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Article

Factors Influencing the Willingness to Pay in Yachting Tourism in the Context of COVID-19 Regular Prevention and Control: The Case of Dalian, China

by
Yunhao Yao
*,
Ruoquan Zheng
and
Merle Parmak
College of Public Administration and Humanities, Dalian Maritime University, Dalian 116000, China
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(20), 13132; https://doi.org/10.3390/su142013132
Submission received: 12 August 2022 / Revised: 2 October 2022 / Accepted: 9 October 2022 / Published: 13 October 2022
(This article belongs to the Special Issue Culture, Tourism and Leisure Behavior)
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Abstract

:
This study attempts to construct a framework of factors affecting the yachting tourists’ willingness to pay (WTP) in the context of COVID-19 regular prevention and control in Dalian, China. Relying on the framework of the extended theory of planned behavior (TPB), perceived external institutional and destination attribute factors are introduced to enhance the prediction of WTP. The results of the multivariate ordinal logistic regression model show that significant factors affecting yachting tourists’ WTP are income, education, past consumption experience, attitudes, destination attributes, and perceived behavior control. In addition, different factors affect the WTP of tourists who prefer motor boats and non-motor boats.

1. Introduction

At the beginning of 2020, the COVID-19 outbreak disrupted people’s normal life and work. This major public health event had a huge impact on international economy and social development, and the tourism industry was hit hard. The number of domestic tourists in 2020 was 2.879 billion, down 3.022 billion or 52.1% from the same period in 2019 in China. The average spend per trip was 774.14 yuan, 18.8% lower than the same period in 2019 [1]. The number of imported and local cases reported in China has decreased significantly. To ensure that COVID-19 does not spread further, the Chinese government has adopted a number of routine prevention and control policies, such as “dynamic zero clearing”, “widespread vaccination”, and “early detection and notification” (hereinafter referred to as “regular prevention and control measures”). Chinese President Xi Jinping emphasized that regarding the COVID-19 regular prevention and control measures, people’s lives, safety, and physical health should be put first, and the restoration of production and life order should be accelerated. Furthermore, the establishment of an effective long-term mechanism to promote consumption growth should be explored [2].
Despite the impact of COVID-19 on tourism, the global development of yachting tourism has been unexpected [3]. Yacht destinations with highly developed local markets, such as the Netherlands, Germany, and Italy, have emerged as “winners” in the market. Yacht chartering businesses were full from May to September 2020, with bookings far exceeding those in 2019 [4]. Although China’s yachting tourism experienced a temporary pause in the early days of the epidemic (the first half of 2020), with the regular epidemic prevention and control measures, China’s yachting tourism is also gaining momentum after the epidemic. For example, statistics released by Sanya Maritime Administration in Hainan province show that 139 new yachts were registered in 2020, up 27.7% year-on-year [5]. Referring to the data of the official media “Dalian Release”, Dalian ushered in a tourism peak in July 2022, receiving 9.2689 million tourists, an increase of 80.18% year-on-year, of which 43.29% were tourists received by maritime tourism [6]. According to the latest data, in 2019, mainland China built 114 yacht marinas, with a total of 11,506 berths and 25,000 yachts (including fishing and sailing boats), and more than 100 sailing events were held [3]. Although the pandemic has changed the way people live, the safety, privacy, leisure, sports, and other attributes of yachts are more and more favored. Yachting tourism provides a way for the tourism industry to resume after the epidemic [3]. Researchers should pay attention to changing trends in yachting activities, and it is very important to examine the factors that may influence choices in yachting tourism.
Although the industry has performed well after the epidemic, few studies have comprehensively investigated the factors that influence the consumption decision-making of yachting tourism [7,8]. The theory of reasoned action (TRA), proposed by Fishbein and Ajzen, proposes that human behavior is determined by behavioral intentions, and behavioral intentions are affected by attitudes and subjective norms. The theory of planned behavior (TPB), the technology of acceptance model, and other theories have been built on this model [9]. Among them, TPB theory is the current mainstream model of endogenous influencing factors of consumer behavior. It uses attitudes, subjective norms, and perceived behavior control to explain individual behavior intentions [10]. Several studies have verified TPB theory related to tourism intentions, destination selection, information search behavior, and mobile payment willingness [11,12,13,14].
However, as the TPB model cannot fully explain and predict individual consumption behavior without contextual variables, it is necessary to improve the traditional model by integrating other predictive variables [15,16]. These influencing factors may include perceived guarantee institutional factors (like policy support during the pandemic) [17], perceived destination attributes [18], past behavior patterns [19], and so on. Therefore, to provide the yachting tourism business operators with more reasonable marketing strategies and suggestions, this study will deepen the TPB model to explain tourists’ willingness to pay for yachting tourism products.
In the context of the COVID-19 regular prevention and control, establishing a new tourism development pattern in which the domestic tourism cycle is the main body, and the domestic and international dual cycles promote each other, is a new change in China’s “14th Five-Year Plan” period. The development of yachting tourism can effectively stimulate domestic demand and promote the revitalization of the consumer market in China [3]. Therefore, this study used the expanded TPB theory as the analytical framework, taking yachting tourists (consumers who have participated in yachting activities) and potential consumers (not participating but may participate in the future) as the analysis objects. It builds an influencing mechanism for yachting tourism consumption behavior under the conditions of COVID-19 regular prevention and control.
The specific aims of the study are as follows: (1) to clarify the influencing factors of the WTP for yachting activities; (2) to identify different factors affecting the WTP of tourists who prefer motor boats and non-motor boats; and (3) to put forward targeted policies and recommendations for yachting tourism business operators and destination managers, which may have specific significance for other countries aiming to revive and develop yachting tourism. The organizational structure of this study is thus: Section 2 presents the literature review and research hypotheses; Section 3 describes the method and data collection; Section 4 describes the results of influencing factors on the WTP for yachting tourism in Dalian coastal line; and Section 5 and Section 6 are the conclusions and limitations, respectively.

2. Literature Review and Research Hypotheses

2.1. Yachting Tourism

No official definition of yachting tourism is provided in the documents and manuals for tourism statistics [20] or in the Encyclopedia of Tourism [21]. Overall, yachting tourism is defined as a form of special interest tourism and refers to the use of water vessels or boats for leisure purposes [22], which is a basic classification of nautical tourism. The latter is more extensive and also includes cruise tourism [23,24]. The China Cruise and Yacht Industry Association (CCYIA) functions as either a marketing body or a government department involved in yachting development issues [25]. It has defined a yacht as a boat with a length of no less than 5 m, which is used for sightseeing, recreation, and water sports, and all other forms of navigation and water appliances, also known as “recreational boating”, mainly including yachts, sailboats, speedboats, motor boats, canoes, and so on which give tourists the freedom to sail to different destinations and enjoy a lifestyle of entertainment. Yachting tourism is a comprehensive industry that takes marine tourism resources as its content and serves nautical tourists. It includes boat builders, engine manufacturers, boat accessories and marine equipment manufacturers, and service providers [4]. Marina is the main service provider of yachting tourism [26]. It has a set of operation forms different from other marine tourism, making yachting tourism a high-end, exclusive leisure form of tourism consumption [27,28]. The available studies agree that yachting tourism promotes economies [29,30], and many countries, such as Estonia, Egypt, Montenegro, and Turkey, tend to invest capital in this industry [27,31]. The development of yachting tourism also has significant environmental and social impacts, both positive and negative [32,33,34,35]. There are some studies on the consumption behavior of yachting tourism, mainly focusing on consumer demographic characteristics, expenditure structure, yachting experience, marina choice, service satisfaction, and other fields [24,26,27,36,37,38]. However, there is still a lack of in-depth research on the influence mechanism of yachting tourists’ WTP, especially during the COVID-19 pandemic.

2.2. Extended Theory of Planned Behavior (TPB)

TPB was the derivative theory of reasoned action, which was proposed to explain the decision-making process of individual behaviors, those performing the behavior, and the subjective norms acting as driving factors affecting behavioral intention [5,39]. However, non-volitional factors exist in various situations when the actor is restricted by the environment. The TRA theory could not predict behavior well, then Ajzen introduced perceived behavioral control and proposed the TPB to improve the predictive ability and application scope of the TRA [7]. People’s behaviors are affected by attitude, subjective norms, perceived behavioral control, and behavior intention [12,40]. Attitude refers to an individual’s tendency to demonstrate positive or negative views through a particular behavior; subjective norms refer to the social pressures that individuals take into account when deciding whether or not to behave in a certain way; and perceived behavioral control refers to a person’s subjective judgment of their ability to demonstrate a specific behavior [12,41,42,43].
Although the TPB is increasingly used and is effective in improving the explanatory and predictive power of research on behavior, Ajzen believes that the TPB model is not perfect. Other factors need to be introduced to supplement and improve the study of individual decision-making behavior in specific situations [15]. Studies have combined different tourism scenarios and introduced additional variables to expand the theory, such as the application of moral norms, local attachment, perceived risk, and other factors to the fields of rural tourism, ecotourism, slow tourism behavior intention, and so on [11,14,15]. New variables have been introduced to the TPB model to enhance its ability to predict human behavior in specific tourism types. This applies as long as these new variables are necessary factors for a particular behavioral decision and are conceptually independent of the existing factors in the theory [16].
However, to the authors’ knowledge, like perceived institutional guarantee, destination attribute factors are still rarely included in extended the TPB in tourism and pandemic studies [44]. This reveals a gap that could lead to the extension of the TPB framework for analyzing this promising niche market. Research specifically designed for the context of yachting tourism could contribute to the development of measurement criteria for yachting tourism and yachting tourism research in the future. Through focus groups and literature review, demographic, psychological and behavioral factors, perceived institutional guarantees, and perceived destination attribute factors could be developed for yachting tourism.

2.3. Willingness to Pay (WTP)

The WTP emphasizes the recognition of products and services from the perspective of prices, including the affordability and tolerance of prices [45]. As a research hotspot in the field of consumption, the WTP measures the economic value of non-market goods, such as the application of the conditional value method in the demand and evaluation of public goods. Examples of this are ecological compensation payments, scenic spot fees, and low-carbon products [46,47,48]. Additionally, the WTP in this study is set as a direct expression of the behavioral intention, which is an ordinal scale to assess the degree of willingness and quantitatively reflect consumption intention, see Section 3.2. Measures for details.
According to Kalish and Nelson, WTP is the highest price a consumer is willing to pay for a good or service, which is the upper limit of the acceptable price [49]. There are four ways to obtain consumers’ WTP: market data analysis, experiment, direct survey, and indirect survey [50]. Methods include laboratory, field, and auction experiments. Direct surveys include expert judgment and customer surveys, indirect investigations including conjoint analysis, and discrete choice analysis. Breidert, Li and Yang found that each of these approaches has its own advantages and disadvantages [51]. For example, historical data cannot reflect all of the changing trends of prices, and it is difficult to meet the requirements of payment prediction for new commodities and services. The experiment method is especially suitable for the payment prediction of new commodities and services, but it is time-consuming and laborious, and the predictive accuracy is limited. The indirect survey method is suitable for payment prediction for new goods and services; the cost is not high, but the prediction accuracy is general and not closely related to actual purchase behavior.
There are many studies on tourism consumption intention, but they mainly use the Likert scale to measure subjective consumption intention [52] or use typical binary variables of willingness (or not), purchase (or not), and participation (or not) as measurement items [15,53]. However, these forms of measurement do not reflect consumers’ recognition of service levels from the price level. The only reasonable way to express the value of all goods and benefits is the willingness to pay.

2.4. Theoretical Model and Research Hypotheses

This study aims to construct an influencing factor framework of the WTP based on the TPB model and the research results of influencing factors of yachting tourism consumption willingness at home and abroad. It examines five aspects: demographic, psychological, behavioral, perceived institutional guarantees, and perceived destination attributes. The theoretical analysis framework is shown in Figure 1.
Boaters’ sociodemographic characteristics such as gender, age, marital status, educational level, and income are important determinants of expenditure on boating trips. Lee conducted a study on recreational boating expenditure and found that household income level was significantly positively correlated with all consumption types, while age was significantly negatively correlated with spending on boat food and autogas [30]. In a case study of yacht sales companies, Sherman, Leach and Zhang found that owners of sailboats were about 55-years-old and most of their children had finished college, while motor boat fans tended to be younger, between 35- and 50-years-old. Therefore, we propose the following [54]:
Hypothesis 1.
Individual demographic factors such as gender, age, education level, average annual income, and family structure affect the WTP for yachting tourism, but there will be differences in the impact of each factor.
According to psychological factors in the TPB theory, a positive attitude toward yachting tourism inclines people to practice yachting tourism behavior. High levels of subjective norms and perceived behavioral control lead to stronger behavioral intention [10]. In addition, in the context of specific tourism consumption, values are often better than demographic characteristics to explain the differences in tourism behavior [55]. The fundamental reason for the slow development of yachting tourism in China is not high consumption, but values. Chinese people advocate frugality and do not like excessive publicity and adventure, which does not match yachting activities that pursue freedom, adventure, excitement, and individualism [56]. Therefore, this paper proposes the hypothesis:
Hypothesis 2.
Positive attitudes, values that support challenge and adventure, subjective norms, and perceived behavioral control positively affect the WTP for yachting tourism.
Behavioral variables are important supplements to demographic factors [57]. Bagozzi and Kimmel believe that the variable of “past behavior” should be taken as an independent component of the revised TPB model, because no other indicator can better reflect a consumer’s consistent values between past behavior and future behavior [58]. If consumers are familiar with the commodities or services, their WTP will be increased. Therefore, we formulate the following:
Hypothesis 3.
Past frequent consumption experiences positively affect the WTP for yachting tourism.
In the context of normalized COVID-19 prevention and control, stimulating yachting tourism consumption is inseparable from a huge and complex social support system. From the perspective of the macro system, a sound social security system will have a “crowding out effect” on national savings, which will help release social consumption power. Secondly, the institutional system related to China’s yachting tourism is still very immature. Yachting activities involve many regulatory links such as registration, sailing, mooring, pollution prevention, and safety. Yacht safety management will affect the WTP for yachting tourism. Thirdly, the COVID-19 inspection and epidemic prevention system for yachting destinations should be improved. For example, the International Council of Marine Industries Association (ICOMIA) has issued the “Port Operation Guide” integrating many aspects of technologies and methods to create responsible and safe yacht marinas. Regulating the reception links of yachting tourism is beneficial to dispel consumers’ worries and improve the travel consumption experience. Accordingly, we formulate the following:
Hypothesis 4.
Perceived institutional guarantee factors such as a sound social security, yacht safety management, and epidemic prevention and control systems positively affect the WTP for yachting tourism.
The push-pull theory emphasizes that the formation of tourism behavior is inseparable from the external pull factor [59,60,61]. Yachting tourism destinations are the sum of the tourism hardware and service software of a region, which reflect yachting tourists’ overall experience of the destination. It is composed of multi-dimensional attributes such as attraction, natural and social environments, infrastructure, and so on [62,63,64]. Concerning yachting tourism, waterfront scenery, yachting routes, supporting facilities, transportation systems, etc. are important attractions. These “hard conditions” can be classified as perceived destination core attributes; “soft conditions” can be classified as the service level of employees, yacht marketing, tourism information, and safety conditions, which provide external guarantees and can be attributed to perceived destination external factors. The improvement of perceived destination attributes can enhance the charm of yachting tourism, and improve the accessibility, comfort, and convenience of consumers participating in yachting, thereby enhancing the WTP. Hence, we formulate the following:
Hypothesis 5.
Perceived rich destination attributes positively affect the WTP for yachting tourism.
The price of yachting tourism varies greatly due to different types of yachts. In Dalian, our research destination, the price of a non-motor boat experience (such as sailing, windsurfing, water skiing, canoeing, rowing, and inflatable boats) is approximately 30–300 yuan/hour/person, while the price of a motor boat cruise experience (such as a speedboat, fishing boat, and auxiliary power sailing boat) is 100–1000 yuan/hour/person. Due to the relatively high price of motor boats, the WTP may be more affected by tourists’ income, attitude and perceived destination attributes [36,37]. In contrast, non-motor boat fans mainly play near the shore and have a relatively dense population. They may pay more attention to epidemic prevention and safety management. Therefore, we propose the following:
Hypothesis 6.
There are differences in the influencing factors of the WTP between motor boats and non-motor boats preferences.

3. Research Design

3.1. Measures

According to Ajzen and Fishbein, an elicitation study is required for identifying the beliefs and vital referents of a new context or population [39]. Therefore, we introduced the focus group discussion method and invited one professor, one associate professor, and five graduate students in the field of yachting tourism research to conduct focus group discussions on the WTP for yachting tourism and its influencing factors at Dalian Maritime University in April 2020. The team’s task was to summarize and refine the relevant measurement variables, and constantly verify against previous literature to form the items.
The WTP in yachting tourism is a variable that describes how much consumers are willing to pay for yachting tourism products, including bareboat or crewed charters, day cruises or cabin rentals, etc. The direct survey method was used, taking into account that there are consumers who have not participated in yachting before and would be less familiar with the questions. There are significant differences in yachting tourism prices (such as motor boats and non-motor boats), so when designing the questionnaire, we did not use open-ended questions to obtain WTP but set seven options, namely 1 = less than 100 yuan/hour, 2 = 101–300 yuan/hour, 3 = 301–500 yuan/hour, 4 = 501–1000 yuan/hour, 5 = 1001–5000 yuan/hour, 6 = 5001–10,000 yuan/hour, 7 = 10,001 yuan/hour above. Consumers could choose one option considering the value of yachting tourism products, or services according to their preference, experience, and ability. This method has been confirmed in the existing research on the WTP [65,66].
The explanatory variables included five groups of specific and measurable descriptive variables, as shown in Table 1. (1) Demographic variables of gender, age, education level, average annual income, and family structure. (2) Psychological variables, four variables of consumer values, attitudes, behavior norms, and perceived behavior control. A modified version of the original TPB scale [41] was used, and the wording was modified to make the items relevant to yachting tourism [67,68]. (3) A behavior variable, using the statement “frequency of past yachting tourism” to measure past yachting tourism behavior [66,69,70]. (4) Perceived institutional variables to measure policies or systems adopted by government departments that can promote or inhibit the development of yachting tourism, including social security, yacht safety management and COVID-19 prevention and control systems [52,71]. (5) The perceived destination attribute variable was studied by Yu et al. [55], and the specific measurement indexes involved eight statements about yachting tourism scenery, onshore activities, and marina construction [37,72].

3.2. Data Source

Dalian is located at the southern end of the Liaodong Peninsula. It is the junction of the Yellow Sea, the Bohai Sea, and the vast northeast plain. The annual average temperature is about 10 degrees Celsius, the humidity is suitable, and it has unique maritime tourism resources and a prosperous tourism industry, making it a popular tourist city in China. In 2020, Dalian received 39.973 million tourists, with a total tourism revenue of 61.03 billion yuan. There are 103 star-rated hotels, 483 travel agencies, and 56 national A-level tourist attractions. Dalian has a coastline of 2211 km and a sea area of 23,000 square kilometers under its jurisdiction. It has more than 60 bathing beaches and six yacht marinas that have been built or are under construction. In view of Dalian’s developed maritime tourism, its superior natural, economic, cultural, and other geographical advantages have made it an important yachting tourism destination in northern China. Therefore, Dalian was selected as the case study.
Considering that the tourists around the marinas are the primary source of yachting tourism, they were selected as the survey participants. The questionnaire consisted of three parts: first, the basic personal information of consumers; second, the consumption characteristics and behavior preference of yachting tourism, such as favorite yacht type, frequency of yachting, main motivation, WTP etc.; and third, the influencing factors of WTP for yachting tourism. The relevant items (all the items of AT, SN, PBC, INS, CA, and PA) used the Likert 5-point scale method, and the numbers 1–5 indicated in turn “strongly disagree, disagree, general, agree, and strongly agree”.
The questionnaire survey was divided into two stages. The first stage was the pre-survey stage, which took place in Xinghai Plaza and Xinghai Bay Marina in June 2021. Through the pre-survey, the questions that were difficult for tourists to understand, unclear and ambiguous were revised, and the explanation of the concept of yachting tourism was supplemented to form the final survey questionnaire. The second stage was the formal investigation and data collection period from 1 July to 10 July 2021. A convenient sampling method was used for this study. As our main focus is on groups interested in paying for yachting tourism, we first asked a screening question to determine inclusion in the study (“Are you interested in yachting tourism?”). To meet the requirements for the number of participants (the number of participants in the study should be 5–10 times higher than the number of items in the questionnaire) [73], we aimed to distribute 300 questionnaires. Considering that recruiting more participants would increase the representativeness of the sample and reduce the sampling error in the survey, we increased the number of distributed questionnaires to 500.
Five members of our research team distributed the questionnaires to Dalian’s main scenic locations, such as Xinghai Bay, Donggang, Tiger Beach, Xinghai Plaza, and Bangchui Island (see Figure 2). Before we requested participants to complete the questionnaires, they were asked for their oral consent. A total of 500 questionnaires were distributed. Incomplete questionnaires (random responses, incomplete, and uniform responses) were excluded from the final sample. Finally, our study sample consisted of 453 participants, with an effective response rate of 90.6%.

4. Analysis and Results

4.1. Descriptive Statistics

Most of the sample were male (61.4: 38.6), were 25 to 45 years old (61.6%), had a junior college or bachelor’s degree (56.5%), had an average annual income less than 150,000 yuan (82.8%), and 19.4% of them had never participated in yachting before. In the sample, yacht cruising was the main consumption mode (93.37%), and bareboat charter only accounted for 6.62%. The motor boat was the main type of yacht preferred by consumers (42.83%); the non-motor boat was 57.17%. The WTP for yachting tourism was low, less than 100 yuan/hour, 101 to 300 yuan/hour account for 50.6% and 37.7% of the total sample, respectively.
Secondly, the demographic, psychological, behavioral, perceived institutional, and destination attribute characteristics of different yacht preferences are also different (see Table 2). By comparing the mean values, tourists who preferred motor boats had a more positive attitude, more support from surrounding groups, stronger perceptual control of money and ability, richer experience, paid more attention to tourism scenery, onshore activities, tourism services, tourism marketing and tourism safety, and had higher education and economic income. The tourists who preferred non-motor boats paid more attention to macro system guarantees, marina construction, tourism traffic and tourism information, were older, and were at a lower cultural and economic level.

4.2. Reliability and Validity Test

To improve the accuracy of the model analysis results, it is necessary to test whether the questionnaire has high reliability and validity. This study uses the Cronbach’s α coefficient to test the reliability of each variable. The Cronbach’s α coefficient was above the cut-off point of 0.7, indicating acceptable reliability [74], while in practical research, Cronbach’s α coefficient only needs to reach 0.6 (the minimum requirement) [42]. The subscales had a good reliability (with a range of values from 0.684 to 0.942), with the overall scale having strong credibility and high internal consistency.
To ensure the face validity of the constructs, the content and structure of the questionnaire were adjusted and revised based on pre-investigation of a large number of studies and in consultation with relevant scholars and experts to ensure the validity of the items [16]. In terms of construct validity, the exploratory factor analysis method was used to filter according to the principle that the items exhibiting low factor loadings (≤0.40), high cross-loadings (>0.40), or low communalities (<0.50) would be removed as a principle [75]. The factor of “easy to obtain information about yachting tourism” was excluded. The questionnaire has high construct validity. The results are shown in Table 3.

4.3. Result and Discussion

SPSS16.0 statistical software was used to estimate the influencing factor of the WTP for yachting tourism by using an ordered logistic regression model. Considering that yachting tourists with different preferences differ greatly in their WTP, the overall sample model, and the sample of tourists who prefer motor boats and non-motor boats, were regressed, respectively, to study the differences in the WTP further.
First, we introduced all explanatory variables into the ordered logistic model and use the “Forward: Conditional” strategy to select the explanatory variables. This strategy judges whether the explanatory variables can enter the model based on the value of the score test statistic. According to the change of the likelihood ratio chi-square under the conditional parameter estimation principle, it is judged whether the explanatory variable should be excluded from the model. The maximum likelihood estimation method was used to solve the parameters in the multivariate ordinal logistic model.
The significance level of the statistical test of the model was set as 0.05. The overall sample model I, the model II corresponding to the sample with a preference for motor boats, and the model III corresponding to the sample with a preference for non-motor boats were optimized in seven, eight and eight steps, respectively. Finally, the chi-square statistical values of the models were 214.908, 119.651, and 115.235, respectively, and p < 0.01 for all models, indicating that explanatory variables had a significant explanatory ability to influence the WTP. The overall estimation effect of the model was good, and the parameter estimation results of the model are shown in Table 4. There is no doubt that tourists who prefer motor boats and non-motor boats have different factors affecting their WTP, and hence, H6 is supported.
(1)
Demographic factors. Firstly, for the overall sample, education (β = 0.356, p < 0.05) and income (β = 0.420, p < 0.01) both had significant positive correlations with the WTP, and thus, H1 is partially supported. The continuous improvement of people’s economic and educational level would be conducive to the popularization of yachting tourism [76]. For tourists who prefer motor boats, age (β = 0.463, p < 0.1) and income (β = 0.651, p < 0.01) are significantly positively correlated with the WTP, the price of motor boat rental experience is relatively high, and consumer demand will increase with age and income. In contrast, the consumption threshold of non-motor boats is relatively low, and the offshore is close and relatively safe, so there is no significant relationship with the age and income of tourists. In addition, married families with minor children have a greater impact on the WTP for motor boats than married families with adult children (β = 1.200). Since most married families with minor children are in the stage of strong purchasing power, physical quality, and learning ability, their consumption for yachting tourism is higher, which is also consistent with the research results of Sherman et al. [54].
(2)
Psychological factors. First, there is a significant positive correlation between the attitude and the WTP for yachting tourism. The β values of the three models are 0.302 (p < 0.01), 0.245 (p < 0.05), and 0.318 (p < 0.01) respectively. Hence, H2 is partially supported. If individuals believe that yachting tourism is the embodiment of life interest and are interested in it, the probability of participating and the amount of expenditure would be greater. Secondly, there is a significant positive correlation between perceived behavior control and the WTP (β = 0.125). The influence of perceived behavioral control on WTP depends on individual control and perceived belief [12]. If individuals think their physical condition or ability is better, their control belief will be stronger, and they may participate more deeply in yachting under the normalized situation of COVID-19. If individuals perceive that they have more money, time, and other resources, the convenience of participating in yachting tourism will be stronger, and then the WTP for yachting tourism will be higher. However, values and subjective norms have no significant impact on the WTP. There may be no connection between values and tourist behavior, or the tourists are not aware of the relationship, or what the exact meaning is [77,78]. Yachting tourism consumption decisions are relatively independent, as yachting tourism has a limited following and belongs to a niche market; and people tended to travel in smaller groups and become more responsible tourists during the COVID-19 pandemic.
(3)
Behavioral factors. Past consumption experience has a positive correlation with the WTP for yachting tourism (β = 0.345, p < 0.01). Especially for the tourists who prefer non-motor boats (β = 0.627, p < 0.01), past yachting tourism behavior can reduce time, costs, and selection risks of consumers, and has a significant impact on future yachting behavior. Similar to Bagozzi and Kimmel’s study, past behavior had a direct impact on intentions and subsequent behavior [58]. In contrast, due to the relatively high personal income of people who prefer motor boats, past consumption experience and other factors have no significant impact on them. They have enough economic capacity to maintain a high frequency of yachting experience. This high frequency of consumption behavior is not highly correlated with good feelings associated with past consumption experience.
(4)
Perceived institutional factors. Perceived institutional factors were generally not significant for the WTP for yachting tourism. This result may be related to the current situation in which epidemic prevention and control is becoming routine and consumption in the domestic tourism market is steadily opening up and growing. With the liberalization of China’s domestic tourism, the resumption of flights for inbound and outbound tourism, as well as favorable policies and measures such as “vaccine passports” and non-quarantine entry, China’s tourism market is steadily recovering, and “reservation, limit, and off-peak” has become a new tourism rule [79]. The Chinese government’s strict epidemic prevention policy has, in a sense, guaranteed the consumption of yachting tourism. However, for tourists who preferred non-motor boats, perceived institutional guarantees had a significant positive correlation with the WTP (β = 0.112, p < 0.05). As consumers who prefer non-motor boats sail mainly close to the coast and in relatively densely populated areas, they are also more sensitive to epidemic prevention measures (e.g., reporting personal information, monitoring body temperature, and social distancing). The sounder the social security, yacht safety management, and epidemic prevention and control systems, the more the worries of consumers are reduced and their WTP stimulated [80].
(5)
Perceived destination attribute factors. There were significant positive correlations between the core attributes of destination and the WTP, with the β values of the three models being 0.182 (p < 0.01), 0.287 (p < 0.01), and 0.161 (p < 0.01), respectively. Hence, H5 is partially supported. The more beautiful the destination, the richer the onshore activities, the more complete the marina basic service facilities, and the more developed the tourism transportation are, the more consumers are willing to purchase yachting tourism services. As far as the degree of influence is concerned, the core attributes had a greater impact on consumers who preferred motor boats. The reason concerns high fuel consumption, and high maintenance, berthing and labor costs. Sailing distances are also relatively far from the mainland coastline, and motor boats users have higher demands for natural scenery on the route, marina facilities, and shore transportation. Users have greater demand and higher requirements for core attributes, and they are willing to pay higher prices for them [54]. In addition, perceived destination peripheral attributes have no significant impacts on the WTP. This may be because local yacht clubs or sea cruise companies could provide safe and high-quality services, as well as a socially secure environment, reducing consumers’ sensitivity to peripheral attributes.

5. Conclusions

The local distance, high frequency, nature-friendly, family-oriented, customized, and small group properties of yachting tourism could meet the new transformation characteristics of current domestic tourism in China, under the background of COVID-19 regular prevention and control. There are many studies on tourist behavior from the perspective of social psychology [81,82] that use the TPB as a theoretical framework. However, there are still other internal and external factors that should be considered, such as demographic characteristics, values, past behaviors, and perceived destination attributes in specific tourism situations [13,14]. Under the complex and changeable situation of COVID-19, tourists have generally increased their risk awareness. They pay more attention to the sanitary conditions, emergency measures, and diversion measures of destinations [44].

5.1. Theoretical Implications

This study constructs a comprehensive framework of factors affecting the WTP for yachting tourism under the COVID-19 pandemic. It expands the original TPB theory in line with Ajzen’s standards for theoretical expansion [10]. Since there were few studies on the role of yachting on perceived institutional guarantees and destination attribute factors, considering these variables could greatly improve our understanding of the WTP for emerging yachting tourism and enhance the explanatory power of the TPB theory. It might be beneficial for future researchers to consider the role of these key variables when developing and extending theories related to the decision-making process of yachting tourism consumption.
Second, this study innovatively takes the WTP as the dependent variable and uses ordinal logistic models to systematically analyze the factors influencing the WTP and their differences in different yacht preferences. It fills the relative gap in the quantitative research of yachting tourism consumption decision-making in China. The WTP reflects tourists’ recognition of yachting services from the price level, which has specific practical significance for yachting tourism market positioning and segmentation. This study has found that the WTP for yachting tourism is very low, less than 100 yuan/hour and 101 to 300 yuan/hour account for 50.6% and 37.7% of the total sample, respectively. The COVID-19 pandemic has profoundly impacted people’s tourism psychology, behavior and demand, and reduced tourism consumption expenditure. According to the Statistics of the Ministry of Culture and Tourism of China, domestic tourists spent 774.14 yuan per trip in 2020, 18.8% lower than the same period in 2019. Under the normal prevention and control of the epidemic, the weakening trend of tourism consumption intention is inevitable [17].
Third, the significant variables influencing the WTP for yachting tourism consumption are income, past experience, education level, attitudes, perceived destination core attributes, and perceived behavior control in descending order of contribution degree. Among them, attitude and perceived core attribute factors affect the payment behavior of tourists who prefer both motor and non-motor boats, so they are key factors during the COVID-19 pandemic. The results of this study confirm the positive impact of perceived destination core attributes on attracting yachting tourists.
Fourth, this study recognizes the particularity of the connotation and extension of yachting tourism and innovatively divides the investigation of motor boat and non-motor boat. It confirms that there are differences between motor boat tourists and non-motor boat tourists in terms of the influencing factors. The reason lies in the difference in consumption cost between the two. As Lee showed, the difference in consumer spending ability and income level is an important reason for the different ways of recreational boating [30]. Specifically, the consumption threshold of motor boats is relatively higher. Family structure, income, age, perceived core attributes of destination, and attitude positively affected their WTP, while factors such as education level, yachting experience, and perceived institutional guarantee had no significant impact on them. This is also because these tourists have a relatively strong ability to bear risks [83]. Entry into non-motor boating is relatively simple, and the cost relatively low. The influence of age, income, family structure, and other factors on non-motor boat users was not significant, but factors such as education level, past experience, attitudes, perceived destination core attributes, and institutional guarantees positively affected the WTP.

5.2. Managerial Implications

By analyzing the research results, this study can provide practical marketing management strategies for yachting tourism destinations. Multiple stakeholders, including the government, yachting enterprises, and industry associations, need to make efforts to improve the consumption WTP of yacht tourists and focus on tourists’ attitudes, perceived behavior control, perceived institutional guarantee, and other key factors.
Yacht clubs and operators could: (1) conduct theme activities, such as yacht experience, sailing race, exhibition exchange, and other promotional activities, to attract a wide range of sports enthusiasts, to enrich the consumer experience, and reinforce a positive attitude; (2) provide safe and meticulous service facilities and high-quality service levels, including ship maintenance, berth chartering, and maritime consultation, and improve contracts and treaties to create convenient consumption conditions for consumers and increase their perceived behavior control; (3) reduce the yachting tourism cost through marketing methods such as “partnership yacht purchase, time-sharing vacation”, financial leasing and the strategy of cooperation with the destination cultural industry, hotel, business district, and sports industry to facilitate public participation in yacht consumption; (4) develop different marketing strategies for motor boats and non-motor boats preferers. For example, motor boat market development could focus on high-income, married, middle-aged families; the non-motor boat market development could increase experience marketing, and improve relevant yacht safety and epidemic prevention systems, so as to improve the WTP for this market segment.
Attitude and core attribute factors affect the payment behavior of yachting tourists, so yacht clubs, industry associations, government, and other organizations should guide the public to establish a positive attitude toward yachting tourism, and use formal and informal channels to display and publicize yachting culture, eliminating the misunderstanding of luxurious yachting tourism. Government departments should advertise beautiful natural and cultural tourism scenery, and design high-quality yachting tourism network routes with enterprises. It should integrate and utilize stereo marine resources to enrich waterfront tourism products to cater to the public leisure demand, improve the infrastructures such as marinas, strengthen the external traffic and municipal road network of yachting tourism cities, and attract the public to participate in yachting tourism activities. In addition, there must be a considerable increase in peripheral facilities, mooring facilities, and water area facilities of yacht marinas; further, cooperation with the market is important to build the marina into a tourist destination with a “vacation atmosphere” rather than retain it merely as a mooring facility. For example, establishing a yacht museum at the destination marina to enhance the charm of yachting tourism, popularizing yachting culture, and helping tourists form positive attitudes would make it an attractive tourist destination.
Finally, industry associations must be allowed to play a full role in ensuring and promoting yachting tourism. Yachting tourism skills standards and industry standards must be standardized under the framework of safety standards. Environmental protection must be offered along with social responsibility, and a good order of yachting tourism consumption must be maintained along with optimizing consumer experience. During the epidemic, perceived institutional guarantee must ensure that prevention and control standards are in place. For example, ICOMIA has issued a port operation guide, which advocates the establishment of a responsible and safe marina, including standardizing the reception link of the marina, maintaining communication with relevant departments, encouraging franchisees to disinfect ships regularly, and promoting marina digital management to ensure the standardized operation of yachting tourism. Yachting tourism related enterprises should ensure the safety of tourists by improving the system to increase consumers’ WTP.

6. Limitations and Future Research

Novel Coronavirus may stay with human beings for a long time and become a normal existence. This study focuses on the consumption behavior of yachting tourism in the context of COVID-19, which can also be used as a reference for other countries. However, this study has some limitations that provide opportunities for future research. First, the data was collected in one city. Future studies should provide comparison results with data obtained from yachting destinations in other regions or even other countries. Secondly, future studies could provide a more comprehensive understanding of the factors influencing the WTP of yachting tourists, by adding factors from other theories, such as motivation, perceived risk, and social concern. Finally, we only discussed the WTP of tourists with different yacht preferences and its influencing factors, and there is lack of discussion on the reasons why some tourists are not willing to pay. Future studies should expand sample types (people who do not choose yachting tourism) and use a broader theoretical framework to explain their behavior.

Author Contributions

Conceptualization, Y.Y. and R.Z; methodology, Y.Y.; software, R.Z.; validation, Y.Y., R.Z. and M.P.; formal analysis, Y.Y. and R.Z.; investigation, Y.Y.; resources, Y.Y. and M.P.; writing—original draft preparation, Y.Y. and R.Z.; writing—review and editing, Y.Y., R.Z. and M.P.; supervision, Y.Y. and M.P.; funding acquisition, Y.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by The National Social Science Foundation of China, The economic and social development research project of Liaoning Province in 2023, Basic Research Project in Central Universities, grant number 18CJY050/2023lslybkt-015/3132022302.

Institutional Review Board Statement

School of Public Administration and Humanities at Dalian Maritime University, 110207, 28 April 2021.

Informed Consent Statement

Not applicable.

Data Availability Statement

All the data are available within this manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Theoretical framework of influencing factors on the WTP for yachting tourism consumption.
Figure 1. Theoretical framework of influencing factors on the WTP for yachting tourism consumption.
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Figure 2. (a) Dalian geographic location. (b) Xinghai Bay marina. (c) Donggang marina.
Figure 2. (a) Dalian geographic location. (b) Xinghai Bay marina. (c) Donggang marina.
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Table
Table 1. The index design of the influencing factors as independent variables in the model.
Table 1. The index design of the influencing factors as independent variables in the model.
VariablesMeaningVariable Types
Demographic variablesGender1 = male, 2 = femaleNominal
Age1 = under 24-years-old, 2 = 25–34-years-old, 3 = 35–44-years-old, 4 = 45–55-years-old, 5 = over 55-years-oldOrdinal
Education1 = junior high school or below, 2 = senior high school or technical secondary school, 3 = junior college or bachelor’s degree, 4 = master’s degree or aboveOrdinal
Income1 = below 50,000, 2 = 50,000–100,000, 3 = 100,000–150,000, 4 = 150,000–200,000, 5 = 200,000–300,000, 6 = 300,000–500,000, 7 = more than 500,000 (yuan)Ordinal
Family Structure1 = unmarried, 2 = married without children, 3 = married with minor children, 4 = married with adult childrenNominal
Psychological variables [67,68]ValueI like challenges and adventures.Ordinal
Attitude (AT)AT1. I am interested in yachting tourism.
AT2. Yachting tourism allows me to experience a different kind of fun.
AT3. Yachting tourism has expanded my horizon.		Ordinal
Subjective Norm (SN)SN1. My family or relatives often participate in yachting.
SN2. My friends or colleagues often participate in yachting.
SN3. My family or relatives think I should participate in yachting.
SN4. My friends or colleagues think I should participate in yachting.		Ordinal
Perceived Behavioral Control (PBC)PBC1. I have sufficient income to participate.
PBC2. I have plenty of time to participate.
PBC3. I have the ability to deal with problems arising from yachting tourism.		Ordinal
Behavioral variable [66,67,68,69,70]Past experience (PE)The frequency of yachting tourism in the past: 1 = 0 times, 2 = once in many years, 3 = once in 3 years, 4 = 1 once in a year, 5 = multiple times in a year.Ordinal
Perceived
institutional variables [52,71]		Institution (INS)INS1. The social security system is sound.
INS2. The yacht safety management system is perfect.
INS3. Tourism epidemic prevention and management measures are comprehensive.		Ordinal
Perceived
destination attributes variables [37,55,72]		Core attributes (CA)CA1. The destination has a good natural environment, unique scenery and high tourism value.
CA2. Onshore destinations are rich in culture, sports, entertainment, shopping and other activities.
CA3. Basic service facilities of the marina are complete (water, electricity, sanitation, technical services, etc.).
CA4. Developed destination tourism transportation system.		Ordinal
Peripheral attributes (PA)PA1. The service level of yachting tourism practitioners is high.
PA2. The promotion of yachting tourism is strong.
PA3. The destination is in good security.
PA4. Easy access to information on yachting tourism.		Ordinal
Table
Table 2. Basic information of tourists with different yacht preferences.
Table 2. Basic information of tourists with different yacht preferences.
Prefer Motor BoatsPrefer Non-Motor Boats Prefer Motor BoatsPrefer Non-Motor Boats
ItemsMeanSDMeanSDItemsMeanSDMeanSD
WTP1.941.0431.520.813PBC3. Ability3.050.9932.980.827
Age2.120.9062.4321.161PE3.601.3752.431.329
Education2.790.6232.530.744INS1. Security2.461.0082.491.013
Income2.711.4352.101.124INS2. Safety2.620.9752.720.848
Value3.470.8353.250.926INS3. Prevention2.850.9522.820.778
AT1. Interest3.540.7542.990.823CA1. Environment3.171.2533.161.325
AT2. Fun3.750.7763.460.759CA2. Onshore3.061.1512.951.175
AT3. Meaningful3.670.7213.170.835CA3. Marina3.111.2243.151.321
SN1. Family2.770.9432.510.906CA4.Transportation3.111.2393.161.355
SN2. Friends2.840.9322.570.961PA1. Service2.901.1352.751.125
SN3. Relatives2.970.9052.610.940PA2. Promotion2.941.1632.681.070
SN4. Colleagues2.940.8912.650.971PA3. Public security3.161.1702.981.216
PBC1. Income3.141.1043.000.852PA4. Information2.770.9452.820.815
PBC2. Time2.930.9682.970.803
Note: AT = Attitude, SN = Subjective norm, PBC = Perceived behavioral control, PE = Past experience, INS = Institution, CA = Core attributes, PA = Peripheral attributes.
Table
Table 3. Reliability and validity tests of questionnaires.
Table 3. Reliability and validity tests of questionnaires.
ItemsFactor
Loading		Cumulative Variance Contribution RateItem-Total
Correlation		Alpha If Item DeletedCronbach’s α
Attitude (AT)0.684
AT1. Interest0.68561.596%0.3960.718
AT2. Fun0.8040.5100.572
AT3. Meaningful0.8560.5930.455
Perceived behavioral control (PBC)0.702
PBC1. Income0.76362.660%0.4850.651
PBC2. Time0.8180.5530.565
PBC3. Ability0.7920.5200.609
Subjective norm (SN)0.930
SN1. Family0.93582.696%0.7930.923
SN2. Friends0.9230.8790.894
SN3. Relatives0.8960.8590.901
SN4. Colleagues0.8820.8150.916
Institution (INS)0.840
INS1. Security0.91476.185%0.6710.819
IN12. Safety0.8540.7830.700
INS3. Prevention0.8490.6710.810
Core attributes (CA)0.942
CA1.Environment0.93985.324%0.8860.917
CA2. Onshore0.9360.8200.938
CA3. Marina0.9230.8840.918
CA4.Transportation0.8970.8620.925
Peripheral attributes (PA)0.899
PA1. Service0.92183.377%0.8160.843
PA2. Promotion0.9200.8140.846
PA3. Public security0.8980.7750.880
Table
Table 4. Logistic model estimation results of influencing factors of the WTP for yachting tourism under different preferences.
Table 4. Logistic model estimation results of influencing factors of the WTP for yachting tourism under different preferences.
VariablesModel I; (Population Sample)Model II (Prefer Motor Boat)Model III (Prefer Non-Motor Boat)
βSESig.βSESig.βSESig.
Age 0.463 *0.2560.070
Education0.356 **0.1550.022 0.651 ***0.2140.002
Income0.420 ***0.0820.0000.65 1 ***0.1340.000
Family Structure 3 1.200 *0.7340.100
AT0.302 ***0.0600.0000.245 **0.0980.0120.318 ***0.0860.000
PBC0.125 **0.0500.013
PE0.345 ***0.0770.000 0.627 ***0.1150.000
INS 0.112 **0.0550.042
CA0.182 ***0.0260.0000.287 ***0.0460.0000.161 ***0.0340.000
Sample size453189264
Cox and Snell R20.3780.4690.354
Nagelkerke R20.4260.5160.416
−2 Log Likelihood764.282326.673382.877
Sig.0.0000.0000.000
Note: *, ** and *** mean significant at 10%, 5% and 1% levels, respectively. Family structure 3 = married with minor children, and control group 4 = married with adult children. AT = Attitude, PBC = Perceived behavioral control, PE = Past experience, INS = Institution, CA = Core attributes.
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Yao, Y.; Zheng, R.; Parmak, M. Factors Influencing the Willingness to Pay in Yachting Tourism in the Context of COVID-19 Regular Prevention and Control: The Case of Dalian, China. Sustainability 2022, 14, 13132. https://doi.org/10.3390/su142013132

AMA Style

Yao Y, Zheng R, Parmak M. Factors Influencing the Willingness to Pay in Yachting Tourism in the Context of COVID-19 Regular Prevention and Control: The Case of Dalian, China. Sustainability. 2022; 14(20):13132. https://doi.org/10.3390/su142013132

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Yao, Yunhao, Ruoquan Zheng, and Merle Parmak. 2022. "Factors Influencing the Willingness to Pay in Yachting Tourism in the Context of COVID-19 Regular Prevention and Control: The Case of Dalian, China" Sustainability 14, no. 20: 13132. https://doi.org/10.3390/su142013132

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