Yachting Tourism Consumption Potential and Its Influencing Factors: Considering 12 Coastal Cities in China as Examples

Abstract

Releasing the consumption potential of yachting tourism is important for marine economic development. The purpose of the study is to evaluate a comprehensive potential index for yachting tourism (based on consumption capacity, expenditure, quality, and environment) in 12 cities in China with high development potential for coastal yachting tourism. Data from 2014, 2017, and 2019 were included in the study. Analytic Hierarchy Process (AHP), entropy methods, and gray correlation analysis are applied in the study. A panel data regression model is used to estimate the factors affecting the consumption potential of yachting tourism. The results show that the consumption potential index of yachting tourism in China’s coastal cities has been continuously increasing, and the consumption potential is closely related to consumption quality and capacity. The consumption potential of yachting tourism is highest in Shanghai, Shenzhen, and Guangzhou. The overall spatial pattern shows a gradual decrease in consumption potential in the Pan-Pearl River Delta region to the Yangtze River Delta region and the Bohai rim region.

1. Introduction

Yachting tourism is a new form of tourism that integrates sports, sailing, entertainment, leisure, and socialization and involves yacht cruising, sailing, rowing, kayaking, motorboating, fishing boats, and other ocean-friendly activities [1]. As a product of the integration of the yachting and tourism industries, the economic, sociocultural, and environmental impacts of yachting tourism, consumer motivation and market segmentation of yachting tourists, and the management and collaborative governance of local governments are topics of interest for international scholars [2,3,4,5]. Scholars generally agree that yachting tourism development has a positive impact on economic development, as it ensures the differentiation of tourism products and promotes the development of tourism enterprises [6,7,8].

North America and Europe currently dominate yachting tourism worldwide. 15.75 million yachts have been reported in the U.S. (~33% of the world total); in Europe, ~4.76 million yachts and a total of 10,197 marinas [9]. With the rapid development of the Chinese economy and the expansion of the middle class, China has entered the stage of rapid development of yachting tourism. As of 2020, mainland China has 114 marinas, 12,000 water berths, 2000 dry storage facilities, and 2600 yachting-related enterprises [10]. However, the consumption potential of yachting tourism in China still has room to grow, mainly due to the low per capita yacht ownership ratio and the underdevelopment of yacht infrastructure. For instance, the number of marinas and water berths in China is only 9/1000 in the United States and 1/100 in Europe, and there is only one public yachting marina in Haikou, making it difficult to popularize yachting tourism consumption.

The “Outline of the 14th Five-Year Plan (2021–2025) for National Economic and Social Development and Vision 2035 of the People’s Republic of China” proposed improving the yachting development policy. The “14th Five-Year Tourism Development Plan” also proposed promoting the mass development of yachting consumption and supporting the development of an innovative yachting industry in coastal cities such as Dalian, Qingdao, Weihai, Zhuhai, Xiamen, and Sanya. Under the guidance of the central government, local governments strongly support yachting tourism development, the active construction of several yachting berths, and the formation of yachting tourism routes and networks. In this study, 12 Chinese coastal cities are selected to illustrate developments in China’s yachting tourism.

Current research on yachting tourism consumption focuses on yachting tourism consumption behavior and its influencing factors [11,12,13], consumer market segmentation [5,8,14], and barriers to marketing promotion [2,15,16]. The research on tourism potential mainly focuses on the evaluation of tourism industry potential and tourism development potential [17,18]. By establishing the evaluation index system, the measurement and evaluation of tourism development potential are carried out, and the countermeasures are put forward. Tourism consumption potential is the unrealized consumption demand, which is the potential energy that can finally be transformed into actual tourism consumption expenditure through the satisfaction of certain factors and conditions [19]. The consumption potential of yachting tourism comprehensively reflects tourists’ consumption demand and willingness to sail, but there is still a lack of empirical research to evaluate it [20,21,22]. Effectively identifying the influencing factors and avoiding the adverse factors is of great significance for releasing the consumption potential of yachting tourism in China.

Therefore, the main objective of this study is to develop a comprehensive evaluation system consisting of consumption capacity, expenditure, quality, and environment to evaluate the consumption potential of yachting tourism and also to reveal the spatial and temporal differences and influencing factors of yachting tourism consumption potential of major coastal cities in China. This research is not only helpful in unleashing the consumption potential of China’s yachting tourism and meeting the demand for high-quality tourism but also expands the research on yachting tourism consumption and provides a reference for developing countries in the world. The organizational structure of this study is thus: Section 2 presents the literature review; Section 3 describes the study area, methods, and data sources; Section 4 describes the results of yachting tourism consumption potential and its influencing factors; and Section 5 is the conclusion, the theoretical and practical implications, future research prospects of the paper are proposed.

2. Literature Review

2.1. Yachting Tourism

The International Maritime Organization does not include yachts in the compulsory management objective of the International Maritime Convention, and all member states define and manage their yachts. Yachts mainly refer to boats or watercrafts used for sightseeing, recreation, and water sports, such as inboard and outboard motor boats, fishing boats, catamarans, sailing boats, hovercrafts, jet boats, and kayaks [23,24,25].

The research on yachting tourism in China has explored three relevant niche aspects. The first is the study of consumer groups and their characteristics [5,20]. The second is consumption intention and its influencing factors [26]. The third is restrictive factors of yachting tourism consumption [23]. Previous studies in this field have not used a system of evaluation indices measuring the consumption potential of yachting tourism. Additionally, the spatial-temporal differentiation and characteristics of the consumption potential of yachting tourism have rarely been analyzed. Research methods applied in domestic yachting tourism studies are mainly qualitative and rarely involve mathematical modeling analysis based on survey data or statistical data.

There are mainly two types of consumption needs for yachting tourism in China: the needs of the public for leisure and entertainment and the luxury enjoyment of the elite class [22]. The main market for yachting tourism consumption is the high net worth group and the middle class, and there are various types of yachting tourism consumption, such as private yacht, yacht leasing, and yachting experience [26]. Studies outline that to harness the potential of yachting tourism consumption in China; it is imperative to optimize the product supply, improve policies and regulations related to the yacht industry, innovate yacht club business operations, empower the role of industry associations, and expand the domestic and foreign yachting markets [25,27,28,29,30]. In addition, the consumption of residents coexists with that of tourists [5]. Thus, in the evaluation of yachting tourism consumption potential, the consumption capacity and expenditure structure of residents should be considered, together with the consumption level and environmental support of tourists.

2.2. Consumption Potential and Its Influencing Factors

There are two main ways of understanding this “potential” in academia: “gap theory” and “support and guarantee theory”. The former emphasizes that potential is the gap between the ideal level of resources available at the optimal allocation and the current actual level, while the latter emphasizes that potential is the sum of existing resource elements that can guarantee future development and is a comprehensive evaluation of the support and guarantee role of existing elements [19].

Tourism consumption potential is the potential energy that can eventually be transformed into actual tourism consumption expenditure by satisfying certain factors and conditions. Based on the perspective of the “gap theory” between the ideal level of consumption and the current actual level, Feng calculated the development potential index of off-season tourism to provide a basis for decision-making for off-season tourism market development [31]. Song predicted the recovery potential of the domestic tourism market during the pandemic [32].

Moreover, tourism consumption potential is not only the gap but also the sum of existing resource elements that can guarantee future development. It is a comprehensive evaluation of existing elements that have a supporting and guaranteeing function [19]. In other words, yachting tourism consumption potential is a comprehensive reflection of people’s apparent consumption ability and potential consumption willingness and is greatly affected by the supply quality of the yachting tourism market and the consumption environment. Therefore, from the perspective of the “support and guarantee theory” of potential, the consumption potential of yachting tourism can be viewed as an integrated system consisting of consumption capacity, expenditure, quality, and environment [33,34]. Consumption capacity is the basis for the realization of consumption potential [17,19,34], and consumption expenditure is a direct expression of the consumption potential of yachting tourism [17,22]. Consumption quality reflects the sustainability of yachting activities [18,29,33], and the consumption environment is an important condition for yachting consumption [18,28,33].

Many factors influence the consumption potential of yachting tourism, including both the economic and social development environments and the consumption intentions of tourists. According to the traditional consumption function theory, along the main line of the income-consumption relationship, the analysis of internal and external factors impacting the consumption potential of yachting tourism mainly includes the level of residents’ income, living cost, household fixed assets, demographic structure, and the level of social security and economic urbanization [26]. First, increasing the income of residents is the basis for expanding consumption, which is a prerequisite for turning consumption desires into consumption reality, and the income level of residents represents their purchasing power for yachting tourism consumption [35]. Second, housing prices have a role in the consumption potential of yachting tourism using two channels [36,37,38]. On the one hand, the increase in housing prices brings about an increase in household wealth, which affects the adjustment of residents’ consumption structure and has a “wealth effect” [39,40]. On the other hand, as housing costs increase, residents may choose to reduce leisure consumption, creating a “crowding out effect” [37,41,42]. Third, the change in family burden caused by the adjustment of the population age structure will have a significant impact on the consumption potential of yachting tourism. Some scholars highlight that the child dependency ratio has a significant negative correlation with leisure consumption, whereas the elderly dependency ratio has a positive correlation with leisure consumption [43,44]. Due to differences in sample selection and research methods, researchers have not reached a consensus on the results, and the need to systematically study the factors affecting the consumption potential of yachting tourism is still relevant.

3. Methods

3.1. Evaluation Index System Construction

To develop the yachting tourism consumption potential evaluation system, 31 indicators were selected from these four dimensions (consumption capacity, expenditure, quality, and environment) based on the principles of comparability, availability, and objectivity of evaluation indicators (see

Table 1. Evaluation index system and weight of yachting tourism consumption potential.

Level 1 Index	Level 2 Index	Level 3 Index	Description of Specific Indicators (Unit)
Yachting tourism consumption potential	Consumption capacity [17,19,22,34]	Income level	Wage income (yuan/person)
			Net business income (yuan/person)
			Net property income (yuan/person)
			Net transfer income (yuan/person)
		Knowledge level	Education expenses (million yuan)
			Number of college students
	Consumption expenditure [17,22,28,29,34]	Expenditure Level	Per capita tourism spending (yuan)
			Total number of tourists (10,000 person times)
			Average dwell time
		Expenditure Structure	Tourism consumption rate (%)
			Education, culture, and entertainment consumption expenditure (yuan/person)
			Household Engel Coefficient (%)
	Consumption quality [18,22,28,29,33]	Infrastructure	Number of yachts
			Number of yacht marinas
			Number of yacht berths
			Number of yacht clubs
		Resource Endowment	Number of tourist attractions above the national level A
			Coastline length (km)
			Sea area (km2)
			Number of islands
			Marine nature reserve area (hm2)
			Marine water quality (%)
			Air quality index (AQI) compliance days
	Consumption environment [18,22,28,29,33]	Social Environment	GDP per capita (yuan)
			Share of tertiary sector in GDP (%)
			Year-on-year growth rate of savings deposits (%)
		Tourism Environment	Tourism revenue (billion yuan)
			Number of star hotels
			Number of travel agencies
		Industrial Environment	Yacht management policy
			Yacht industry supporting
			Yachting culture

).

First, yachting tourism consumption capacity is the ability of residents to pay for yachting tourism products or services, which directly determines whether residents’ yachting consumption demand can be realized, mainly through an increase in personal disposable income and improvement in knowledge level as the basis and guarantee. The level of payment is reflected in the actual income level of urban residents, which includes four aspects: wage income, business income, property income, and transfer income. Additionally, whether it is private yachting, yachting charter, or experience, consumers must have a certain level of knowledge and skills [13], which can be measured using the local educational expenditure and the number of college students [36].

Second, the consumption expenditure of yachting tourism reflects the apparent demand for yachting tourism, which is the direct embodiment of consumption potential. As it is difficult to obtain the specific type and structure of consumption expenditure within yachting tourism, and coastal tourists are an important source of yachting tourism, the consumption expenditure index of tourism in coastal cities was used instead [33]. In total, three indicators were selected to reflect the level of yachting tourism consumption expenditure: per capita tourism spending, the total number of tourists, and the average number of days tourists stay. Furthermore, three indicators were chosen to measure the expenditure structure, namely tourism consumption rate, education, culture, and entertainment consumption expenditure, and the Household Engel coefficient. Among them, the tourism consumption rate refers to the proportion of tourism consumption expenditure of tourists in the total personal consumption expenditure, reflecting the intensity and level of tourists’ tourism consumption. The consumption expenditure of education, culture, entertainment, and the Household Engel coefficient can reflect the proportion of leisure tourism consumption in urban residents’ consumption and the consumption potential of yachting tourism.

Third, the quality of yachting tourism consumption is the comfort and convenience that tourists obtain from yachting tourism and its spiritual and psychological enjoyment. This notion essentially maps the durability of yachting tourism consumption and can be reflected by the abundance of tourism resource endowment and the soundness level of infrastructure in yachting tourism destinations [33], which, to a certain extent, determines the yachting tourism consumption potential. The number of yachts, marinas, water berths, and yacht clubs reflects the completeness of infrastructure construction. The length of coastline, sea area, number of islands, area of marine nature reserves, seawater quality, number of Air Quality Index (AQI) compliance days, and abundance of coastal tourism resources (the number of scenic spots above level A) can be employed as the main indicators to measure the endowment of yachting tourism resources [45].

Fourth, the yachting tourism consumption environment is the macro socioeconomic background and industrial development conditions experienced by consumers, which largely influences the yachting tourism consumption potential [34], including three aspects: the social environment, tourism environment, and industrial environment. The social environment mainly consists of gross domestic product (GDP) per capita, the share of tertiary industry in GDP, and the year-on-year growth rate of savings deposits. The GDP per capita and savings deposit growth rate reflect the regional economic development environment from macro and micro perspectives, respectively. The tourism development environment mainly includes total tourism revenue, the number of star-rated hotels, and travel agencies. The yacht industry’s environment reflects the ability of the yacht policy, industrial support, and yachting culture to support regional yachting tourism consumption.

3.2. Study Area

The development of China’s yachting tourism has obvious pro-sea attributes; Dalian, Tianjin, Qingdao, Weihai, Ningbo, Zhoushan, Shanghai, Xiamen, Guangzhou, Shenzhen, Haikou, and Sanya cities have the strongest development of yachting tourism in China. They are the basic embodiment of the scale of China’s yacht industry and lead to the future development of this niche market [9]. In 2019, these cities received 1.384 billion tourists from home and abroad, accounting for 23.05 percent of the national total. There were 6681 travel agencies, accounting for 17.16 percent of the country’s total, and 3564 power boats, accounting for 82.3 percent of the total on the Chinese mainland. Given that these 12 coastal cities have started to develop yachting tourism in a targeted manner, this area is chosen to describe the current developments of yachting tourism in China.

3.3. Data Source

Given that the development of yachting tourism in China is still in the primary stage, the statistical caliber of the yachting industry reports in previous years is not consistent, and it is difficult to form complete time series data. This study relies on the 2014/2017/2019 China Yacht Industry Development Report, and the cross-sectional data of 2014, 2017, and 2019 were obtained for research. The data of indicators in the consumption capacity, expenditure, and environment of yachting tourism are mainly obtained from the statistical bulletin of the national economic and social development of each city, China City Statistical Yearbook, China Tourism Statistical Yearbook, and tourism sample survey information. The data relating to resource endowment in consumption quality are mainly obtained from the annual marine functional zoning and marine environment status bulletin of each city. The number of yachts, marinas, berths, and expert scoring data of yacht policy support and industrial development comes from the China Yacht Industry Development Report each year, and the number of yachting clubs is obtained from the corporate database (https://www.qcc.com/ (accessed on 22 July 2022)). The data of the indicators are pre-processed through elimination, checking, and corroboration, and the missing data are mainly assigned by the weighted average method to fill in the gaps.

3.4. Research Method

Evaluating the consumption potential of yachting tourism is a multifaceted problem involving several indices. Currently, the necessary scientific tools and theoretical foundations for this mainly come from analytic hierarchy process and entropy methods [19,22], cluster analysis [18], gray correlation degree analysis [33], regression model [34], etc. To increase the credibility and objectivity of the findings, the AHP-entropy method is used to comprehensively weigh the evaluation indicators of the consumption potential of yachting tourism. Gray correlation analysis is used to study the relationship between the yachting tourism consumption potential system and each subsystem and the evaluation index. A panel regression model is used to investigate the factors affecting the consumption potential of yachting tourism in China.

3.4.1. AHP-Entropy Method

The index is weighted using combining the analytic hierarchy process (AHP) and entropy methods. The AHP method decomposes the relevant elements of the decision problem into levels of objectives, rules, and plans and quantifies the subjective judgment of each expert on a certain scale (1–9 scale method) to make it objective. Three experts in the field of industrial economy and tourism management and five researchers in the field of tourism economy and tourism management were invited to the expert panel to compare the significance of the factors. All involved professionals are familiar with the current consumption situation of Chinese yachting tourism. After the judgment matrix is formed, the maximum value of the characteristic roots and the corresponding characteristic values are calculated, and the individual ranking weights of a layer relative to the elements of the previous layer are calculated, as well as the total ranking of the layer after the weighted synthesis. The weight of a layer is calculated relative to the previous layer and the total ranking weight of the layer after the weighted synthesis.

Then, the entropy method was used to determine the weights objectively, and the difference rate of the indicators was used to determine the weights to avoid the interference of human factors. The entropy method was calculated using the following steps.

① A linear dimensionless threshold is used to process the original data. It is necessary to add one after dimensionless processing to make the logarithm meaningful when calculating the information entropy using Equation (1):

$$x_{\prime }^{ij}=\frac{x_{ij}-x_{\min }}{x_{\max }-x_{\min }}+1i=1,2,\dots ,n; j=1,2,\dots ,m$$

(1)

where $x_{ij}$ is the value of $j$ for each city under the indicator $i$. $x_{\max }$ and $x_{\min }$ are the maximum and minimum values for each city under $i$, respectively, and $x_{\prime }^{ij}$ is a dimensionless non-negative value of $x_{ij}$.

② Calculate the $i$ indicator of city $j$ share of the sum of this indicator for all cities $p(x_{ij})$ based on Equation (2):

$$p_{ij}=\frac{x_{\prime }^{ij}}{{\displaystyle \sum _{j=1}^m{x}_{\prime }^{ij}}} i=1,2,\dots ,n; j=1,2,\dots ,m$$

(2)

③ The entropy value of the $i$ indicator is calculated as per Equation (3):

$$e_i=-k{\displaystyle \sum _{j=1}^m{p}_{ij}}ln{p}_{ij}$$

(3)

where $e_i$ > 0 and $k$ > 0. If $x_{\prime }^{ij}$ is fully equal for a given $i$, then $p_{ij}=\frac{x_{\prime }^{ij}}{{\displaystyle \sum _{j=1}^m{x}_{\prime }^{ij}}}=\frac{1}{m}$, and $e_i$ takes a great value. Let $k=\frac{1}{lnm}$ be normalized to $e_i$, then $0\le e_i\le 1$.

④ Calculate the coefficient of variation of the $i$ indicator and define the coefficient of variation $g_i$, $g_i=1-e_i$, and $g_i$; the larger the indicator, the more important it is.

⑤ The differentiation coefficients of the entropy value method $g_i$ were used to adjust the weights derived from the analytic hierarchy process (AHP) method, that is $w_i=\frac{w{g}_i}{{\displaystyle \sum _{i=1}^{n}w{g}_i}}$, where $0\le w_i\le 1$ and ${\displaystyle \sum _{i=1}^n{w}_i}=1$, to obtain a more scientific and reasonable revised composite weight. The overall weight changes each year due to changes in objective data.

⑥ The linear weighting method is employed to measure the yachting tourism consumption potential index for each city. The index is then expanded for the convenience of studying the differences between indices using Equation (4):

$$F=100\times {{\displaystyle \sum }}_{i=1}^{ n}{w}_i{z}_i i=1,2,\dots ,n$$

(4)

where F is the yachting tourism consumption potential index; $i$ indicates the order of indicators in the system; $w_i$ is the corrected total weight value of the indicator; and $z_i$ is the dimensionless value of the $i$ indicator for the city.

3.4.2. Gray Correlation Analysis

The consumption potential system of yachting tourism is a complex system in which each subsystem is closely related to the evaluation index. Based on the gray system theory, gray correlation analysis was employed to study the correlation between the yachting tourism consumption potential system and each subsystem and evaluation index. The principle is that by analyzing the difference in each factor of the system, the magnitude of the influence of each factor on the whole system is derived (i.e., the degree of influence decreases with an increase in the variability of each factor). The calculation steps of the method are as follows.

① Determine the comparison object (object of evaluation, e.g., subsystems of consumption potential) and the reference series (evaluation criteria, e.g., comprehensive index of consumption potential). Suppose there are m evaluation objects and n evaluation indicators; the reference series is $x_0=\left\{x_0(k)\left|k=1,2,\dots ,n\right.\right\}$, and the comparison series is $x_i=\left\{x_i(k)\left|k=1,2,\dots ,n\right.\right\},i=1,2,\dots ,m$.

② The weights corresponding to each index value are determined. The AHP-entropy value method is utilized to determine the weights corresponding to each index $w=\left[w_1,w_2,\dots ,w_n\right]$, where $w_k$ and $k=1,2,\dots ,n$ are the weights corresponding to the kth evaluation index. See Step 5 of Section 3.4.1 for the specific algorithm.

③ Calculate the grey correlation coefficient according to Equation (5):

$${\xi }_i(k)=\frac{\underset{s}{min} \underset{t}{min}\left|x_0(t)-x_s(t)\right|+\rho \underset{s}{max} \underset{t}{max}\left|x_0(t)-x_s(t)\right|}{\left|x_0(k)-x_i(k)\right|+\rho \underset{s}{max} \underset{t}{max}\left|x_0(t)-x_s(t)\right|}$$

(5)

Which is the correlation coefficient of the comparison series $x_i$ with the reference series $x_0$ on the $k$ index, where $\rho \in \left[0,1\right]$ is the resolution coefficient, and the value is 0.5. In the Equation, $\underset{s}{min} \underset{t}{min}\left|x_0(t)-x_s(t)\right|$ and $\underset{s}{max} \underset{t}{max}\left|x_0(t)-x_s(t)\right|$ are the minimum and maximum differences between the two levels, respectively. In general, the resolution is positively correlated with the resolution factor $\rho$.

④ Calculate the gray-weighted correlation degree as per Equation (6):

$$r_i={\displaystyle \sum _{k=1}^n{w}_k{\xi }_i(k)}$$

(6)

As a result of the calculation, the degree of correlation between the yachting tourism consumption potential system and each subsystem, as well as the evaluation index, is obtained. Where $r_i$ is the gray-weighted correlation of the ith evaluation object to the ideal object; the larger the correlation, the better the evaluation result.

3.4.3. Panel Data Regression Model

According to the research objectives of this study and the discussion of the influencing factors mentioned in Section 2.2, the following model was constructed to explore the factors influencing the consumption potential of yachting tourism in China:

$$\begin{gathered} LnYC{P}_{it}={\beta }_0+{\beta }_{1}LnH{P}_{it}+{\beta }_{2}LnFA{I}_{it}+{\beta }_{3}LnPD{I}_{it}+{\beta }_{4}LnOD{R}_{it}+ \\ {\beta }_{5}LnCD{R}_{it}+{\beta }_{6}LnBP{I}_{it}+{\beta }_{7}LnCP{I}_{it}+{\epsilon }_{it } \end{gathered}$$

(7)

where LnYCP_it denotes the composite index of yachting tourism consumption potential in the year $t$ of the region $i$; ${\beta }_0$ denotes the constant term; ${\beta }_1~{\beta }_7$ denotes the regression coefficients of the influencing factors 1–7, respectively; and ${\epsilon }_{it}$ denotes the random error term. The average selling price of commodity houses (LnHP), total social fixed asset investment (LnFAI), per capita disposable income (LnPDI), the old-age dependency ratio (LnODR), child dependency ratio (LnCDR), number of people participating in basic pension insurance (LnBPI), and consumer price index of residents (LnCPI) were selected as explanatory variables.

4. Results and Discussion

4.1. The Grey Correlation Degree of Consumption Potential System Index

There is a correlation between the yachting tourism consumption potential system and subsystems and evaluation indicators, as illustrated in

Table 2. Gray correlation between the composite index of yachting tourism consumption potential and each subsystem.

Subsystems	Correlation Degree	Ranking
Consumption capacity	0.890	2
Consumption expenditure	0.829	3
Consumption quality	0.896	1
Consumption environment	0.813	4

. First, according to Equation (6), the yachting tourism consumption potential has the largest correlation with the consumption quality subsystem, which is approximately 0.896, signifying that the size of the yachting tourism consumption potential is directly related to the consumption quality, and the marine resource conditions of yachting tourism and infrastructure construction, such as yacht marinas and clubs, directly determine the yachting tourism consumption potential level. Second, the correlation between yachting tourism consumption potential and the consumption capacity subsystem is 0.890. Notably, the increase in tourists’ disposable income and the enrichment of knowledge and skills, together with the rising willingness of tourists to participate in yachting activities, continuously facilitates yachting tourism consumption. Third, the correlation between yachting tourism consumption potential and consumption expenditure was 0.829, and the correlation with the consumption environment was 0.813, outlining that there is still significant room for improvement in the development environment of yachting tourism in coastal cities.

Further, the gray correlation analysis of the yachting tourism consumption potential system with 31 specific indicators reveals that the correlation with each indicator is distributed between 0.840 and 0.906, where the top three factors are the level of wage income, net property income, and per capita tourism consumption, relaying that an increase in income level and tourism consumption expenditure can help promote tourism consumption. The next two influencing factors are the number of yachting clubs and the abundance of marine tourism resources, which suggests that the consumption potential of yachting tourism is closely related to the perfection of its infrastructure and tourism resource endowments. The more sound the yachting facilities and the richer the marine resources, the greater the consumption potential of yachting tourism. Overall, China’s coastal yachting tourism consumption potential is more closely linked to consumption quality and consumption capacity, among which the top 10 ranking indicators belong to the yachting tourism consumption capacity.

4.2. Temporal and Spatial Characteristics of Yachting Tourism Consumption Potential

The comprehensive weight is determined using the combination of the AHP and entropy methods using Equations (1)–(3); the comprehensive weight changes due to the objective data change for each year are shown in

Table 3. Yachting tourism consumption potential composite index and composition.

Year	Consumption Potential Composite Index	Consumption Capacity Index (Comprehensive Weight)	Consumption Expenditure Index (Comprehensive Weight)	Consumption Quality Index (Comprehensive Weight)	Consumption Environment Index (Comprehensive Weight)
2014	34.98	8.38 (0.227)	8.51 (0.268)	10.68 (0.336)	7.41 (0.168)
2017	43.50	13.39 (0.237)	8.52 (0.270)	14.10 (0.343)	7.50 (0.149)
2019	51.93	18.30 (0.260)	9.85 (0.276)	15.16 (0.316)	8.61 (0.147)

. The non-dimensional value of each index is multiplied by the comprehensive weight value, and the yachting tourism consumption potential and subsystem composite indexes are obtained using linear weighting method using Equation (4). According to the calculation results, the general index of the consumption potential of yachting tourism in coastal areas showed a stable growth between 2014 and 2019 (see Table 3). This is due to the combined effect of several factors, such as the development of tourism in coastal areas, the construction of infrastructure, and the gradual improvement in the yachting policies [26]. Among them, the consumption capacity and consumption quality subsystems rose and were the main driving forces that enhanced the consumption potential of yachting tourism, whereas the consumption expenditure and consumption environment subsystems rose slowly.

From the comprehensive index of yachting tourism consumption potential (see

Table 4. The composite index of yachting tourism consumption potential in coastal cities.

	2014	2017	2019	Average Value	Ranking
Dalian	32.17	34.11	38.39	34.89	9
Tianjin	36.05	42.48	45.74	41.42	7
Qingdao	46.00	48.74	57.37	50.71	4
Weihai	22.47	26.79	29.88	26.38	11
Bohai Sea Rim	34.17	38.03	42.84	38.35
Ningbo	31.79	39.25	49.82	40.29	8
Zhoushan	21.95	32.09	42.29	32.11	10
Shanghai	51.98	64.94	77.04	64.65	1
Yangtze River Delta	35.24	45.43	56.38	45.68
Xiamen	33.72	46.90	52.20	44.27	6
Guangzhou	45.27	53.91	66.41	55.20	3
Shenzhen	35.67	61.39	72.65	56.57	2
Haikou	21.60	24.58	30.54	25.57	12
Sanya	41.03	46.85	60.79	49.56	5
Pan-Pearl River Delta	35.46	46.73	56.52	46.23

), there is a clear gap in consumption potential among cities, with Shanghai, Shenzhen, and Guangzhou ranking in the top three and Zhoushan, Weihai, and Haikou in the bottom. According to the original basic data analysis, Shanghai and Shenzhen, as first-tier cities are far ahead of other cities in terms of regional economic development, tourists’ consumption capacity, and yacht policy support (see Figure 1). These cities’ yachting tourism infrastructure is better, yacht industry policy support is stronger, and the tourism public service system is more mature, which can attract a large number of consumers. Guangzhou has a high potential for yachting tourism consumption mainly because of its high level of net property income, a large number of college students, and huge potential market for yachting tourism. Although the Bohai Rim region is endowed with unique marine resources, there are still deficiencies in the consumption capacity, consumption environment, and infrastructure construction.

4.3. Influencing Factors of Yachting Tourism Consumption Potential

In the panel data regression using Equation (7), model selection affects the outcome of the regression analysis, and inappropriate selection of the regression model causes a large error in parameter estimation. The three main types of panel data regression models are pooled OLS (POOL), fixed effects (FE), and random effects (RE). The suitability of a specific type of model can be evaluated with various tests [46]. First, model tests were conducted to facilitate the identification of the optimal model that showed significance at the 5% level (see

Table 5. Results of model test.

Type of Test	Purpose of Test	Test Value	Test Conclusion
F test	FE model and POOL mode are compared and selected	F (11, 17) = 8.564, p = 0.000	FE model
BP test	RE model and POOL model are compared and selected	χ2(1) = 5.596, p = 0.009	RE model
Hausman test	FE model and RE model are compared and selected	χ2(7) = −4.858, p = 1.000	RE model

Note: POOL: pooled OLS; FE: fixed effects; RE: random effects.

). Furthermore, F (11,17) = 8.564 and p = 0.000 < 0.05, implying that the FE model is superior to the POOL model. The BP test showed significance at the 5% level. With chi (1) = 5.596 and p = 0.009 < 0.05, the RE model proved to be superior to the POOL model. The Hausman test does not show significance; chi (7) = −4.858, p = 1.000 > 0.05, implying that the random effects model optimizes the fixed effects model. Thus, the final results were analyzed with reference to the random-effects model 3.

In Model 3 (see

Table 6. Panel data regression model results.

Variables	Model 1 (POOL Model)		Model 2 (FE Model)		Model 3 (RE Model)
	Correlation Coefficient	T-Statistic Value	Correlation Coefficient	T-Statistic Value	Correlation Coefficient	T-Statistic Value
Intercept distance	−20.097	−0.641	−4.474	−0.419	−16.105	−1.173
LnHP	0.480 **	3.969	0.001	0.003	0.304 **	2.897
LnFAI	0.184 *	2.520	0.117 *	2.615	0.110 *	2.141
LnPDI	0.238	1.718	0.884 **	3.554	0.520 **	4.426
LnODR	0.087	1.333	−0.023	−0.683	−0.024	−0.428
LnCDR	0.118 *	2.187	0.030	1.251	0.036 *	2.213
LnBPI	−0.049	−0.910	0.145 *	2.310	−0.007	−0.157
LnCPI	3.215	0.463	−0.660	−0.276	2.254	0.761
R2	0.745		0.904		0.869
Test	F (7, 28) = 61.243, p = 0.000		F (7, 17) = 44.430, p = 0.000		χ2 (7) = 508.879, p = 0.000

Note: * p < 0.05 ** p < 0.01. HP: the average selling price of commodity houses; FAI: total social fixed asset investment; PDI: per capita disposable income; ODR: the old-age dependency ratio; CDR: child dependency ratio; BPI: number of people participating in basic pension insurance; CPI: consumer price index of residents.

), all variables are significant at the 5% confidence level, except LnODR, LnBPI, and LnCPI, which do not pass the significance test. The coefficient of disposable income per capita was 0.520, the average sales price of commodity houses was 0.304, the social fixed asset investment was 0.110, and the child dependency ratio was 0.036. These calculations confirm that per capita disposable income has the greatest influence on the consumption potential of yachting tourism, while the influence of the child dependency ratio is relatively small.

For the LnHP, it shows significance at 0.01 level (t = 2.897, p = 0.007 < 0.01) with a regression coefficient value of 0.304, indicating that the average sales price of commodity houses has a significant positive effect on consumption potential. Here, the increase in house prices exerts a “wealth effect”. Accordingly, the increase in house prices leads to an increase in household wealth and increases the consumption capacity of residents [40,47,48], which, in turn, influences the restructuring of residents’ consumption and promotes the release of the consumption potential of yachting tourism.

For the LnFAI, it was significant at the 0.05 level (t = 2.141, p = 0.041 < 0.05), and the regression coefficient value is 0.110 > 0, indicating that social fixed asset investment has a significant positive influence on consumption potential. Social fixed asset investment can reflect the level of economic urbanization to a certain extent; the higher the level of urbanization, the more sound the social infrastructure construction, especially the increase in investment in tertiary industry construction, which creates a good consumption environment for yachting tourism [47,48,49].

For the LnPDI, it was significant at the 0.01 level (t = 4.426, p = 0.000 < 0.01) with a regression coefficient value of 0.520 > 0, denoting that disposable income per capita has a significant positive relationship with consumption potential. First, an increase in disposable income can improve the consumption structure of residents who have more discretionary income to spend on enjoyable consumption while satisfying the consumption of necessities [50,51,52,53]. Yachting tourism is an enjoyment-oriented consumption, which is a manifestation of the upgrading of consumption structure and quality of life after residents’ income level reaches a certain level. The demand for yachting tourism consumption is positively related to the residents’ income level. Therefore, the per capita disposable income has an obvious role in promoting the consumption potential of yachting tourism.

For the LnCDR, it was significant at the 0.05 level (t = 2.213, p = 0.035 < 0.05) with a regression coefficient value of 0.036, indicating that the child dependency ratio can have a significant positive relationship with consumption potential. Although an increase in the number of children may, to a certain extent, increase the burden on households and thus create relatively strong incentives for saving and cautious consumption [46,54,55], the process of raising children includes many leisure consumption components such as the widespread development of youth sailing in China [56,57,58]; the prevalence of the concept of “raising children for old age” in China makes the increase in the child-rearing ratio a boost to yachting leisure consumption [34]; hence, the child-rearing ratio has a positive rather than a negative impact on the consumption potential of yachting tourism.

5. Conclusions

Current research on tourism consumption potential is scarce, with previous studies focusing on the tourism industry potential [18,59,60] and tourism development potential [61,62,63]. The consumption potential of yachting tourism is not only the “gap” between the ideal level and the current actual level but also the sum of the existing resource elements that can guarantee future development. From the perspective of the “support guarantee” theory, the consumption potential of yachting tourism can be regarded as a comprehensive system composed of consumption capacity, expenditure, quality, and environment, so this study constructs an index system to evaluate the consumption potential of yachting tourism.

Using empirical research, we found that the consumption potential of yachting tourism in China’s coastal cities was closely related to consumption quality and capacity, and the consumption expenditure and environment of yachting tourism still had great room for improvement. It is essential to strengthen the construction of a yachting tourism consumption environment and increase support for the yachting industry.

This study explored the factors that influence the consumption potential of yachting tourism. It was found that the level of residents’ income, household fixed assets, level of economic urbanization, and residents’ household burden were the main factors influencing yachting tourism consumption potential. The child dependency ratio, social fixed asset investment, average selling price of commodity houses, and per capita disposable income all positively influence tourism consumption potential in coastal cities in China, and the effects are in increasing order. What’s interesting here is the relationship between the price of housing and the potential for yachting. Based on the China Household Group Study (CFPS), property wealth significantly increased travel spending, and the influence of residential wealth on tourism consumption is not through the mortgage effect but the wealth effect. The possible reason is that the families who buy houses may have the pressure of mortgage in the short term and reduce the travel consumption expenditure, but in the long term, with the increase in family income and housing wealth accumulation, they will expand the travel consumption expenditure and may choose to pay off the housing mortgage loan in advance [63]. Thus, economic and social development, housing policies, and population policies all have key roles in harnessing the leisure consumption potential of residents [34].

This study also found that the main path to unleashing the potential of China’s yachting tourism consumption is to effectively increase residents’ income, enhance consumption capacity, improve the quality of tourism consumption, and create a good consumption environment. However, there is a large gap in yachting tourism consumption potential among Chinese cities, with Shanghai, Shenzhen, Guangzhou, and other cities having higher yachting tourism consumption potential. In response to the uneven regional development, different regions should find weak links in the development of consumption potential and make up for the shortcomings according to local conditions.

Developing countries such as Turkey, Egypt, and Estonia regard yachting tourism as an alternative form of tourism and are choosing to invest capital in this area [8]. This study proposes a method to measure a comprehensive index of consumption potential based on consumption capacity, expenditure, quality, and environment of yachting tourism. This approach provides a theoretical basis and provides a practical tool for coastal cities in other countries to promote the consumption and development of yachting tourism.

Based on the above conclusions, we offer the following recommendations. First, it is necessary to continuously improve the income of residents, increase the corresponding wage, family business, and property income, implement a paid leave system, and improve the social security system to relieve the worries of workers. At the same time, yachting tourism consumption payment willingness and purchasing power should be enhanced by reducing the yachting consumption tax and mooring and membership fees. Second, the construction of yachting tourism infrastructure and service upgrades can be promoted, and public marinas can be reasonably laid out to satisfy the demand for a large amount of low-end yachting consumption. Third, there is the need to extend the yachting tourism industry chain to create a good consumer environment, whereby the product structure of yachting tourism on land, shore, and water is enriched. Additionally, the relationship between yachting activities and the regional ecological environment should be handled well, and shoreline resources should be protected. Finally, socioeconomic development is crucial to harnessing yachting tourism consumption potential. For example, it is necessary to improve the supporting measures of the three-child policy, formulate marine sports events or sponsorship programs for teenagers, and cultivate potential consumer markets to develop yachting tourism. This study has some limitations, which offer opportunities for future research. First, given the lack of statistical data on China’s yacht industry, it is still difficult for relevant information to form time series data; hence, the selection of cross-sectional data from the past three years cannot explain the development trajectory of the sample more comprehensively, and the consumption potential of yachting tourism cannot be grasped and analyzed in the longer term. Second, the study units also failed to reflect all cities in China’s yachting tourism development, especially inland non-coastal cities. Future studies could select data with longer time series and expand the number of sample units to improve the scientific and objective nature of the findings. Variables such as nautical culture and specific consumption expenditure of yachting tourism can be continuously incorporated into the construction of an indicator system to measure the consumption potential of yachting tourism more thoroughly.