0.891	0.803	0.594	0.814
UI2	2.5319		0.724
UI3	4.0106		0.783

.

This paper uses the Amos 26.0 analysis structural equation model to examine the research hypotheses. Before the model analysis, a validity analysis of the questionnaire needs to be conducted, i.e., to test the correspondence between the question items and the latent variables [48]. The structural validity is divided into two categories, the CFA and EFA. Due to the transformation of the model in this study, based on proven research, the adequacy of the model scales was analyzed directly by the CFA method. The three main indicators commonly used for a validity analysis are the following. Firstly, Hair [49] suggests that the factor loadings of each latent variable question items should exceed 0.50, with values preferably greater than 0.7 and p < 0.05. Secondly, the value of the average variance extracted (AVE) is greater than 0.5. In addition, the value of the composite reliability (CR) should be higher than 0.7. According to the above principles, as for the results of the analysis in Table 5 and Table 6, in general, it is assumed that the data analysis results of the hypothesis model present strong validity and internal consistency. Among them, the factor loadings values of PBC3 and PU4 in the resident measurements were close to 0.7, 0.689, and 0.637, respectively. Among the surveyed enterprises, a small number of the ATT, PR, and PB have factor loadings values close to the recommended value of 0.7, with the lowest value being 0.675. And the AVE value of the ATT is 0.478, close to 0.5, while the others are basically satisfied. Combining the results of the observed variables mean values and the factor loadings values, the core demand of the residents for staggered shared parking is to solve the problem of daily parking difficulties. Secondly, the users are concerned about the time it takes to find a parking space, the distance of the parking space from home, and the cost of parking. The reason for this analysis is that the policy is currently not well accepted in the core of Beijing and is less influenced by the people around it. However, more than half of the survey respondents said they had government and community organization and support, and they would be willing to try to get involved.

4.2. Empirical Verification of User

4.2.1. SEM Test Results

Structural equation modeling (SEM) was used to test the hypotheses in the proposed model. Byrne [50] pointed out that the goodness-of-fit indices is used to evaluate whether the hypothetical model fits with the collected data, which cannot indicate the goodness of the path analysis model. There is no single criterion to comprehensively evaluate the goodness of the model fitness, and scholars generally refer to the Bagozzi and Yi [51] model fitness evaluation criteria. This paper tests the hypothetical model of the residents studied in this paper with reference to the evaluation criteria, as shown in

Table 7. SEM goodness-of-fit results of residents’ model.

Statistical Test Quantities	Model Fitness Value	Recommended Value	Fit Judgment
χ2/df	2.063	1~3, indicate that the model is well adapted; >3, indicates poor model fit.	Fit
RMSEA	0.071	<0.08 (reasonable adaptation)	Fit
GFI	0.872	>0.90	Basic fit
NFI	0.902	>0.90	Fit
IFI	0.947	>0.90	Fit
CFI	0.947	>0.90	Fit

. Except for the GFI, which is close to the recommended values of fitness, all the other models are consistent, indicating that the theoretical model studied in this paper shows better consistency with the actual data.

4.2.2. Path Analysis

After confirming the model fitness, the results of the resident-side path analysis as a user are shown in Figure 6 and

Table 8. Results of path analysis of residents.

Hypothesis	Path	Coefficients	p-Value	Inference
H1	ATT→UI	0.247	***	Supported
H2	SN→UI	0.017	0.736	Not Supported
H3	PBC→UI	0.380	***	Supported
H4	PEOU→ATT	0.195	**	Supported
H5	PEOU→PU	0.634	***	Supported
H6	PU→ATT	0.630	***	Supported
H7	PU→UI	0.328	***	Supported
H8	PBC↔PEOU	0.906	***	Supported

** statistically significant at level of 0.05, *** statistically significant at level of 0.01.

and

Table 9. Test of path effect of residents.

Hypothesis	Intervening Variable	Direct Effect	Indirect Effect	Total Effect
SN→UI	--	0.017	--	0.017
PU→UI	ATT	0.328	0.156	0.484
ATT→UI	--	0.247	--	0.247
PBC→UI	--	0.380	--	0.380
PEOU→UI	PU	--	0.208	0.355
	ATT	--	0.048
	PU→ATT	--	0.099

. The results presented in the graphs indicate significantly that all the hypotheses are well supported (H1 and H3–H8). Specifically, the UI was positively affected by the ATT (0.247 ***), PBC (0.380 ***), and PU (0.328 ***), while not significantly affected by the SN (0.017). The PU (0.630 ***) and PEOU (0.195 **) were positively associated with the ATT, and the PEOU was positively associated with the PU. Meanwhile, there was a strong positive correlation (0.906 ***) between the PBC and PEOU. Thus, hypotheses H1–H8 were all supported except for hypothesis H2. In terms of the coefficient data in Figure 6 and Table 9, the PBC strongly influences the UI, followed by the PU. The path PEOU→PU→ATT showed a strong influence relationship.

From the hypothetical model, it can be noticed that the potential variables, such as the PU and ATT, can not only receive the influence of exogenous variables (e.g., PEOU) but also influence other variables (e.g., ATT), and such variables that have both exogenous and endogenous properties are mediating variables. Therefore, the indirect and direct effects of all the latent variables of the model were analyzed, as shown in Table 9. The regression coefficients of the direct effects between the variables in the chain mediation structure all reach a significant level. Further analyzing the effect of the mediating variables ATT and PU in the path analysis, the total effect of the PU (0.484), PBC (0.380), and PEOU (0.355) in turn showed a stronger effect intensity on the UI.

4.2.3. Qualitative Analysis

This study is concerned with analyzing the influential elements in the implementation of the staggered shared parking policy, in which the resident side adopts a hypothetical model of C-TPB-TAM to explore the key factors that residents care about in the process of participating in this policy. The hypothetical model proposed in this paper can highly evaluate the real thoughts of residents’ behavioral decisions.

The results of the experiment suggest that residents as policy users depend primarily on perceptual behavioral control (0.380) for their decision intentions in participating in the behavior of staggered shared parking. Meanwhile, the scale evaluation mean shows that the observed variable mean of the PBC is between 4.3 and 4.5 with the highest recognition. This reveals that individual residents understand the utility of the policy and whether they are eligible for the policy is directly related to the ease of completing this behavior, which directly affects behavioral intentions. This phenomenon is supported by the results of previous scholarly research in the sharing economy [52]. Meanwhile, the PU (0.484) and PEOU (0.355) directly and indirectly play a stronger role in promoting UI, where Jin Xie [23] confirmed that there is a compensation effect between the PB and PU in the shared parking. This relationship is expressed as the greater the benefit, the greater the tolerance of risk. Between the two, the PEOU influences the PU more strongly (0.634). In terms of the total effect, the effect of the PU on the UI exceeded that of the PBC, and this finding was supported by the results of Yu Ning’s study [29]. As well, the results of this study’s PU present a mediating effect consistent with Yu Ning’s research literature, which is in the PEOU → PU → ATT path and the PEOU → PU → ATT → UI path. It is emphasized that the PEOU has a vital role in the shared parking acceptance. For users, the perceived usefulness of the new policy and the ease of participation are crucial considerations. This is consistent with Liang’s research [28] that the PEOU and PU to some extent with PBC are based on mastering the resources (e.g., time, distance, and money) and opportunities (participation eligibility) that individuals have. The ATT has a positive impact on the UI, but not significant. Among other things, the residents generally agreed that the implementation of a staggered shared parking policy would be more beneficial to the management of the parking resources within the residential neighborhoods. However, the study hypothesis H2 did not support this, which is supported by Yu Ning’s finding [29]. The SN has a non-significant positive effect on the UI; the reason could probably be the lack of prior experience in practicing shared parking. This statement can be referred to in the findings of Chu Zhang [53] who confirmed that an important factor influencing the participants willingness to share is their pervious participation experiences. This is a reasonable explanation considering the current low awareness of staggered shared parking.

4.3. Empirical Verification of Supplier

4.3.1. SEM Test Results

According to the evaluation criteria in Section 5.2, the hypothetical theoretical model fitness of the enterprises in this paper is verified, and the results are shown in

Table 10. SEM goodness-of-fit results of enterprises’ model.

Statistical Test Quantities	Model Fitness Value	Recommended Value	Fit Judgment
χ2/df	2.686	1~3, indicate that the model is well adapted; >3, indicates poor model fit.	Fit
RMSEA	0.077	<0.08 (reasonable adaptation)	Fit
GFI	0.855	>0.90	Basic fit
NFI	0.899	>0.90	Basic fit
IFI	0.934	>0.90	Fit
CFI	0.934	>0.90	Fit

. Of these, the GFI and NFI are slightly less than the recommended values but are considered acceptable. It is confirmed that the theoretical model designed in this paper can predict the actual data.

4.3.2. Path Analysis

The results of the enterprise-side path analysis as a supplier are shown in Figure 7 and

Table 11. Results of path analysis of enterprises.

Hypothesis	Path	Coefficients	p-Value	Inference
H1	ATT→UI	0.426	**	Supported
H2	SN→UI	0.329	***	Supported
H3	PBC→UI	0.216	***	Supported
H9	PB→ATT	0.612	**	Supported
H10	PB→UI	0.170	0.214	Not Supported
H11	PR→ATT	−0.372	***	Supported
H12	PR→UI	−0.221	**	Supported
H13	PR⇔PB	−0.708	***	Supported
H14	PR⇔PBC	−0.419	***	Supported

** statistically significant at level of 0.05, *** statistically significant at level of 0.01.

and

Table 12. Test of path effect of enterprises.

Hypothesis	Intervening Variable	Direct Effect	Indirect Effect	Total Effect
SN→UI	--	0.329	--	0.329
ATT→UI	--	0.426	--	0.426
PBC→UI	--	0.216	--	0.216
PB→UI	ATT	0.170	0.261	--
PR→UI	ATT	−0.221	−0.158	−0.379

. The results presented in the graphs indicate significantly that all hypotheses are well supported (H1–H3, H9, and H11–H14). Specifically, the UI was positively affected by the ATT (0.426 **), SN (0.329 ***), and PBC (0.216 ***), negatively affected by the PR (−0.221 **), while not significantly affected by the PB (0.170). In addition, the ATT was shown to be positively affected by the PB (0.612 **) and negatively affected by the PR (−0.372 ***). Meanwhile, there is a negative effect between the PR and the two latent variables PB and PBC. Thus, hypotheses H1–H3 were supported and H9–H14 were supported, except for hypothesis H10. In terms of the coefficient data in Figure 7 and Table 12, the ATT strongly influences the UI, followed by the SN and PR.

It can be seen that the ATT serves as an intermediate variable in the firm study model. The degree of influence of endogenous, exogenous, and intermediate variables on the UI were further analyzed, and the test results are shown in Table 12. Considering that the latent variable PB in the chain-mediated structure does not have a significant direct effect on the UI, its total effect cannot be statistically analyzed. Comparing the total effect values, the variable with the largest effect on the UI is the variable ATT, followed by the SN, and the variable with the largest negative effect is the variable PR.

4.3.3. Qualitative Analysis

This paper attempts to use the C-TPB-BRA research model to explore the elements of concern for companies in the process of implementing a staggered shared parking policy. As parking providers, different types of parking management companies have similar concerns regarding the consideration of participation in the policy. The hypothetical model proposed in this paper can highly evaluate the real thoughts of enterprise’ behavioral decisions.

Of the many potential variables that affect the UI, the ATT shows the strongest positive impact on its total effect on the UI (0.426). Secondly, the SN is stronger to directly influence the UI (0.329). Finally, the PBC and PR effects on the UI were not prominent (direct effect) and the PB effect was not significant. The above findings are consistent with previous research [30,52]. But the finding that the PR presents a stronger negative impact on the UI in the total impact cannot be ignored, which is supported by Yu Wang [45]. The means of the three observed variables for the SN indicate that firms’ decisions to provide parking resources are strongly influenced by government streets and mass media attitudes, and the specific data are shown in Table 6. To a certain extent, attitudes predict the behavioral intentions of the company, and at the same time, it is emphasized that the factors PB and PR determine the formation of the ATT. In other words, the PB (0.612) and PR (−0.372) indirectly influence the UI through the ATT, and the degree of impact is strong. It is worth noting that Yu Wang pointed out that the PB has a relatively strong impact on consumer willingness when the PR is regarded as a higher effect. This confirms the findings of Chu Zhang’s study [53] that the supplier always put more concern on their own parking demands ahead of sharing decisions. A further analysis is as follows. Among the PBs that contribute to the positive attitudes of providers, the influence of PB3 is more significant, indicating that other types of parking management companies, except for institutions, pay equal attention to the ability to contribute to society [43]. At the same time, the average of the PR observation variables (all mean values exceeded 4.1) shows that companies are more concerned about the cost of equipment replacement, management, and operation among the possible risks of participating in staggered shared parking. The following is the consideration of security issues, including the user’s uncontrollable trespassing behavior affecting the normal operation of the company, possible traffic accident disputes, and user privacy security. Management pressure is not significant, compared with Yu Ning’s findings [29] that the PR of shared parking is conceptually examined in terms of cost risk, safety risk, and management pressure. Cost risk is the strongest influence, which is consistent with this author’s study. The reason for the insignificant PBC analysis is that the surveyed companies generally have the conditions and capacity to provide parking spaces and therefore have less influence on behavioral decisions.

5. Discussion and Conclusions

5.1. Governmental Explanation

The initial intention of the staggered shared parking policy is dedicated to solving the problem of difficult parking for residents living at night. The policy relies on government forces to promote the active use of residents and the active participation of businesses in providing parking resources. Yu Ning [29] pointed out that the countermeasures from the government level are of great importance to help develop an initial but substantial push for the generation of domino reactions. This paper attempts to use the theory of planned behavior extended model to explore the core factors in terms of exploring the factors influencing the behavioral intentions of the users and providers of the policy regarding participation in the policy. We tracked the implementation process of the policy and develop a hypothetical model for the research, including a questionnaire survey and an analysis of the model. Based on the above research results, we provide the government with referenceable and scientific recommendations for policy implementation.

For participants, PBC showed the strongest influence on residents’ behavior in using the staggered shared parking policy. Meanwhile, PU and PEOU play a non-negligible positive role in the overall impact (including the direct and indirect effects) of UI. To further explore the observed variables of the potential variables, firstly, the government needs to pay attention to the political advocacy in a way that is easy for residents to understand. The purpose is to enable residents to understand the procedure for using the policy, the conditions of use, and the ways to participate. Among them about the use of operations here are different from previous studies [54] using new technology techniques; this paper focuses more on the offline contact community to complete the participation behavior of the staggered shared parking policy. Second, to visualize the direct benefits that can be gained from participation in the policy, the results of the study show that the most important factors influencing residents’ parking needs include the time, distance, cost, and comfort of finding a parking space and completing the act of parking. Based on residents’ concerns, the government attempts to match residents with the optimal staggered shared parking spaces with multi-dimensional trade-offs.

For providers, ATT was shown to have the strongest influence on UI, and the next major influence is the SN. At the same time, firms’ attitudes are significantly influenced by predictable perceived risks and perceived benefits, which ultimately contribute jointly to behavioral intentions. It is clear that companies take the government’s attitude seriously [55]. As companies weigh the pros and cons of participating in this policy, the role of government in promoting active business participation is indispensable. In order to increase business engagement, the underlying logic is to reduce business risk as well as enhance potential benefits [20,29]. On the one hand, the government develops the incentive mechanisms. The participation of companies can be stimulated with the ability to provide parking spaces through subsidies [23], corporate reputation, social contribution, etc. On the other hand, the government should assume the credit endorsement for the residents. Yu Ning [29] recommended that a user integrity mechanism could be built and the residents who violate the regulations can be penalized to avoid a crisis of trust if users do not remove their vehicles beyond the shared time, users enter corporate offices privately, etc. All of these potential problems require a credible government to endorse residents, thus increasing business trust [28,55].

5.2. Theoretical Implications

This study provides theoretical applications on the impact of policy implementation in the shared parking field. In previous studies, psychological models (such as the TPB, TAM, etc.) have been widely used to explore the intention to participate in shared parking. The research model was expanded in a relatively single direction, for example, residents or managers only. And to the best of our knowledge, we are the first to explore the perceived intention of this complex behavior during the implementation of a staggered shared parking policy. From the real practice of the policy, we examine the core factors that inherently affect its implementation. This paper focuses more on the influence mechanism of the implementation of the staggered shared parking policy. This policy is targeted at solving the parking demand of residential living. The parking resources are provided by the authorities, enterprises, and institutions with the conditions near the residential areas. The implementation of the staggered shared parking policy requires the joint cooperation of residents, enterprises, and the government. As the government is the policy administrator, this paper explores the influential elements of this policy, mainly around two subjects, the residents and enterprises, as well as constructing different hypothetical models for specific studies, respectively. This is helpful for advancing the shared parking to the cities. And this theoretical research that can truly guide practical applications.

This study proposed two structural models on the theoretical basis of the TPB to examine residents and enterprises influence factors in terms of accepting the staggered shared parking policy. Based on the TPB model, we incorporate the TAM model (including the latent variables PEOU and PU) to explore the mechanisms influencing residents’ use of the policy. We confirm that PBC has the strongest effect on residents making this decision, which is supported by Duy Quy Nguyen-Phuoc [52] who highlighted that the impact of PBC derives from the perception of passengers that the service is easily accessible. Different findings include Ziboud Van Veldhoven’s [56] study in which subjective norms are the most influential factor in the public’s willingness to use shared mobility in Belgium, followed by PBC. PU was shown to exert the most decisive influence on use intention in terms of its total effect, which is in line with previous research about the sharing economy [28,29,57]. Moreover, the results of this study confirm that the PU and PEOU play a crucial role in the total impact of UI, for which this conclusion is in accordance with previous studies [23,29].

This study integrates perceived risks and perceived benefits (the BRA model) into the TPB research model to examine the multiple intrinsic factors on usage intentions about firms’ participation in staggered shared parking policies. The previous literature [25,53] has studied the provider of shared parking in terms of the resident or driver, while the role of companies has not been explored. To our best knowledge, this study is the first work to explore the different companies in studying shared parking acceptance and perceived intention, which is significant for further study. We confirmed that the company’s focus is different from that of an individual, as it needs to consider the interests and reputation of a company. And the focus of attention will vary depending on the type of parking management company. This paper concludes that ATT has the greatest influence on a company’s intention to participate in shared parking, which is supported by Yu Ning [29] and Duy Quy Nguyen-Phuoc [52]. Moreover, ATT is jointly influenced by numerous observed variables of PB and PR, which is supported by Yu Wang [45] who emphasized the relative relationship between them.

5.3. Practical Implications

This paper explores the mechanisms that influence the participation of residents and businesses in staggered shared parking policies. Based on the previous research on residents’ willingness to use shared parking, this paper focuses more specifically on the group of residents who do not have a fixed parking space. Compared to high on-street parking fees, this policy can provide a good choice for users with daily nighttime parking demand that has a good price and a suitable location. In exploring the influence of user intention to use, the PBC shows the most positive impact on the UI. The findings are consistent with the Liang study [28], which suggests that residents’ willingness to participate in a staggered shared parking policy relies not only on resources requirement and abilities but also on whether residents are eligible and conditioned to participate. Therefore, the government needs to stimulate companies which are eligible for sharing and around residential areas to actively participate in this policy. The government needs to make many efforts to deploy the supply and demand of shared parking resources.

The company’s internal parking resources are fully utilized, taking advantage of the complementary relationship between the company and the residents in terms of parking hours. The providers of staggered shared parking are businesses. By exploring the influencing factors of the provider, ATT has shown the strongest influence on UI. At the same time, ATT is jointly influenced (directly and indirectly) by the PR and PB. The providers differ from other studies [28], but the providers all have a common concern with the safety and risk involved in the participation process. The BIS [58] recommended establishing Disclosure and Barring Service Checks to protect providers by setting certain conditions of participation. Businesses and individuals think similarly; they also need to be provided peace of mind and more willingness to get involved. The research analysis shows that it is vital that the government should set up an incentive mechanism and a credit mechanism, which is consistent with the recommendations of Li et al. [20], Liang et al. [28], and Yu Ning, [29]. Through the power of policy, it can reduce the risk undertaken by companies and provides business insurance.

5.4. Limitations and Future Research

The present study also has some limitations. The first point is that the subject of this study is specific, and the study area is in the core urban area of Beijing. It is characterized by a developed economy, inadequate parking resources, and policies that have been implemented in the area to some small extent. Survey respondents included both those who had participated and those who had not. If extended to other cities of different size classes, further in-depth studies are needed in the future. For example, Shanghai and Chengdu are already exploring shared parking policies.

The second point is that there are several types of shared parking management companies, and this paper analyzes the potential psychological factors of three types of companies. However, the differences in specific impact mechanisms were not considered in our research; their influence deserves further attention. This could be helpful in guiding the government to develop different incentive policies.

As a final point, this paper extends the psychological theoretical model of planned behavior by adding other potential variables (PB, PR, PEOU, and PU) that could better characterize the study of staggered shared parking policies and yield valuable findings. However, the effect of exogenous variables influencing perceptions on behavioral intentions was not considered in relation to the sociological characteristics of the policy. Scholars used regression analysis methods combined with the theory of planned behavior to conduct empirical and theoretical analyses of exogenous variables affecting the ATT, PBC, and SN. Thus, the impact mechanism of this policy can be further studied in the future based on this idea.