Investigating Critical Factors That Encourage Private Partners to Participate in Sports and Leisure Characteristic Town Public-Private Partnerships: Evidence from China

Abstract

The Sports and Leisure Characteristic Town (SLCT) has become a reasonable strategy for enhancing the sustainability of new urbanization processes in rural China. Although the Chinese government has issued a series of policies to support the development of SLCTs, limited financial resources are a major obstacle. Thus, public-private partnerships (PPPs) have been increasingly encouraged for establishing SLCT projects. However, the factors that significantly influence private partners’ willingness to participate in SLCT PPP projects remain unclear. The authors of this paper conducted expert interviews and questionnaire surveys concerning the SLCT PPP projects that have been implemented in China, identifying 23 factors that can be grouped into five major components using principal component factor analysis. Multiple linear regression was then performed to evaluate the relationships between factors and private partners’ willingness to participate. The results indicated that the factors that critically influence private partners’ willingness to participate include stakeholder factors, the internal factors of private partners, external environmental risk factors, the supporting measure factors of SLCTs, and the locational factors of SLCTs. This work also offers suggestions for encouraging private partners to participate in SLCT PPP projects. This study can provide a theoretical basis and practical guidance for government and private partners in order to help them implement sustainable SLCT PPP projects.

1. Introduction

The level of urbanization in China will reach 60% by 2020 and 70% by 2035 [1]. Although China has rapidly become urbanized over the past four decades, its urbanization rate was 59.58% by the end of 2018 [2], which is lower than the average urbanization rate of 80% in most developed countries today [3]. During the process of urbanization in China, some unsustainable issues presented themselves due to dual structure mechanisms such as the tremendously uneven development between urban and rural areas and significant income differences between urban and rural residents [4,5]. Therefore, the Chinese Government proposed the Rural Revitalization Strategy in 2017 to increase farmers’ incomes and stimulate sustainable rural development relating to economic, cultural, and ecological aspects. In particular, the Characteristic Town (CT) is regarded as one of the prominent drivers of urban-rural economic development that will play a key role in achieving sustainable targets in Chinese urbanization, industrialization, and agricultural modernization in the 21st century [6,7]. Chinese CTs are different from traditional small towns [8] because they are defined as an innovation and start-up platform rather than as an industrial park or administrative town. Similar to India, most small towns are administrative towns that are managed by the government [9].

Different types of CT projects are constructed in China, with the characteristic of New Innovative industry, High-end Manufacturing industry, Eco-tourism, etc. In essence, different types of CT projects depend on leading industries. Experiences from the developed world have demonstrated that when the per-capita income of residents reaches more than $5000, residents tend to look beyond their basic material necessities to improve their health and spiritual lives [10] by taking part in sports and leisure activities. In 2017, the per-capita income of Chinese residents reached $8836 [11]. Therefore, several Sports and Leisure Characteristic Town (SLCT) projects have recently been implemented in China. SLCT projects primarily revolve around activities related to the sports and leisure industry, in addition to the tourism, health, culture, education and training, and big data industries. According to official statistics from the General Administration of Sports, there were 96 pilot SLCT projects in the country in 2017 [12]. As one of the critical tasks of new urbanization construction [13], SLCT projects can promote sustainable development in the sports industry, boost local economic growth, reduce poverty issues, and satisfy people’s dreams to live positive and fulfilling lives. When the per-capita income reached $8000, the sports industry became one of the pillars of the national economy [14]. In 2019, the annual per-capita income in China had grown to $10,000 [15]. However, sports industry investments account for only 1% of the gross domestic product (GDP) and they are expected to contribute to roughly 4% of the GDP by 2035 [16]. Therefore, the development of SLCT projects is necessary to improve the country’s sustainable economic development.

There exist various barriers to the implementation of SLCT projects, such as complex construction, large investments and long operation periods [17]. Indeed, some CTs have faced termination due to shortages in funds [5,18]. On average, about $7191.45 million is invested in each CT. By 2020, it is estimated that $71,914.5–$12,944.61 million will have been invested in 100 SLCTs [19]. With less than $8629.74 million in local revenue among cities in 2017, this represents a significant financial challenge. Therefore, public-private partnerships (PPPs) have been proposed by the government as promising measures for effectively combining the advantages of governmental policy with the funds and operational benefits of private partners [20]. PPPs have widely been applied in infrastructure projects, such as water conservancy facilities, transportation infrastructures, and waste-to-energy plants [21]. The majority of existing research has focused on the practical construction and operational issues of SLCT PPPs. As an example, most failed CT PPPs have resulted from inappropriate risk allocations [22]. Several studies have identified some risk categories and proposed developmental paths to counter these risks for SLCT PPPs [17,23,24]. There are a limited number of studies that have explored the potential barriers to SLCT PPP projects from the perspective of stakeholders. As the key stakeholders involved in SLCT PPP projects, private partners play a vital role in SLCT PPPs. Their willingness to participate is critical to the implementation of SLCT PPPs [25,26] and directly contributes to sustainable urbanization. Nonetheless, it is unclear if private partners in China are willing to participate in SLCT PPP projects, and the factors that contribute to their willingness to participate remain uncertain.

In order to fill this research gap, the current paper aims to explore the critical factors that affect private partners’ willingness to participate in SLCT PPP projects in China. The results can contribute to the provision of effective suggestions for the government to create policies that attract the participation of private partners, ensuring the sustainable development of SLCTs so that the eventual target of new, high-quality urbanization is achieved.

2. Literature Review

2.1. Characteristic Towns (CTs)

Howard’s theory of a ‘Garden City’ was the theoretical source for guiding the construction of CTs [27,28]. It focused on urban-rural integration and targeted cities with perfect urban infrastructure and industrial allocation, such as cities with pastoral scenery. The idea of the garden city has a significant influence on the city planning projects of Western countries. To achieve sustainable development, a number of garden cities have been established in the United States, Canada, Australia, and Germany. As an example, the United States has developed various types of CTs that are home to unique values, lifestyles, and economic development patterns [29].

In China, the concept of the CT, or ‘Tese Xiaozhen’, was first proposed in 2014 and was later defined by several scholars from multiple points of view. Although CTs refer to towns, they are actually ‘cities’ with clear boundaries to growth and the industrial chain [30]. A CT is a form of industrial space organization [31] and courier station that coordinates the development of the urban and rural economy [7]. Therefore, this paper views the CT as a relatively independent space development platform with evident and distinctive industry and culture that adhere to local conditions. The roles of industry, traditional culture, environmental protection, and ecology in CT construction were identified in research abroad [32,33], and concerned the wishes and interests of these cities’ residents [34,35]. CT research in China has mostly been performed from the perspectives of meaning, type, developmental status, and strategies for constructing CTs. It has also examined issues relating to culture [36,37,38,39], space [40,41,42], the characteristics of regional economies [43,44,45], the extent of coupling [46,47], supply-side reform [48], and innovations in ecosystems [49], etc.

2.2. Sports and Leisure Characteristic Towns (SLCTs)

At present, the literature related to SLCTs primarily focuses on the developmental paths and driving forces behind these projects. Under the domain of industrial research, Zhang [50] studied the meaning, categories, and developmental paths of SLCTs and concluded that SLCTs functioned as platforms for national development and sports industries with a focus on sports and leisure, along with health, pension, tourism, culture, training, and big data industries. These findings have garnered support in other studies by Lv [51], Bai and Meng [52], Liu and Zhang [24], Hu [53], and Zhang [54]. According to the PPP project libraries that cover all PPP projects in China [55], more than half of the SLCT pilot projects have been developed by PPPs, and most of the SLCT PPP projects are located in Central and Western China (see Figure 1). These SLCTs have a positive correlation with local economic development [56]. As one of the pilot SLCT projects in 2017, the Mashan SLCT in Guangxi Province saw its poverty rate decrease from 20.22% in 2016 to 5.91% in 2019 because of the effective industrial integration and development of sports and tourism. In addition, the Mashan SLCT’s tourist and tourism consumption numbers increased by 57.32% and 52.7%, respectively, in 2018 [57]. Similarly, the cycling industry generates an average of $1.5 million per year in the city of Fruita, USA [14].

However, construction of SLCTs in China remains unsustainable due to massive shortfalls in funding, limited resources, excessive intervention from government administrations, and serious tendencies towards real estate development [58,59]. Insufficient funds and resources are regarded as the bottlenecks of CT projects [5,9,18,60,61], and are hampered by a substantial need for investment and lengthy payback periods [18,43,62,63]. In order to boost the sustainability of SLCT construction and operation, some suggestions were put forward by analyzing the operational modes of SLCTs across the globe, which included activities such as attracting social capital investments [64,65,66,67,68]. The private partners’ willingness to participate is the principal force behind the sustainable development of SLCTs. Nevertheless, few private partners are willing or able to invest in SCLTs due to the high down payments that are required to begin these projects, a sum which amounts to $142,205 in China [69]. Thus, finance is the critical issue that hinders the sustainable development of SLCTs. However, only a few studies have investigated the financial issues of SLCT projects. Therefore, this paper introduces the PPP model to SLCT projects.

2.3. PPP Model

The PPP model originated in Britain and has become widely adopted in developed countries that have completed their urbanization. The PPP model has been proven to be a desirable option for boosting infrastructural projects [70,71] in the United States, Spain, Australia, the United Kingdom, and China [72]. It has extensively been employed in the field of transportation [63], environmental and urban governance [73], the waste and garbage disposal industry [74,75], in electric vehicle charging infrastructure [76], the reconstruction of buildings [77], and housing delivery [78,79]. It can help a government to achieve its economic goals and raise the level of its public services [80]. Nonetheless, less attention is paid to the social dimensions of sustainability in PPPs [81].

Financing is critical to the success of PPP projects [82,83]. Existing studies that have examined the risk allocation and operation mechanism of PPPs in infrastructure [84,85] and CT construction [5,17,71,86,87,88] have concluded that private partners are inclined to invest in projects with less risk [89]. Therefore, the PPP model is well-suited to SLCT construction due to its ability to satisfy multiple partners’ interests and demands [18,73,90] by way of funds, talent, operational experience, and financial insurance [91]. Private partners are the key stakeholders in SLCT PPP projects [17,92,93], and their willingness to participate can directly contribute to sustainable urbanization. Related studies have explored the selection criteria for private partners from the perspectives of governments [94,95] and the willingness of private sectors to invest in the infrastructures PPP projects from case studies in the UK [25,96,97] and emerging markets [23,94]. Research into private partners’ willingness to participate in SLCT PPP projects has not been performed yet. At present, more than 12 central policies have been proposed to encourage enterprises to effectively invest in SLCTs in China. These policies consist of reducing the proportion of minimum project capital to a maximum of 15%, issuing special bonds, encouraging financial institutions to participate in PPP-related equity investments, and severely punishing the dishonesty of local governments [69]. These measures are likely to substantially reduce the pressure for private partners and encourage them to invest in SLCTs. Because it is necessary to examine if these policies can realistically attract private partners to participate in SLCTs, this paper will validate their effectiveness below.

2.4. Critical Factors Identified in PPPs

To identify the critical factors that affect private partners’ willingness to participate in SLCT PPP projects, it is essential to review the factors that relate to PPPs from previous research (see

Table 1. List of Critical Factors Affecting PPP Projects From Previous Research.

Critical Factors Affecting PPP Projects	References	Critical Factors Affecting PPP Projects	References
1. Government policy	[17,98,99,100,101]	11. Supervision mechanism	[98]
2. Public participation	[98,102,103,104,105]	12. Project complexity	[17,87,100,102]
3. Financing capacity	[98,100,106]	13. Profitability of projects	[25,26,99,101,103,106]
4. Cooperation channel	[98,99]	14. Market demand of industry	[17,99]
5. Information publicity	[98,101]	15. Experience in PPPs	[5,97,107]
6. Contractor management	[5,17,98]	16. Institutional environment	[17,91,107]
7. Economic environment	[17,98]	17. Return mechanism	[61,91,106]
8. Operational capability	[98,106]	18. Financial strength of enterprise	[102,103,108]
9. Risk management	[17,91,98,100,103,106,109,110]	19. Enterprise’s concept	[106,111]
10. Performance ability	[91,98]	20. Culture risk	[17,87,111]

).

Ye et al. determined that there are 11 critical success factors (CSFs) that affect the cooperative efficiency of PPP projects [98], including government policy (the primary factor), public participation, capacity for financing, channels for cooperation, information publicity, contractor management, the economic environment, operational capability, risk management, performance ability, and supervision mechanisms. A project’s complexity is negatively correlated with private partners’ willingness to participate [102]. Qi et al. investigated the reasons behind failed PPP projects in China and identified several risk factors such as changes in the law, approval delays, financing, insufficient market revenue, and changes to market demand [99]. Tang and Shen [107] concluded that the relationship between organizations within the public and private sectors and their past experiences with PPP projects were critical to the success of PPP projects. For private partners, high profitability and prosperous experiences in PPP projects have significantly influenced their willingness to participate [25,26,87,91,102,103,112]. Li [91] highlighted certain obstacles that can affect private partners’ willingness to participate in public service programs, such as the institutional environment, the spirit of contracts, risk security, and return mechanisms. Among these factors, private partners are most concerned with return mechanisms [61,91]. Furthermore, fair risk allocations [103,109,110], powerful financial strength [102,103,108], and public support [102,103,104,105] have proven to be key elements in attracting the participation of private partners in PPP projects. Ye and Shi [102] noted that there is no evidence that public support and the institutional environment can affect an enterprise’s willingness to participate in PPPs.

Wu [100] identified six risks related to CT projects, including risks related to policy, marketing, technology, financing, industry, and force majeure. In addition, Wan et al. [111] discovered several risks in CT PPPs, such as those that exist in the background environment, government support, social capital, sharing, population, the enterprise concept, culture, financial support, and the publicity of government information. Lai [87] proposed other risks that included the uniqueness of characteristic culture, industrial integration and positioning, and costs, etc. Within the entire process of CT PPPs, Zhu [101] observed legal risks, procurement procedure and payment risks, project contract risks, project company risks, and exit risks. In the SLCT PPPs, Shao and Guo [17] identified administrative and policy risks, legal and special statute risks, risks for public objections, financial risks, technological risks, macroeconomic risks, sports and leisure risks, marketing risks, construction risks, and force majeure risks. Hu and Wang [106] opined that single industries, unreasonable charging mechanisms and profit models, insufficient construction and management capacity, and the absence of risk sharing mechanisms can weaken enterprises’ willingness to participate in tourism PPPs.

3. Methodology

By retrieving the relevant literature and conducting expert interviews, this study identified the factors that affect private partners’ willingness to participate in SLCT PPPs. A questionnaire survey was then administered to investigate private partners’ willingness to participate in SLCT PPPs, along with the significant factors involved. Based on the results of the questionnaire, a factor analysis and multiple linear regression analysis were performed using Statistical Product and Service Solutions (SPSS) (25.0) software to determine the relationships between the factors and the private partners’ willingness. The corresponding methodologies are shown in Figure 2.

3.1. Preliminary Factor Identification Based on Literature Retrieval

First, a retrieval of the literature was conducted to establish a relatively complete indicator system for factors [113]. By examining the pertinent factors associated with PPPs and the real dilemmas that SLCT projects encounter, the list of factors that affect private partners’ willingness to participate in SLCT projects were initially identified by existing literature (see

Table 2. Preliminary Identification—List of Factors Influencing Private Partners’ Willingness to Participate in Sports and Leisure Characteristic Town (SLCT) Projects.

Influence Factor	Reference	Influence Factor	Reference
1. Government support	[5,96,97,106,114,115]	11. Operational capability of enterprises	[5,86,103,116]
2. Economic situation of characteristic town	[5,111]	12. Economic strength of enterprises	[91,108,117]
3. Traffic situation of characteristic town	[116,118]	13. Enterprises’management experience of PPPs	[5,97,107,117]
4. Ecological environment of characteristic towns	[5,106]	14. Enterprises’ experience of characteristic towns	[94,95,97,119]
5. Market demand	[5,17]	15. Enterprises’ concept	[5,106]
6. Construction complexity of projects	[17,86,97,112]	16. Financial institutions’ support for financing	[17,94,95]
7. Profitability of projects	[17,25,26,97,103,110]	17. Contractors’ compliance with the contract	[5,17,87]
8. The distinct local culture	[87,106,120]	18. Suppliers’ ability to provide materials for projects	[5,17,87]
9. Macroeconomic risks of investment such as interest rate, exchange rate, and inflation	[17,87]	19. Public support	[103,105,121]
10. Participation of intermediaries in risk management	[17,87,109]	20. Support and supervision of the media	[17,103]

).

3.2. Final Factor Identification Based on Expert Interviews

Based on the preliminary identification factors shown in Table 2, expert interviews were conducted to modify the initial factor list and to ensure that the factors were suitable for SLCT construction in China. The expert interview method has been widely adopted in research on the construction industry due to the complexity and professionalism involved in construction [120]. An authoritative expert database was used to select 20 experts from the China Public Private Partnerships Center and Chinese Characteristics Towns Network, most of whom were university academics, outstanding private partners, or policymakers who had engaged in CT PPPs for at least 5 years. The interviews were held at PPP Conferences at a university. After 20 factors were proposed to the experts, four questions about SLCTs were put forward.

Q1: What are the barriers in implementing CT projects?

Q2: What are the barriers in implementing CT PPPs?

Q3: What is your opinion about the initial influencing factors?

Q4: What are your suggestions for increasing private partners’ willingness to participate in CT PPPs?

After the expert interviews, three additional factors were added to better incorporate a Chinese context:

• The Population in the Surrounding Towns.
  The interviews presented the hypothesis that the shortage of important resources, such as labor and talent, will restrict regional development. At present, there is a relatively low number of residents in the surrounding towns who are familiar with the sports culture of towns who support the construction of SLCTs. However, because the success of these projects relies on the initiative of China’s citizens [122], the quantity and quality of the population will be considered.
• Leaders’ Personal Tendencies.
  Leaders are individuals or collectives who make the strategic decisions for enterprises. In general, leaders’ non-power influence is more significant than their power influence [123]. In reality, leaders who prefer leisure sports are inclined to be interested in sustainable projects for society. Zhongtifeixing, an enterprise, whose leader is Leiming Zhao, invested in the Xujiaya SLCT in 2016. As a top airline athlete, Zhao wanted to encourage people to participate in the aviation flight movement. Therefore, a leader’s personal tendencies should be considered.
• Industrial Convergence Capacity for Enterprises.
  All experts pointed out that industrial chain integration is key to the development of CTs. Wei and Zhang [18] indicated that the sports and leisure industry needs to integrate other industries into its top-level design. For SLCT projects, this type of integration can benefit tourism, sports, and high-tech industries, among others. A convergence of industries will also be evident during the operations stage. Therefore, the capacity for enterprises to converge their industries increases their willingness to participate in SLCT PPPs.

The final 23 factors that affect private partners’ willingness to participate in SLCT projects are summarized in

Table 3. Final Factors that Influence Private Partners’ Willingness to Participate in SLCTs.

Codes	Factors
F1	Government support
F2	Economic situation of sports and leisure towns
F3	Traffic situation of sports and leisure towns
F4	Ecological environment of sports and leisure towns
F5	Market demand for the characteristic industries of towns
F6	Construction complexity of towns
F7	Profitability of sports and leisure town projects
F8	Characteristic culture of towns
F9	Macroeconomic risks of investment such as interest rate, exchange rate, and inflation
F10	Intermediaries’ participation in risk management
F11	Operational capacity for enterprises
F12	Enterprises’ economic strength
F13	Enterprise’ experience of PPP project management
F14	Enterprise’ experience of participating in characteristic towns
F15	Enterprise concept
F16	Financial institutions’ support for financing
F17	Contractor’s compliance with the contract
F18	Suppliers’ ability to provide long-term materials for projects with stable prices and quality
F19	Public support
F20	Media supervision
F21	Population in the surrounding towns
F22	Leaders’ personal tendencies
F23	Industrial convergence capacity for enterprises

.

3.3. Empirical Analysis

3.3.1. Questionnaire Design

By using empirical methodology [124], questionnaire surveys can serve as an effective research method for quantitatively analyzing data and drawing scientific conclusions [92]. Akintoye and Skitmore’s study [125] of pricing approaches in the construction industry forms the basis of the current paper’s empirical study. Therefore, the questionnaire method this paper adopts was applicable for investigating the significant factors that influence private partners’ willingness to participate in SLCT PPPs. The questionnaire was designed for respondents whose occupational positions were at an average or high level within the enterprises for which they worked. The first part of the questionnaire focused on the respondents’ demographic characteristics and included questions about their gender, age, education, professional title, personal hobbies, etc. For the second part of the questionnaire, the respondents were required to score the factors and their companies’ willingness to participate in SLCT PPPs. This was achieved using a Likert 5 scale that ranged from 1 (extremely unimportant or disagree) to 5 (extremely important or agree). Finally, open-ended questions were provided so that respondents could list other key factors. To ensure an effective response rate, a total of 160 questionnaires were distributed in accordance with Equation (1) [126].

$$n={\left[\frac{Zs}{E}\right]}^2,$$

(1)

where

• n = sample size;
• Z = Z-score (value is 1.96, which represents a 95% confidence level);
• s = the sample standard deviation (value is 4); E = error factor (value is 1)

3.3.2. Data Collection

Questionnaires were distributed on the website Wenjuanxing. To ensure the effectiveness of the data, more than 100 enterprises were chosen from the list of enterprises that had participated in PPP projects. Using on-the-spot distribution, email, and telephone consultations, questionnaires were filled out by relevant personnel from the previously selected enterprises. Between 23 April, 2019 and 22 May, 2019, 160 questionnaires were received. After eliminating invalid or incomplete responses, 105 responses were considered to be valid. The effective response rate for the questionnaire was about 65%, which met the requirement of 60% for the analysis and report writing [127] and exceeded the rate of 20%–30% for most questionnaire surveys in the construction industry [128].

3.3.3. Demographic Analysis

As shown in

Table 4. Respondents’ Industries.

Respondent’s Industries	Frequency	Percentage of Total	Cumulative Percentage
Construction business	43	40.95	40.95
Real Estate	20	19.05	60.0
Financial industry	3	2.86	62.86
Manufacturing industry	12	11.43	74.29
Formation transmission, computer service, and software industry	5	4.76	79.05
Culture, sport, and entertainment	7	6.67	85.72
Other industries	15	14.29	100.0
Total	105	100.0

, most of the respondents were engaged in the construction, real estate, and manufacturing industries. At least 40.59% of the respondents were from the construction industry, and 19.5% of the respondents were from the real estate industry. Because of their rich experiences and professional abilities in the construction industry, the survey sample fit the aims of the questionnaire.

The respondents’ working experiences are summarized in

Table 5. Respondents’ Years of Experience at Surveyed Enterprises.

Years of Experience	Frequency	Percentage of Total	Cumulative Percentage
0–5	17	16.19	16.19
6–10	51	48.57	64.76
11–15	11	10.48	75.24
>15	26	24.76	100.0
Total	105	100.0

. Most of the respondents (75.24%) had less than 15 years’ working experience and were employed in the positions of commissioner, supervisor, or manager. Respondents who were employed as directors, general managers, or presidents who had worked for more than 15 years and were the key decision makers in the strategic planning of the enterprises were the most targeted interviewees. The sample distribution in the survey indicated that the respondents’ views determined the current and future transformative directions of the enterprises.

As shown in

Table 6. Respondents’ Units.

Nature of Units	Frequency	Percentage of Total	Cumulative Percentage
State-owned listed	19	18.1	18.1
State-owned unlisted	35	33.33	51.43
Private listed	22	20.95	72.38
Private unlisted	25	23.81	96.19
Foreign listed	4	3.81	100.0
Total	105	100.0

, most of the respondents were from unlisted state-owned enterprises (33.33%), followed by unlisted private companies, listed private companies, listed state-owned companies, and listed foreign companies. Because the proportion of state-owned companies was nearly identical to the number of privately-owned companies, the survey comprehensively reflected the impact that each type of enterprise had on the willingness to participate.

According to

Table 7. Scales of Measurement, Mean, Median, and Standard Deviation for Influencing Factors and Willingness.

Influencing Factors (Scale of Measurement = 1–5).	Mean	Median	Standard Deviation
1. Government support	3.96	4.00	1.046
2. Population in the surrounding towns	4.07	4.00	0.963
3. Economic situation of sports and leisure towns	4.23	4.00	0.823
4. Traffic situation of sports and leisure towns	3.92	4.00	1.010
5. Ecological environment of sports and leisure towns	4.33	5.00	0.840
6. Market demand for the characteristic industries of towns	4.23	4.00	0.858
7. Construction complexity of towns	3.93	4.00	0.902
8. Profitability of sports and leisure town projects	4.43	5.00	0.908
9. Characteristic culture of towns	4.26	4.00	0.888
10. Macroeconomic risks of investment	3.91	4.00	0.942
11. Intermediaries’ participation in risk management	4.07	4.00	0.891
12. Leaders’ personal tendencies	3.78	4.00	1.074
13. Enterprises’ economic strength	4.29	5.00	0.906
14. Industry convergence capacity for enterprises	4.27	4.00	0.835
15. Operational capacity for enterprises	4.31	5.00	0.847
16. Enterprise’ experience of PPP project management	4.09	4.00	0.931
17. Enterprise’ experience of participating in characteristic towns	3.92	4.00	1.026
18. Enterprise concept	4.11	4.00	1.003
19. Financial institutions’ support for financing	4.08	4.00	0.927
20. Contractor’s compliance with the contract	4.12	4.00	0.968
21. Suppliers’ ability to provide long-term raw materials for projects with stable prices and quality	4.09	4.00	0.925
22. Public support	4.19	5.00	1.010
23. Media supervision	4.13	4.00	1.038
24. The participating willingness of private partners in SLCT PPPs	4.07	4.00	0.657

, the average value of the assessed factors was higher than 3.5 points, indicating that the factors identified in this study were valid. Among them, the average value for ‘project profitability’ was highest (4.43). This indicates that profitability is a key concern for private partners who consider participating in SLCT PPPs. While the lowest average value was 3.78 for the factor of ‘leader’s personal inclination’, this may indicate that the personal inclinations of leaders are not critical to decision-making processes. In addition, more than half of the enterprises expressed a willingness to participate in SLCT PPPs, suggesting that the development prospects for SLCT projects are promising. Otherwise, the reasons why some enterprises opposed involvement in SLCT PPPs could be related to the abovementioned factors.

4. Results

4.1. Factor Analysis

This study used SPSS (25.0) software to analyze the survey’s results. First, the internal consistency of the scale was assessed using Cronbach’s alpha. The value for Cronbach’s alpha coefficient (α) ranges from 0–1 and can be used to describe the reliability of factors extracted from questionnaires or scales. A high α value means high internal consistency in the scale. In the present paper, the calculated Cronbach’s α of the influencing factors was 0.936, indicating that the factors were internally consistent. To distinguish the correlation between the variables, Bartlett’s test of sphericity and the Kaiser–Meyer–Olkin (KMO) test were used to determine the applicability of factor analysis in factor extraction. As shown in

Table 8. Bartlett’s test of sphericity and the Kaiser–Meyer–Olkin test.

The Bartlett Test of Sphericity and Kaiser-Meyer-Olkin Test (KMO)
Kaiser–Meyer–Olkin test		0.886
Bartlett test of sphericity	Approximate Chi Square	1640.230
	Freedom	253
	Significance	0.000

, Bartlett’s test of sphericity was significant (P < 0.001), and the value for the KMO index was 0.886 (greater than 0.5). In summary, the results of the validity analysis ensured that the data were suitable for factor analysis [129].

Factor extraction and factor rotation were carried out. While factor extraction aims to determine factors by principal component analysis, factor rotation can make factors easier to explain [128]. According to the rule that ‘eigenvalues are greater than one’, principal components can be extracted. As such, five components were extracted from 23 factors, accounting for almost 70.545% of the total variance. Therefore, these five components were reliable for factor analysis.

The higher the factor loading, the greater the factor’s contribution to the component. Based on varimax rotation, factor loadings for these five components are shown in

Table 9. Rotated Factor Matrix—Factor Loadings for Influencing Factors.

Components	Code	Influencing Factors	Factor Loading
C1 Stakeholder factors	F17	Contractor’s compliance with the contract	0.858
	F18	Suppliers’ ability to provide materials for projects	0.847
	F19	Public support	0.710
	F20	Media supervision	0.673
	F16	Financial institutions’ support for financing	0.659
	F1	Government support	0.547
C2 Internal factors of enterprises	F14	The enterprise’ experience of participating in the construction of CTs	0.835
	F13	The enterprise’ experience of PPP projects	0.758
	F23	Industrial convergence capacity for enterprises	0.696
	F11	Operational capacity for enterprises	0.672
	F15	Enterprise concept	0.659
	F22	Leaders’ personal tendencies	0.596
	F12	Enterprises’ economic strength	0.581
C3 External environmental risk factors	F9	Macroeconomic risks of investment	0.786
	F10	Intermediaries’ participation in risk management	0.714
	F7	Profitability of SLCT projects	0.567
C4 The locational factors of towns.	F12	Economic situation of sports and leisure towns	0.786
	F8	Characteristic culture of towns	0.756
	F21	The population in the surrounding towns	0.705
C5 The supporting measures of town construction	F3	Traffic situation of sports and leisure towns	0.786
	F4	Ecological environment of towns	0.532
	F6	Construction complexity of towns	0.513
	F5	Long-term stable market demand for the characteristic industries of towns	0.461

, among which, most of the factor loadings exceeded 0.5. In general, factor loading values that are greater than 0.5 indicate that a factor can significantly interpret a component. In order to facilitate further discussion, the extracted five components were renamed and summarized as follows:

Component 1 consisted of six factors: The contractor’s compliance with the contract; the suppliers’ ability to provide materials for projects; public support; media supervision; financial support from financial institutions; and support from the government. These subjects were stakeholders who were involved throughout the entirety of the SLCT projects. Therefore, this component can be called stakeholder factors.

Component 2 consisted of seven factors: The enterprises’ experience in participating in the construction of CTs; the enterprises’ experience in PPP project management; the capacity for enterprises to industrially converge; the enterprises’ operational capacity; the enterprises’ concepts; the leaders’ personal tendencies; and the enterprises’ economic strengths. These factors were related to enterprises. Therefore, this component can be called the internal factors of enterprises.

Component 3 consisted of three factors: The macroeconomic risks of investment, such as interest rates, exchange rates, and inflation [71]; intermediaries’ participation in risk management; and SLCT project profitability. Therefore, this component can be called external environmental risk factors.

Component 4 consisted of three factors: The economic situations of towns; the characteristic cultures of towns; and the populations that surround towns. Therefore, this component can be called the locational factors of towns.

Component 5 consisted of four factors: The traffic situations of towns; the ecological environments of towns; the construction complexity of towns; and the long-term stable market demand for the characteristic industries of towns. Therefore, this component can be called the supporting measures for town construction.

4.2. Multiple Linear Regression Analysis

Following factor analysis, 23 influencing factors were divided into five components according to their degrees of correlation. However, factor analysis did not show the factors that significantly impacted private partners’ willingness to participate in SLCT PPPs. Hence, multiple linear regression analysis was conducted using SPSS (25.0) software. The multiple linear regression has seen wide use in the identification of the critical factors that affect the management of PPP projects, and it can effectively evaluate the relationship between several independent variables (i.e., factors) and a dependent variable (i.e., willingness) [97,130,131]. The general form of this study’s linear regression model was as follows:

$$\mathrm{y}={\beta }_0+{\beta }_1{X}_1+{\beta }_2{X}_2+{\beta }_3{X}_3+···+{\beta }_p{X}_p+\mathsf{\epsilon },$$

(2)

where y is the dependent variable, X₁-X_p are the independent variables, β₀ is constant, β₁-β_p are the coefficients of the corresponding independent variables, and ε is the random error.

In the regression analysis model, the five principle components identified in the factor analysis were the independent variables, which can be considered as uncorrelated [132], and private partners’ willingness to participate in SLCT PPPs was the dependent variable. To test the reliability and validity of the regression results, an enter regression technique and a stepwise regression technique were conducted to select the variables. Because the regression results were insignificant differences in the two model specification techniques, this paper adopted the enter technique. The regression results are summarized in

Table 10. Multiple Linear Regression Results.

Model	R	R2	Adjusted R2	Errors in Standard Estimation	R2 Variation	F Value	Freedom 1	Freedom 2	Significance
1	0.907	0.823	0.814	0.285	0.823	92.195	5	99	0.000

. As indicated, the model was significant at a level of p < 0.001. In addition, the R² value was 0.823, indicating that the extent to which the five components affected private partners’ willingness to participate in SLCT PPPs was 82.3%.

As illustrated in

Table 11. Beta Coefficient for the Five Components.

Model		Beta	t	Significance
1	(constants)		69.240	0.000
	Stakeholder Factors	0.567	13.411	0.000
	Internal Factors of Enterprises	0.430	10.168	0.000
	External Environmental Risk Factors	0.364	8.625	0.000
	The Supporting Measures of Town Construction	0.337	7.967	0.000
	The Locational Factors of Towns	0.267	6.315	0.000

, according to the value of the beta coefficient, the greatest to least significant factors that affected private partners’ willingness to participate were stakeholder factors, the internal factors of enterprises, the external environmental risk factors, the supporting measures of town construction, and the locational factors of towns. The correlations between these factors are shown in Figure 3. These results warrant further discussion.

5. Discussions

The SLCT PPPs in the Shandong and Zhejiang Provinces, which are characterized by a significant demand for sports and leisure, abundant resources, and advanced technologies, were analyzed to demonstrate the effectiveness of this paper’s conclusion.

5.1. Stakeholder Factors

The stakeholder component with the highest beta coefficient (0.567) is the most significant factor. This is in line with Wojewnik–Filipkowska’s [90] study, which indicated that stakeholders determined and were conditional to the success of sustainable PPPs. Shao et al.’s [17] two-dimensional stakeholder matrix also verified that government and private partners are key stakeholders, financial institutions are the main stakeholders, project contractors and suppliers are the secondary stakeholders, and the public and the media are general stakeholders in SLCT PPP projects. Because more stakeholders are involved in PPP projects than in other types of projects [82,133], good relationships between the stakeholders are essential to the success of PPP projects [107,134].

Government and public support: The factor loading for ‘government support’ was lower than the factor loading for the stakeholder component. This could be because the poor governance capacities of SLCT PPPs are exoteric and include insufficient local government revenue and inadequate government credit and fulfilling capability [79]. Nevertheless, political connections and a combination of subsidy and tax cuts have still managed to attract private partners’ participation in SLCTs [89,96,97] such as the Hot Springs Tianheng Sports and Leisure Town, Xujiaya Airplane Town, and Tonglu Football Town. This finding also indicates the significant role that public support plays in attracting the participation of private partners, which is in accord with other studies [102,103,104]. Nonetheless, Boyer et al. [121] and Ye [97] asserted that public involvement only increases the costs of PPPs and has little effect on expediting project delivery. One explanation for this divergence in opinions could be due to the aims of SLCT projects to meet the demands of health, leisure, employment, and economic sustainability. In other words, the public pays more attention to SLCTs than other projects (e.g., transportation). This paper’s findings confirm Boyer’s opinion [121] and complement effectiveness concerning the public and its influence on SLCT projects. Thus, the government and public support are necessary but insufficient conditions for encouraging private partners to participate in SLCT PPPs.

The following results comply with the findings of other studies. Gaining the support of financial institutions is considered to be an effective method for guaranteeing considerable funds for private partners who take part in PPPs [135]. Nevertheless, banks’ approval standards for PPP projects are high, and they often offer no support for PPPs if local government revenue is less than $285.56 million. In addition, private partners have little confidence in the construction risk guarantees for CT projects [17,71,136], which rely closely on the behaviors of contractors and suppliers [128]. Thus, contractors’ and suppliers’ reputations and strengths significantly influence private partners’ willingness to participate in SLCT projects. In other words, stakeholder factors are key to private partners’ involvement in SLCT projects.

5.2. Internal Factors of Enterprises

Private partners are key stakeholders in SLCT PPP projects [17,86]. The present study’s findings show that the internal factors of enterprises are critical to encouraging the participation of private partners in SLCT PPP projects. These internal factors include the experiences of an enterprise, an enterprise’s concepts and abilities in investment, and capacities of an enterprise’s constructions and operations, etc. These factors are also evaluated by governments when they select private partners [119].

Experience of an enterprise: An enterprises’ considerable experience in CT PPP projects can improve an enterprises’ willingness to participate in them, as experience helps enterprises to better share interests and risks. Ye (2018) arrived at a similar conclusion, asserting that experience can allow partners to respond to complexities or uncertainties and improve their routines during the processes of construction [97].

An enterprises’ economic strengths, industrial integration, and operational abilities: Economic strength, industrial integration, and operational ability significantly impact private partners’ willingness to participate in SLCT PPP projects, as each of these influence CTs during the operational stage. In addition, economic strength functions as a fundamental guarantee for the start-up, construction and operation of PPPs [103,137] due to the higher investment requirements for CT projects [73]. This study’s results complement research that has evaluated the effectiveness of industrial integration in ensuring a project’s sustainable development [137]. Because the sustainable development of SLCTs relies on the sports and leisure industry, the capacity of enterprises for related industries to integrate serves as a valuable tool for attracting the participation of private partners.

Enterprises’ concepts and the tendencies of leaders: Enterprise concepts and leaders’ personal tendencies significantly impact private partners’ willingness to participate during the feasibility stage, and each reside within the scope of an enterprise’s soft power [79,138,139]. It also suggest that the non-power influence of leaders is essential to the management of enterprises, an argument that has been confirmed in discussions by Liu [123] and from the interviews in this paper. In summary, the internal factors of enterprises significantly influence the participation of private partners in SLCTs.

5.3. External Environmental Risk Factors

The results showed that various external environmental risk factors, such as macroeconomic and project profitability risks, can hinder an enterprise’s willingness to participate in SLCT PPPs. This is not surprising. Among all the indexes listed in Table 7, the mean value for ‘project profitability’ was the highest (4.43), demonstrating that profit was a major concern. This finding corresponds with conclusions that have been drawn in other PPP studies [97,135]. In essence, profit is a fundamental goal in an enterprise’s willingness to participate in PPPs [93]. One explanation for the lower factor loading value than risk index for Component 3 could be that profit is not only comprised of economic but also public considerations [25]. Public interest can make up for economic interest by the ‘value capturing’ mechanism in SLCT projects [25]. Therefore, when compared to macroeconomic risks, the profit risks are insubstantial among external environmental risk factors. As an example of the imperfect profit model of SLCTs, Laiyin Sports, a firm from China that invested $2876.58 million in four SLCTs in 2017, jeopardized their sustainable operations due to difficulties with cash-flow caused by uncertainties over their sources of repayment and the lengthy period of return on their investments (about 5–7 years) [140].

Interest rates, exchange rate, and inflation are macroeconomic risks of investment [17] that can occasionally be influenced by macroeconomic policies and economic cycles. It is therefore vital for enterprises to identify and avoid these unique risks. The risk management precautions that intermediary agencies conduct throughout this entire process of investing in SLCTs are consistent with private partners’ willingness to ensure effective risk sharing between several stakeholders during the construction of CTs. As such, it is important for private partners to consider external environmental risk factors.

5.4. Supporting Measures of Town Construction

While traffic accessibility, ecological environment, and the market demands of a characteristic industry have a positive correlation with private partners’ willingness to participate in SLCT PPPs, the complexities of construction have a negative impact.

Traffic accessibility: Similar discussions within this paper about traffic accessibility have appeared in highway tolling PPPs in the U.S. [141], wherein the advantages of reducing transportation costs and attracting large numbers of tourists were identified [118]. Convenient transportation will eventually benefit a firm’s profits and strengthen its willingness to participate in SLCT PPPs. Traffic accessibility can also sufficiently drive regional development in China [142].

Ecological environment: In recent years, the concept of environmental conservation has been highlighted in developing countries [143]. Studies about Green PPPs in China have been refined by researchers and enterprises around the world [73]. In SLCT PPPs, a firms’ public interests are built upon ecological sustainability. The traffic and the ecological environment have also played a role in influencing the complexity of construction [71].

Market demand: During the interviews with the five general managers from the state-owned enterprises that participated in CT PPPs, we found that the green industry, transportation infrastructure, and projects with long-term stable market values were consistent with their investment criteria. In reality, the sustained development of SLCTs depends on market demand in the sports and leisure industry. Therefore, private partners’ willingness to participate in these town projects may be influenced by future market demand.

Construction complexity: Construction projects can become complex due to planning, engineering techniques, and engineering quality, etc. [17,97,144], in SLCT projects. These factors affect construction costs, which are centrally considered by private partners [128]. In addition, due to the complexity of construction, private partners are required to have relevant and necessary experience.

5.5. Locational Factors of Town

The cultures, economic situations, and populations of SLCTs are essential to their construction and influence an enterprises’ willingness to participate in their development.

Characteristic culture: Cultural logos are the mark of a CT’s construction and operation. SLCTs with distinct cultural characteristics or characteristic industries can attract the participation or interest of private partners. Through the integration of traditional sports cultures, we can enhance competitiveness in the development of these towns [145].

Economic situation: The economic situation of SLCTs are valued by private partners and banks that invest in PPPs, as the local government’s fiscal position determines its ability to offer support and repay investors. As an example, if a project were located in the county area of Shandong Province, the local government would need more than $100 million to supply general budget revenue, and it would need to increase its GDP to more than $1438.29 million [146]. While local governments with lower revenues may hinder a firm’s investments, governments may always choose to initiate more PPPs, which could undermine the sustainability of PPPs. Unlike other studies, this analysis exhibits the true dilemma of SLCT PPPs in China.

Population: The present study’s results show that the populations that surround towns significantly influence firms’ willingness to participate in SLCT projects; a finding that verified the experts’ opinions concerning citizens’ contributions to successful projects [122]. The surrounding population is important because the residents are beneficiaries and builders of CTs. Although labor and project managers are critical to the construction of SLCTs, these individuals, particularly project managers, cannot always be found. Thus, towns that are characterized by human resources can reduce construction costs and increase private partners’ willingness to participate in these projects.

6. Conclusions

The sustainability of new urbanization in China requires the vigorous development of CTs. As a desired financing method, the PPP model can be applied to SLCT projects to achieve win-win results between the government and private partners. Therefore, this paper investigated the factors that influence private partners’ willingness to participate in SLCT PPPs by conducting an empirical analysis of SLCT PPPs in China. The results indicated that the most critically influential factors were stakeholder factors, while the locational factors of towns were the least impactful. For enterprises, profitability relies on both economic and public interests, and these factors are considered by enterprises that participate in SLCT PPPs.

Several countermeasures and suggestions should be put in place to enhance private partners’ willingness to participate in SLCT PPPs. Firstly, the government should improve construction mechanisms, such as compatible incentive mechanisms, SLCT market value realization mechanisms, cost compensation mechanisms, and price charging systems to ensure that trustworthy enterprises see a reasonable return on their investments. To help enterprises cope with external environmental risks, the government should also encourage the public to take part in sports and leisure activities and introduce intermediary agencies to manage risks during the entire process. Secondly, a joint office innovation mechanism should be performed between the government and private partners. Private partners should also be involved in governmental industrial planning, spatial planning, and investment planning at an early stage. By doing so, enterprises can have a better understanding of the government’s challenges, weaknesses, and regional economic development by the time they reach the implementation phase. Thirdly, management ability, industrial convergence, and operational capability should be strengthened for private partners by controlling costs, cultivating interdisciplinary talents (e.g., PPP, project management, industry, etc.), and mastering advanced technologies and experiences. In addition, financial institutions should broaden their approval restrictions for SLCT PPPs. Contractors and suppliers should also honor their agreements with private partners to improve their credibility. Finally, the government should explore and develop characteristic cultural resources and protect the local ecological environment. These will help them to attract and retain talents for the development of CTs.

This study’s conclusion should serve as a practical and significant reference tool for government decision makers and industry practitioners across developed and developing countries. For the government specifically, understanding the concerns and difficulties of enterprises will benefit its ability to create precise and supportive policies. For industry practitioners, this work will prove valuable in reducing participation barriers and provide them with practical suggestions for contributing to CT PPPs. Due to the limited regional data resources in China, future works may explore additional topics and conduct empirical analyses in other countries to enrich the scope of this research. By comparing varying countries and using the multi-attribute decision-making model to assess the real decision-making behaviors of private partners, subsequent research could produce more valuable results.