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
Yunhao Yao *, Ruoquan Zheng and Merle Parmak
College of Public Administration and Humanities, Dalian Maritime University, Dalian 116000, China
* Correspondence: yaoyunhao@dlmu.edu.cn
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.
Keywords: COVID-19; yachting tourism; willingness to pay
1. Introduction
Citation: 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
Academic Editor: Erwei Dong
Received: 12 August 2022
Accepted: 9 October 2022
Published: 13 October 2022
Publisher’s Note: MDPI stays neutral with regard to jurisdictional
claims in published maps and institutional affiliations.
Copyright: © 2022 by the author. Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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-onyear [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% yearon-year, of which 43.29% were tourists received by maritime tourism [6]. According to
Sustainability 2022, 14, 13132. https://doi.org/10.3390/su142013132
www.mdpi.com/journal/sustainability
Sustainability 2022, 14, 13132
2 of 18
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 [11–14].
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 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
Sustainability 2022, 14, 13132
3 of 18
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 depart-
ment 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
[32–35]. 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 [24,26,27,36–38]. 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, nonvolitional 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 [12,41–43].
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.
Sustainability 2022, 14, 13132
4 of 18
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 [46–48]. 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.
Figure 1. Theoretical framework of influencing factors on the WTP for yachting tourism consumption.
Sustainability 2022, 14, 13132
5 of 18
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:
Sustainability 2022, 14, 13132
6 of 18
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 [59–61]. 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 [62–64]. 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
Sustainability 2022, 14, 13132
7 of 18
= 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].
Table 1. The index design of the influencing factors as independent variables in the model.
Variables
Gender
Age
Demographic
variables
Education
Income
Family Structure
Value
Attitude (AT)
Psychological
variables
[67,68]
Subjective
Norm (SN)
Perceived Behavioral Control (PBC)
Behavioral variPast experiable
ence (PE)
[66,67,68,69,70]
Perceived
institutional
Institution
variables
(INS)
[52,71]
Meaning
1 = male, 2 = female
1 = under 24-years-old, 2 = 25–34-years-old, 3 = 35–44-years-old, 4 = 45–55years-old, 5 = over 55-years-old
1 = 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
above
1 = 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)
1 = unmarried, 2 = married without children, 3 = married with minor children, 4 = married with adult children
I like challenges and adventures.
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.
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.
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.
Variable
Types
Nominal
Ordinal
Ordinal
Ordinal
Nominal
Ordinal
Ordinal
Ordinal
Ordinal
The frequency of yachting tourism in the past: 1 = 0 times, 2 = once in many
Ordinal
years, 3 = once in 3 years, 4 = 1 once in a year, 5 = multiple times in a year.
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
Sustainability 2022, 14, 13132
8 of 18
CA1. The destination has a good natural environment, unique scenery and
high tourism value.
CA2. Onshore destinations are rich in culture, sports, entertainment, shopCore attributes
ping and other activities.
(CA)
Perceived
CA3. Basic service facilities of the marina are complete (water, electricity,
destination atsanitation, technical services, etc.).
tributes variaCA4. Developed destination tourism transportation system.
bles [37,55,72]
PA1. The service level of yachting tourism practitioners is high.
Peripheral at- PA2. The promotion of yachting tourism is strong.
tributes (PA) PA3. The destination is in good security.
PA4. Easy access to information on yachting tourism.
Ordinal
Ordinal
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 presurvey 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%.
Sustainability 2022, 14, 13132
9 of 18
(a)
(b)
(c)
Figure 2. (a) Dalian geographic location. (b) Xinghai Bay marina. (c) Donggang marina.
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 nonmotor 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.
Table 2. Basic information of tourists with different yacht preferences.
Prefer Motor
Boats
Items
Mean
SD
WTP
1.94
1.043
Age
2.12
0.906
Education
2.79
0.623
Income
2.71
1.435
Value
3.47
0.835
AT1. Interest
3.54
0.754
AT2. Fun
3.75
0.776
AT3. Meaningful 3.67
0.721
SN1. Family
2.77
0.943
SN2. Friends
2.84
0.932
SN3. Relatives
2.97
0.905
SN4. Colleagues 2.94
0.891
PBC1. Income
3.14
1.104
PBC2. Time
2.93
0.968
Prefer Non-Motor
Boats
Mean
SD
1.52
0.813
2.432
1.161
2.53
0.744
2.10
1.124
3.25
0.926
2.99
0.823
3.46
0.759
3.17
0.835
2.51
0.906
2.57
0.961
2.61
0.940
2.65
0.971
3.00
0.852
2.97
0.803
Items
PBC3. Ability
PE
INS1. Security
INS2. Safety
INS3. Prevention
CA1. Environment
CA2. Onshore
CA3. Marina
CA4.Transportation
PA1. Service
PA2. Promotion
PA3. Public security
PA4. Information
Prefer Motor
Boats
Mean
SD
3.05
0.993
3.60
1.375
2.46
1.008
2.62
0.975
2.85
0.952
3.17
1.253
3.06
1.151
3.11
1.224
3.11
1.239
2.90
1.135
2.94
1.163
3.16
1.170
2.77
0.945
Prefer Non-Motor
Boats
Mean
SD
2.98
0.827
2.43
1.329
2.49
1.013
2.72
0.848
2.82
0.778
3.16
1.325
2.95
1.175
3.15
1.321
3.16
1.355
2.75
1.125
2.68
1.070
2.98
1.216
2.82
0.815
Note: AT = Attitude, SN = Subjective norm, PBC = Perceived behavioral control, PE = Past experience, INS = Institution, CA = Core attributes, PA = Peripheral attributes.
Sustainability 2022, 14, 13132
10 of 18
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.
Table 3. Reliability and validity tests of questionnaires.
Items
Factor
Loading
Attitude (AT)
AT1. Interest
0.685
AT2. Fun
0.804
AT3. Meaningful
0.856
Perceived behavioral control (PBC)
PBC1. Income
0.763
PBC2. Time
0.818
PBC3. Ability
0.792
Subjective norm (SN)
SN1. Family
0.935
SN2. Friends
0.923
SN3. Relatives
0.896
SN4. Colleagues
0.882
Institution (INS)
INS1. Security
0.914
IN12. Safety
0.854
INS3. Prevention
0.849
Core attributes (CA)
CA1.Environment
0.939
CA2. Onshore
0.936
CA3. Marina
0.923
CA4.Transportation
0.897
Peripheral attributes (PA)
PA1. Service
0.921
PA2. Promotion
0.920
PA3. Public security
0.898
Cumulative Variance
Contribution Rate
Item-Total
Correlation
Alpha If Item
Deleted
61.596%
0.396
0.510
0.593
0.718
0.572
0.455
62.660%
0.485
0.553
0.520
0.651
0.565
0.609
82.696%
0.793
0.879
0.859
0.815
0.923
0.894
0.901
0.916
76.185%
0.671
0.783
0.671
0.819
0.700
0.810
85.324%
0.886
0.820
0.884
0.862
0.917
0.938
0.918
0.925
83.377%
0.816
0.814
0.775
0.843
0.846
0.880
Cronbach’s α
0.684
0.702
0.930
0.840
0.942
0.899
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
Sustainability 2022, 14, 13132
11 of 18
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.
Table 4. Logistic model estimation results of influencing factors of the WTP for yachting tourism
under different preferences.
Variables
Age
Education
Income
Family Structure 3
AT
PBC
PE
INS
CA
Sample size
Cox and Snell R2
Nagelkerke R2
−2 Log Likelihood
Sig.
Model Ⅰ (Population SamModel Ⅱ (Prefer Motor Boat)
ple)
β
SE
Sig.
β
SE
Sig.
0.463 *
0.256
0.070
0.356 **
0.155
0.022
0.420 ***
0.082
0.000
0.65 1***
0.134
0.000
1.200 *
0.734
0.100
0.302 ***
0.060
0.000
0.245 **
0.098
0.012
0.125 **
0.050
0.013
0.345 ***
0.077
0.000
0.182 ***
0.026
453
0.378
0.426
764.282
0.000
0.000
0.287 ***
0.046
189
0.469
0.516
326.673
0.000
0.000
Model Ⅲ (Prefer Non-Motor
Boat)
β
SE
Sig.
0.651 ***
0.214
0.002
0.318 ***
0.086
0.000
0.627 ***
0.112 **
0.161 ***
0.115
0.055
0.034
264
0.354
0.416
382.877
0.000
0.000
0.042
0.000
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.
(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
Sustainability 2022, 14, 13132
12 of 18
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].
Sustainability 2022, 14, 13132
13 of 18
(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,
Sustainability 2022, 14, 13132
14 of 18
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
Sustainability 2022, 14, 13132
15 of 18
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.
References
1.
2.
3.
China Tourism Academy (CTA). “The Annual Report on The Development of China’s Domestic Tourism 2021” Released—The
Beginning of the 14th Five-Year Plan, Marking a New Stage of High-Quality Development for Domestic Tourism. Available
online: https://baijiahao.baidu.com/s?id=1714035058988948225&wfr=spider&for=pc (accessed on 25 October 2021).
CCTV News Client. Accelerate the Restoration of Production and Life Order under the Conditions of Normalization of Epidemic
Prevention and Control [EB/OL]. Available online: http://www.ce.cn/xwzx/gnsz/gdxw/202003/28/t20200328_34572148.shtml (accessed on 28 March 2020).
China Cruise and Yacht Industry Association(CCYIA). China Yacht Industry Report in 2019–2020; China Cruise & Yacht Industry
Association: Beijing, Chin, 2020.
Sustainability 2022, 14, 13132
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
16 of 18
ICOMIA (International Council of Marine Industries Association). Recreational Boating Industry Statistics 2019. 2020. Available
online: http://www.icomia.org (accessed on 4 September 2021).
China Cruise and Yacht Industry Association (CCYIA). National Expert Committee on Yacht Development. Trends of Chinese Yacht
Industry; Internal Report; China Cruise and Yacht Industry Association (CCYIA): Beijing, China, 2021. (In Chinese)
Dalian Release. “Dalian Summer Tour” is on Fire! Data Release! Available online: http://mp.weixin.qq/s/peZxxkWATLf_aY2hooj6g (accessed on 20 September 2022).
Fu, G.C.; Chen, X.H. Analysis on safety management practice of yacht leasing and associated countermeasures. China Marit. Saf.
2022, 09, 38–39, 43. (In Chinese)
Chen, X.; Shi, Q.; Chen, W.X. Perception and attraction of yachting tourism from the Chinese tourist. Econ. Geogr. 2021, 41, 218–
224. (In Chinese)
Fishbein, M.; Ajzen, I. Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research Reading; Addison-Wesley:
Boston, MA, USA, 1975.
Ajzen, I. From intentions to actions: A theory of planned behavior. In Action Control; Springer: Berlin/Heidelberg, Germany,
1985; pp. 11–39.
Crina, P.D.; Florina, B. The use of smartphone for the search of touristic information: An application of the theory of planned
behavior. Econ. Comput. Econ. Cybern. Stud. Res. Acad. Econ. Stud. 2020, 54, 125–140. http://doi.org/10.24818/18423264/54.1.20.09.
Lam, T.; Hsu, C. Predicting behavioral intention of choosing a travel destination. Tour. Manag. 2006, 27, 589–599.
http://doi.org/10.1016/j.tourman.2005.02.003.
Meng, B.; Han, H. Investigating individual’ decision formation in working-holiday tourism: The role of sensation-seeking and
gender. J. Travel Tour. Mark. 2018, 35, 1–15. http://doi.org/10.1080/10548408.2017.1422455.
Qiu, H.L. Developing an extended theory of planned behavior model to predict outbound tourists’ civilization tourism in behavioral intention. Tourism Tribune 2017, 6, 75–85. (In Chinese)
Ajzen, I. The Theory of Planned Behavior. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211. http://doi.org/10.1016/07495978(91)90020-T.
Meng, B.; Choi, K. Extending the theory of planned behaviour: Testing the effects of authentic perception and environmental
concerns
on
the
slow-tourist
decision-making
process.
Curr.
Issues
Tour.
2016,
19,
1–17.
http://doi.org/10.1080/13683500.2015.1020773.
Liu, L.; Shi, X.Q. Research on the impact mechanism of sports tourism consumption behavior under the background of the
normalization of COVID-19 prevention and control: Empirical analysis of MOA-TAM integration model based on S-O-R framework. Tour. Trib. 2021, 36, 52–70. (In Chinese)
Jang, S.; Kim, J.; Kim, J.; Kim, S. Spatial and experimental analysis of peer-to-peer accommodation consumption during COVID19. J. Destin. Mark. Manag. 2021, 20, 100563. http://doi.org/10.1016/j.jdmm.2021.100563.
Tchetchik, A.; Kaplan, S.; Blass, V. Recycling and consumption reduction following the covid-19 lockdown: The effect of threat
and coping appraisal, past behavior and information. Resour. Conserv. Recycl. 2021, 167, 105370. http://doi.org/10.1016/j.resconrec.2020.105370.
Eurostat. Methodological Manual for Tourism Statistics. Version 3.1, 2014 ed.; European Union: Luxembourg, 2015.
Jafari, J. Encyclopedia of Tourism; Routledge: London, UK, 2001.
Alcover Casasnovas, A. Yachting Tourism. Encyclopedia of Tourism; Jafari, J., Xiao, H., Eds.; Springer International Publishing:
Cham, The Netherlands, 2016; pp. 1033–1034.
Luković, T. Nautical tourism-definition and dilemmas. Naše More Znan. Časopis Za More I Pomor. 2007, 54, 22–31.
https://www.bib.irb.hr/792299?lang=EN20&rad=792299.
Yao, Y.H.; Liu, Y.X.; Huang, L. Motivation-based segmentation of yachting tourists in China. Asia Pac. J. Tour. Res. 2021, 26, 245–
261. http://doi.org/10.1080/10941665.2020.1851274.
Sun, X.; Feng, X.; Gauri, D.K. The cruise industry in China: Efforts, progress and challenges. Int. J. Hosp. Manag. 2014, 42, 71–84.
http://doi.org/10.1016/j.ijhm.2014.05.009.
Paker, N.; Vural, C.A. Customer segmentation for marinas: Evaluating marinas as destinations. Tour. Manag. 2016, 56, 156–171.
http://doi.org/10.1016/j.tourman.2016.03.024.
Sariisik, M.; Turkay, O.; Akova, O. How to manage yacht tourism in Turkey: A swot analysis and related strategies. Procedia
Soc. Behav. Sci. 2011, 24, 1014–1025. https://doi.org/10.1016/j.sbspro.2011.09.041.
Chen, J.M.; Balomenou, C.K.; Nijkamp, P.; Poulaki, P. The sustainability of yachting tourism: A case study in Greece. Int. J. Tour.
Hosp. Res. 2016, 2, 42–49. http://doi.org/10.20431/2455-0043.0202005.
Diakomihalis, M.N.; Lagos, D.G. Estimation of the economic impacts of yachting in Greece via the tourism satellite account.
Tour. Econ. 2008, 14, 871–887. http://doi.org/10.1016/S0739-8859(07)21013-3.
Lee, H.C. Determinants of recreational boater expenditures on trips. Tour. Manag. 2001, 22, 659–667.
https://doi.org/10.1016/S0261-5177(01)00033-4.
Jackson,
E.L.
Leisure
constraints:
A
survey
of
past
research.
Leis.
Sci.
1988,
10,
203–215.
http://doi.org/10.1080/01490408809512190.
Sustainability 2022, 14, 13132
17 of 18
32. Burgin, S.; Hardiman, N. The direct physical, chemical and biotic impacts on Australian coastal waters due to recreational
boating. Biodivers. Conserv. 2011, 20, 683–701. http://doi.org/10.1007/s10531-011-0003-6.
33. Gedik, S.; Ertural, S.M. The effects of marine tourism on water pollution. Fresenius Environ. Bull. 2019, 28, 863–866.
34. Łapko, A.; Strulak-Wójcikiewicz, R.; Landowski, M.; Wieczorek, R. Management of waste collection from yachts and tall ships
from the perspective of sustainable water tourism. Sustainability 2018, 11, 121. http://doi.org/10.3390/su11010121.
35. Stoeckl, N.; Birtles, A.; Farr, M.; Mangott, A.; Curnock, M.; Valentine, P. Live-aboard dive boats in the great barrier reef: Regional
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
economic impact and the relative values of their target marine species. Tour. Econ. 2010, 16, 995–1018.
http://doi.org/10.5367/te.2010.0005.
Bizzarri, C.; Foresta, D.L. Yachting and pleasure crafts in relation to local development and expansion: Marina di Stabia case
study. Coast. Process. 2011, 149, 53–61. http://doi.org/10.2495/cp110051.
Dreizis, Y.; Potashova, I.; Ilin, I.; Kalinina, O. Yachting and coastal marine transport development in black sea coast of Russia.
MATEC Web Conf. 2018, 170, 5007. http://doi.org/10.1051/matecconf/201817005007.
Mikulić, J.; Krešić, D.; Kožić, I. Critical factors of the maritime yachting tourism experience: An impact-asymmetry analysis of
principal components. J. Travel Tour. Mark. 2015, 32, S30–S41. http://doi.org/10.1080/10548408.2014.981628.
Ajzen, I.; Fishbein, M. Understanding attitude and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall, 1980.
Ajzen, I. Nature and Operation of Attitudes. Annu. Rev. Psychol. 2001, 52, 27–58. http://doi.org/10.1146/annurev.psych.52.1.27.
Ajzen, I.; Joyce, N.; Sheikh, S.; Cote, N.G. Knowledge and the prediction of behavior: The role of information accuracy in the
theory of planned behavior. Basic Appl. Soc. Psychol. 2011, 33, 101–117. http://doi.org/10.1018/01973533.2011.568834.
Ajzen, I.; Madden, T.J. Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control. J. Exp. Soc.
Psychol. 1986, 22, 453–474. http://doi.org/10.1016/0022-1031(86)90045-4.
Conner, M.; Abraham, C. Conscientiousness and the theory of planned behavior: Towards a more complete model of the antecedents of intentions and behavior. Personal. Soc. Psychol. Bull. 2001, 27, 1547–1561. http://doi.org/10.1177/01461672012711014.
Fitri, R.; Karim, S.; Hera, O.; Heru Purboyo, H.P.; Arief, R. Applying knowledge, social concern and perceived risk in planned
behavior theory for tourism in the COVID-19 pandemic. Tour. Rev. 2021, 76, 809–828.
Kang, K.H.; Stein, L.; Heo, C.Y.; Lee, S. Consumers' willingness to pay for green initiatives of the hotel industry. Int. J. Hosp.
Manag. 2012, 31, 564–572. http://doi.org/10.1016/j.ijhm.2011.08.001.
Shuai, C.M.; Zhang, Y.K. Variance analysis of consumers’ willingness to pay for low-carbon products in China based on scenario
experiment with carbon labeling. China Soft Sci. 2013, 7, 61–70. (In Chinese)
Khan, S.U.; Liu, G.; Zhao, M.; Chien, H.; Misbahullah. Spatial prioritization of willingness to pay for ecosystem services. a novel
notion of distance from origin’s impression. Environ. Sci. Pollut. Res. 2020, 27, 1–13. http://doi.org/10.1007/s11356-019-06538-4.
Namkung, Y.; Jang, S. Are consumers willing to pay for Green Practices at Restaurant? J. Hosp. Tour. Res. 2017, 41, 329–356.
http://doi.org/10.1177/1096348014525632.
Kalish, S.; Nelson, P. A comparison of ranking, rating and reservation price measurement in conjoint analysis. Mark. Lett. 1991,
2, 327–336. http://doi.org/10.1007/bf00664219.
Li, Y.J.; Yang, Q. Empirical research on the audience WTP of Chinese professional soccer games and the influence factors. J.
Xi’an Educ. Univ. 2019, 36, 300–308. (In Chinese)
Breidert, C. Estimation of Willingness-to-Pay: Theory, Measurement, and Application; Wirtschaft Suniversitat Wien: Vienna, Austria,
2005.
Yao, Y.H.; Luan, W.X. Factors influencing yacht tourism consumption behavior based on the TAM-IDT Model. Tour. Trib. 2019,
34, 60–71. (In Chinese)
Qiu, J.W.; Zhang, Y.H.; Zha, A.P. An empirical study on the influencing factors of rural residents’ tourism consumption intention. Lanzhou Acad. J. 2011, 3, 57–64. (In Chinese)
Sherman, H.; Leach, T.C.; Rowley, D.J. Sabre yachts: A case study. Bus. Strategy Ser. 2008, 9, 249–271.
http://doi.org/10.1108/17515630810906765.
Yu, F.L.; Huang, Z.F.; Hou, B. Research progress and enlightenment on the relationship between values and tourism consumption behavior. Tour. Trib. 2017, 32, 117–126. (In Chinese)
Ma, J. A Comparative Study on Tourists’ Cross-Cultural Tourism Behavior; Dongbei University of Finance and Economics: Dalian,
China, 2011. (In Chinese)
Rohm, A.J.; Milne, G.R.; McDonald, M.A. A mixed method approach for developing market segmentation typologies in the
sports industry. J. Appl. Soc. Psychol. 2006, 28, 1429–1464.
Bagozzi, R.P.; Kimmel, S.K. A comparison of leading theories for the prediction of goal-directed behaviours. Br. J. Soc. Psychol.
1995, 34, 437–461. http://doi.org/10.1111/j.2044-8309.1995.tb01076.x.
Crompton, J.L. Motivations for pleasure vacation. Ann. Tour. Res. 1979, 6, 408–424. http://doi.org/10.1016/0160-7383(79)90004-5.
Kim, S.S.; Lee, C.K.; Klenosky, D.B. The influence of push and pull factors at Korean national parks. Tour. Manag. 2003, 24, 169–
180. http://doi.org/10.1080/10548408.2013.835679.
Phau, I.; Lee, S.; Quintal, V. An investigation of push and pull motivations of visitors to private parks: The case of Araluen
botanic park. J. Vacat. Mark. 2013, 19, 269–284. http://doi.org/10.1177/1356766712471232.
Sustainability 2022, 14, 13132
18 of 18
62. Buhalis, D.D. Marketing the competitive destination of the future. Tour. Trib. 2000, 21, 97–116. http://doi.org/10.1016/S02615177(99)00095-3.
63. Hernández-Lobato, L.; Solis-Radilla, M.M.; Moliner-Tena, M.A.; Sánchez-García, J. Tourism destination image, satisfaction and
loyalty: A study in Ixtapa-Zihuatanejo, Mexico. Tour. Geogr. 2006, 8, 343–358. http://doi.org/10.1080/14616680600922039.
64. Uysal, M.; Noe, F. Satisfaction in Outdoor Recreation and Tourism; In Cases in Tourism Marketing; Laws, E., Ed.; Continuum
Publishing: London, UK, 2003.
65. Li, B.K.; Zhao, B.; Liu, Y.; Guo, T.T. Investigation and analysis of aural residents’ willingness to pay for online consumption.
Manag. World 2018, 34, 94–103. (In Chinese)
66. Whitehead, J.C.; Wicker, P. Estimating willingness to pay for a cycling event using a willingness to travel approach. Tour. Manag.
2018, 65, 160–169. http://doi.org/10.1016/j.tourman.2017.09.023.
67. Al-Swidi, A.; Saleh, R.M. How green our future would be? An investigation of the determinants of green purchasing behavior
68.
69.
70.
71.
72.
73.
74.
75.
76.
77.
78.
79.
80.
81.
82.
83.
of young citizens in a developing country. Environ. Dev. Sustain. 2021, 23, 13436–13468. http://doi.org/10.1007/s10668-020-01220z.
Ohnmacht, T.; Husser, A.P.; Thao, V.T. Pointers to Interventions for Promoting COVID-19 Protective Measures in Tourism: A
Modelling Approach Using Domain-Specific Risk-Taking Scale, Theory of Planned Behaviour, and Health Belief Model. Frontier
in Psychology 2022, 13, 940090. http://doi.org/10.3389/fpsyg.2022.940090.
Tolkes, C.; Butzmann, E. Motivating Pro-Sustainable Behavior: The Potential of Green Events—A Case-Study from the Munich
Streetlife Festival. Sustainability 2018, 10, 3731. http://doi.org/10.3390/su10103731.
Javed, M.; Tuková, Z.; Jibril, A.B. The role of social media on tourists’ behavior: An empirical analysis of millennials from the
czech republic. Sustainability 2020, 12, 7735. http://doi.org/10.3390/su12187735.
Hsieh, P.J. Physicians' acceptance of electronic medical records exchange: An extension of the decomposed TPB model with institutional trust and perceived risk. Int. J. Med. Inform. 2015, 84, 1–14. http://doi.org/10.1016/j.ijmedinf.2014.08.008.
Zhang, Q.; Popa, A.; Sun, H.Z.; Guo, W.F.; Meng, F. Tourists’ Intention of Undertaking Environmentally Responsible Behavior
in National Forest Trails: A Comparative Study. Sustainability 2022, 14, 5542. http://doi.org/10.3390/su14095542.
Wu, M.L. SPSS Statistical Application Practice: Questionnaire Analysis and Applied Statistics; Science Press: Beijing, China, 2003; p.
24.
Nunnally, J.; Bernstein, I. Psychometric Theory; McGraw-Hill: New York, NY, USA, 1994.
Hair, J.F. Jr.; Anderson, R.E.; Tatham, R.L.; Black, W.C. Multivariate Data Analysis, 6th ed.; Prentice Hall: Upper Saddle River,
NJ, USA, 2002.
Payeras, M.; Jacob, M.; Alemany, M.; Garcia, M.A. The yachting charter tourism SWOT: A basic analysis to design marketing
strategies. Tour. Int. Multidiscip. J. Tour. 2011, 6, 111–134.
Mcintosh, A.J.; Thyne, M.A. Understanding tourist behavior using means–end chain theory. Ann. Tour. Res. 2005, 32, 259–262.
Watkins, L.; Gnoth, J. Japanese tourism values: A means- end investigation. J. Travel Res. 2010, 50, 654–668.
http://doi.org/10.1177/0047287510382297.
Dai, B. The Domestic Market Is Fully Recovering and the Tourism Economy Is Recovering. Available online:
http://travel.china.com.cn/txt/2021-04/09/content_77392124.html (accessed on 9 November 2021). (In Chinese)
Wang, E.P.; Gao, Z.F. Chinese consumer quality perception and preference if traditional sustainable rice produced by the integrated rice-fish system. Sustainability 2017, 9, 2282. http://doi.org/10.3390/su9122282.
Grubor, A.; Milicevic, N.; Djokic, N. Social-psychological determinants of Serbian tourists’ choice of green rural hotels. Sustainability 2019, 11, 6691. http://doi.org/10.3390/su11236691.
Juan, Y.X.; Kang, S.K.; Lee, C.; Choi, Y.J.; Reisinger, Y. Understanding views on war in dark tourism: A mixed-method approach.
J. Travel Tour. Mark. 2020, 37, 823–835. http://doi.org/10.1080/10548408.2020.1835789.
Sánchez-Caizares, S.M.; Cabeza-Ramírez, L.J.; Muoz-Fernández, G.; Fuentes-García, F.J. Impact of the perceived risk from
COVID-19 on intention to travel. Curr. Issues Tour. 2021, 24, 970–984. http://doi.org/10.1080/13683500.2020.1829571.