Stakeholder Perceptions of Sustainable Tourism Development: A Case Study in Haikou, China

Abstract

The development of sustainable tourism has various stakeholders such as local residents, businesses, governments, visitors, travel agencies, and tourism companies. Tourism destinations need to be protected not only to ensure a better travel experience but also to ensure that they can be enjoyed in the future. This study explored the degree of influence of key stakeholders such as the government, travel agencies, local residents, and tourists on the development of sustainable tourism in Haikou, the capital city of the island province Hainan, China. This city is rich in tropical natural resources and offers unique opportunities for the development of tourism. In 2018, Haikou was selected as one of the first “International Wetland Cities” by the 13th United Nations Ramsar Convention. However, the high dependence on tourism and centralized consumption have caused several ecological and environmental problems in Haikou. An online questionnaire survey of 419 stakeholders was conducted, and factor analysis was used to identify five dimensions. The structural equation modeling method was used to explore the degree of influence of different relationships on sustainable tourism development in Haikou. The results indicated that key stakeholders are most concerned about tourism awareness, ecological protection, and sociocultural development. Therefore, further efforts to promote and develop tourism must focus on ecological and environmental protection. Creating positive travel experiences and managing tourism wisely can meet the demands of today without compromising the future.

1. Introduction

As the social impact of the COVID-19 pandemic weakens, attention has returned to the connection between sustainable tourism and sustainable development [1]. The 76th session of the United Nations General Assembly included the discussion “High-Level Thematic Debate on Sustainable Tourism”, which was focused on promoting a positive transformation of sustainable tourism by considering its impact on people, culture, and the economy. It acknowledged its benefits for human wellbeing, economic prosperity, and sustainable development and considered the vital role of residents in tourism [1,2].

Tourism is an important economic sector that has been experiencing rapid growth worldwide. However, its quick growth has also led to environmental and social consequences in numerous areas [3]. The term “sustainable tourism” first emerged in the 1980s as awareness grew over the negative impacts of tourism activities [4]. Sustainable tourism has been associated with preserving ecosystems and biodiversity while promoting human welfare and cultural equity [5,6,7,8]. Efforts at sustainable tourism were originally focused on nature-based and alternative forms of tourism, and the concept of sustainable tourism has gained popularity as stakeholders seek to achieve a balance between meeting the needs of tourists, enhancing economic growth, protecting physical locations, improving the quality of life for local communities, and preserving the environment for future opportunities [9]. However, the scope of sustainable tourism has not been clearly defined, especially its practices and effectiveness [10,11,12]. Amerta et al. [13] characterized sustainable tourism as reducing the excessive use of natural resources, involving local communities in the development of tourism areas, providing economic benefits to local communities, maintaining biodiversity, not exploiting the natural environment, ensuring natural resources will be available for future generations, coordinating with relevant stakeholders in tourism development, and training local people to be skilled and professional. Public engagement regarding environmental and social impacts is important for increasing the perception of stakeholders of sustainable tourism [14].

Tourism contributes to economic growth by providing access to an international market. Lordkipanidze et al. [15] presented a strength–weaknesses–opportunities–threats (SWOT) analysis showing the need for entrepreneurship to be actively involved in the development of sustainable tourism. Tsaur et al. [16] analyzed the linkages and sustainability between natural resources, communities, and tourism in sustainable ecotourism and used the Delphi method to identify four types of evaluation indicators: pressure on environmental receptors, spatial scale, environmental media (e.g., air, water, and land), and stability. McIntosh and Zahra [17] conducted a qualitative study using deep interviews, diaries, and participation watches to explore volunteer tourism as an alternative to sustainable experiences, and they concluded that cultural interactions and experiences are mutually beneficial. These previous studies have indicated that the tourism industry is moving toward green and ecological development in a flexible manner and exploring ways to manage people and nature in harmony. Sustainable tourism requires urban planning to re-establish the balance between people and nature and management support at travel destinations to promote the comprehensive and coordinated sustainable development of the economy, society, and environment.

Haikou is the capital city of Hainan, which is an island province of China rich in tropical natural resources with unique opportunities for tourism development. Haikou is located in the north of Hainan Island (Figure 1) and has a laidback atmosphere. It is the political, economic, cultural, and technological center of the province [18]. It has a pleasant climate with mild, fogless winters. The air, water quality, and ecological indicators are among the top in the country, and the city has an excellent living environment and a history and culture of national significance [18]. In 2018, Haikou was selected as one of the first “International Wetland Cities” by the 13th United Nations Ramsar Convention [19]. However, the high dependence on tourism and the centralized consumption have caused several ecological and environmental problems in Haikou [20]. According to the Haikou Municipal Government, the total tourism revenue of Haikou in 2019–2020 was impacted by the COVID-19 pandemic [21]. The accelerated construction of a Special Economic Zone in Haikou has emphasized the need to achieve high-quality sustainable development. A National Ecological Civilization Pilot Zone and International Tourism Consumption Center are being developed to encourage Haikou’s tourism industry to follow a sustainable development path and create an international sustainable tourism brand image for Hainan [22]. Since the situation of the COVID-19 pandemic has stabilized, Haikou has launched a series of tourism-themed activities, such as a night bazaar where tourists can shop for special and interesting products [23].

Although the number of tourists has slowly risen due to holiday effects and seasonal peak periods, Haikou’s tourism industry has not kept pace with the general increase in domestic consumption (Figure 2) [21]. At the societal level, Hainan suffers from unbalanced regional development. Although the province is rich in tourism resources, there is a gap between the number of tourists who visit the Haikou economic zone and other regions of the island. In addition, the number of visitors received was 16.5% lower in 2022 than in the previous year (Figure 3) [21]. Wang et al. [24] argued that administrative divisions have hindered the timely sharing of data resources among tourism departments.

The reduced number of tourists indicates uncertainty over the sustainable tourism development of Haikou between the economic zone and other regions. In addition, stakeholders may have differing perceptions regarding the relationship between tourism destination management and sustainable tourism development. Therefore, the purpose of this study was to explore the influences and relationships between different factors of tourism destination management and sustainable tourism. An exploratory analysis was conducted on the impact of relevant key stakeholders on sustainable tourism in Haikou using the structural equation modeling (SEM) method. The results can provide new ideas for potential development of a tourism consumer base, which in turn can be applied as a strategy for sustainable tourism development in Haikou. While many studies so far have focused on tourism destination management by focusing on theoretical analysis, this study investigated the factors affecting sustainable tourism as a basis for analysis, which were combined with empirical findings to develop suitable strategies or recommendations. This was to clarify the relationships among the stakeholders and identify their key areas of concern to ensure the sustainable tourism development of Haikou.

2. Materials and Methods

2.1. Sampling Approach

Gao et al. [25,26] reported that key stakeholders such as local governments often implement policies that hinder the development of local tourism. They divided tourism stakeholders into two main groups: those with internal interests and those with external interests. Stakeholders with internal interests include local residents, enterprises (e.g., souvenir shops and local products, tourism companies, and travel agencies), and communities. Stakeholders with external interests include local governments, state-owned tourism enterprises, businesses (e.g., guesthouse and hotel operators and retailers), experts and research institutions, tourists, pressure and lobby groups, the media, and entertainers [25,26]. Vrontis et al. [27] also classified the various stakeholders in sustainable tourism development as internal or external.

In the present study, four key groups of stakeholders were identified for the sustainable tourism development of Haikou (Figure 4): tourists, the government, travel agencies, and local residents. Tourists are the dominant consumers, so the number of visitors is an important indicator of the success of tourism activities, and attracting and maintaining their interest is key to sustainable tourism development. Travel agencies directly create benefits for local scenic spots or tourism activities. The government has the important role of promoting cooperation and connecting relevant stakeholders. Finally, local residents are both the main beneficiaries and most affected by tourism activities.

Yamane, T.’s [28] formula was used to estimate a suitable sample size:

$$n={\displaystyle \frac{N}{1+N{\left(e\right)}^2}}$$

(1)

where n is the sample size, N is the total target population (i.e., the population of Haikou City), e is the margin of error at 5% (confidence level of 95%), and 1 is a constant. Thus, the suitable sample size was estimated as 399.66, which was rounded up to 400. This is consistent with the recommended sample size of 100–400 for SEM studies [29].

This study was primarily exploratory, and data were collected through a semi-structured questionnaire using a five-point Likert scale. The final version of the questionnaire was distributed online to tourists, the government, travel agencies, and local residents on the Questionnaire Star website. The samples were from respondents from Haikou. The probability proportionate to size sampling technique was used to improve the scientific reliability and representativeness of the results and to create an equal probability of selection [30]. The survey data were collected over a period of 3 months. Survey distribution and data collection were conducted online to avoid the geographic problems caused by COVID-19 and to reduce costs. Overall, 426 questionnaires were obtained. Questionnaire Star software was used to screen out invalid questionnaires with identical or incomplete answers. The final number of valid questionnaires was 419 for a recovery rate of 98%, which met the sample size requirements of the study. Respondents who filled out the questionnaires received some small online reward (e.g., coupons) to encourage their participation and increase the response rate.

2.2. Validity of Interview Questions

The soundness of the content and structure of the questionnaire was evaluated by online interviews conducted via email with three tourism experts or government managers related to key tourism activity areas. An item objective congruence (IOC) analysis was performed using the interview results to check the consistent and important influencing factors of the questionnaire.

2.3. Reliability and Validity Analysis

Reliability and validity are both interrelated and distinct. Reliability analysis involves testing for the correlation and consistency among all items for each dimension of the scale. The Cronbach’s alpha (α) coefficient is commonly used to evaluate reliability [31]. Validity analysis involves assessing the rationality of the questionnaire design. The model scale and structure were modified and adjusted according to pretest data, and the reliability and validity of the final questionnaire were determined and checked. The Kaiser–Meyer–Olkin (KMO) test and Bartlett’s spherical test were used to determine whether factor analysis could be performed. A KMO value of greater than 0.6 generally indicates that a questionnaire has good structural validity for analysis. A p-value of 0.000 indicated the significance level and contribution of factors to explaining variables tested by the total variance interpretation analysis [32].

2.4. Structural Equation Modeling Analysis

SEM is a method that combines statistical techniques with factor analysis in social science research. The reliability and validity are more accurate, and the research is more scientific [33]. SEM tests whether the path relation of each factor in the questionnaire is valid or not by establishing the path relation of each factor. Path analysis is a method for studying multi-level causal relationships between variables and the strength of their correlations. Its main purpose consists in checking the precision and reliable validity of a model of hypothesis and measuring the intensity of the relationship between parameters [34]. In total, 419 responses to the questionnaire were obtained, which was concluded to be sufficient for SEM.

2.5. Indicator Development

Sustainable tourism and its indicators in tourism development contribute to economic growth due to the rapid international market, and Lordkipanidze et al. [15] have outlined the need for entrepreneurship to also be actively involved in sustainable tourism development through the results of a SWOT analysis. However, while most sustainable tourism development emphasizes the importance of community collaboration, Sharpley [35] showed that it is also important for tourism to achieve equitable development. To provide opportunities for all relevant stakeholders to access and use the abundant resources, the development of sustainable tourism is necessarily guided by the principles of ecological, economic, and social aspects.

White et al. [36] showed that the tourism environment and the carrying capacity are the balance principles to achieve sustainable development. They also identified indicators that respond directly to sustainability objectives but did not address interrelationships, such as the direct impact of sustainable tourism on the spiritual quality of the environment, social–cultural atmosphere, and the economy. Tsaur et al. [16] analyzed the linkages and sustainability between natural resources, communities, and tourism in sustainable ecotourism using thematic steps and used the Delphi method to identify indicators for the evaluation of tourism sites in four groups: The first group is indicators of pressure on environmental receptors. The second group is the spatial scale. The third group is environmental media, such as air, water, and land. The fourth group is a classification of indicators based on key aspects of stability, including environment, business, and society.

McIntosh and Zahra [17] conducted a qualitative study using deep interviews, diaries, and participation watches to explore volunteer tourism as an alternative to sustainable experiences, concluding that cultural interactions and experiences are mutually beneficial. A review and analysis of studies related to sustainable tourism reveal that most of the quantitative methods studied are the analysis of the influence relationship between two or more topics. For example, lagged models are developed, and then the relationship between hypothetical excessive tourism and residents is tested by regression analysis. Others used quantitative structured questionnaires to analyze the interdependence of artificial and natural assets. Alternatively, the relationship between resources, communities, and tourism in ecotourism and sustainability can be explored using the Delphi method. Sustainability tourism framework systems and other studies have indicated that tourism is developing with resilience in a green and ecological direction, exploring ways to manage people and nature in harmony.

Indicators were developed based on dimensions and factors extracted from the above-mentioned previous studies in respect of sustainable tourism development. In total, the questionnaire comprised 19 factors encompassing five dimensions: (1) economic development, (2) sociocultural development, (3) awareness of sustainability, (4) tourism development experience, and (5) tourism public infrastructure (

Table 1. Factors in the questionnaire used to evaluate sustainable tourism development.

Dimension	Label	Factor	Notes	Reference
Economic Development	ED1	Tourism product development	Develop a market for tourism and local products.	[38]
	ED2	Household income	Improve livelihoods.
	ED3	Ticket prices for scenic spots	Adjust ticketing and pricing in peak seasons as a reflection of efforts at modernization and innovation.
Sociocultural Development	SCD1	Community management	Establish a committee to respect the local community while improving the visitor experience.	[36]
	SCD2	Cultural heritage protection	Effectively protect local culture and heritage.
	SCD3	Holiday travel	Guide local residents to participate in festive tourism such as the Dragon Boat Festival.
	SCD4	Intelligent tourism service system	Develop intelligent services such as a platform for processing complaints.
Sustainability Awareness	SA1	Environmental awareness	Cultivate awareness of the need to protect local wildlife resources.	[39,40]
	SA2	Volunteer work	Encourage volunteer work to protect the environment.
	SA3	Green tourism products	Use ecotourism products such as promoting cycling experiences.
Tourism Development Experience	TDE1	Talent cultivation	Encourage the training and education of talented staff and improve the stability of employment and income-generating opportunities.	[39,41,42] and IOC results
	TDE2	Medical and transportation systems	Improve medical and transportation systems for improved quality of life.
	TDE3	Resident participation	Involve local residents and communities in tourism management to ensure a fair distribution of socioeconomic benefits and protect their environment.
	TDE4	Tourism uniqueness	Good tourism products, food, and unique events and festivals attract tourists to spend money.
	TDE5	Tourist atmosphere	Preserve the unique traditional culture and beautiful scenic environment to attract visitors and ensure they have a fulfilling experience.
	TDE6	New mode of Internet travel	A high-dimensional, all-round development of new tourism methods, the digital development model of “Internet + Tourism”.
Tourism Public Infrastructure	TPI1	Tourism infrastructure improvement	Construct and develop local infrastructure such as road traffic systems.	[41,43]
	TPI2	Ecofriendly tourism infrastructure	Adopt ecofriendly techniques to reduce consumption.
	TPI3	Appearance of tourism infrastructure	Use friendly and humanized designs to increase the appeal of tourism infrastructure.

). The questionnaire was semi structured, and respondents were asked to evaluate each factor on a five-point Likert scale. An item objective congruence (IOC) analysis was performed by three experts to check the validity of the questionnaire contents before data collection. The experts gave the questionnaire an average IOC index score of 0.50 or higher, which indicated that the factors were valid [37]. The experts also confirmed that the questionnaire was complete, comprehensive, and objective. They suggested including an additional factor called “New mode of Internet travel”, which was given the label TDE6.

2.6. Statistical Analysis Methods

The statistical analysis of the collected data was performed by using the software SPSS22.0 and AMOS24.0.

Confirmatory factor analysis (CFA) was performed on the responses to the questionnaire to evaluate whether the correspondence between dimensions and their factors was consistent with their theoretical relationships as designed by the researcher [44].

3. Results and Discussion

In this part, the basic personal information characteristics (gender, age, education, and occupation) of a total of 419 respondents were statistically analyzed using the frequency analysis method. Of the 419 respondents representing relevant stakeholders in Haikou, 10 were government employees, 12 were travel agency employees, 172 were local residents, and 225 were tourists (Figure 5). The tourists made up the largest group. The majority of respondents in Haikou were male by gender, with 220 males (52.50%) and 199 females (47.49%). The age distribution of respondents was concentrated between “30–39 years old” (38.66%) and “20–29” years old (33.17%), which indicates that the age of the survey respondents in Haikou was a bit younger, mainly young and middle-aged.

For education backgrounds, more than 50% of the respondents in Haikou were “Undergraduate” (63.2%) in terms of their education level. This indicates that the respondents generally have a good knowledge of their education level and showed a trend of high education. It means that the level of education and literacy may have an impact on sustainable tourism, such as enhancing the motivation of tourists to participate in tourism, reflecting the interaction between the tourism market and tourists [45].

The CFA results were used to evaluate whether the 19 factors in the questionnaire could reasonably explain their associated dimensions (

Table 2. Confirmatory factor analysis results.

Dimension	Factor	p	Std. Estimate	CR	AVE
Economic development	ED 1	-	0.855	0.84	0.643
	ED 2	0.000 ***	0.779
	ED 3	0.000 ***	0.739
Sociocultural development	SCD 1	-	0.817	0.876	0.640
	SCD 2	0.000 ***	0.829
	SCD 3	0.000 ***	0.751
	SCD 4	0.000 ***	0.796
Sustainability awareness	SA 1	-	0.872	0.89	0.731
	SA 2	0.000 ***	0.840
	SA 3	0.000 ***	0.850
Tourism development experience	TDE 1	-	0.808	0.911	0.632
	TDE 2	0.000 ***	0.791
	TDE 3	0.000 ***	0.779
	TDE 4	0.000 ***	0.796
	TDE 5	0.000 ***	0.8
	TDE 6	0.000 ***	0.795
Tourism public infrastructure	TPI 1	-	0.809	0.847	0.649
	TPI 2	0.000 ***	0.816
	TPI 3	0.000 ***	0.790

Note: *** represents 1% significance level. Data source: authors’ calculation based on the questionnaire results.

,

Table 3. Discriminant validity test analysis results.

(CFA) Discriminant Validity: Pearson Correlation vs. AVE Square Root Value
	ED	SCD	SA	TDE	TPI
ED	0.802
SCD	0.437	0.8
SA	0.285	0.353	0.855
TDE	0.504	0.76	0.385	0.795
TPI	0.458	0.583	0.333	0.613	0.806

Note: Diagonal blue numbers are AVE square root values.

and Table 4). SEM analysis was conducted to explore the degree of influence of the factors (Table 5). The results showed that some factors had a significant effect on sustainable tourism development in Haikou, particularly those in the three dimensions of sustainability awareness, tourism development experience, and tourism public infrastructure (Table 6 and Table 7). The relationships between all factors of a given dimension were found to be significant (Figure 6). All dimensions in the model had significant impacts according to the p-value, which indicated that all paths are valid. Specifically, the dimension of sociocultural development was found to have a strongly positive influence on sustainable tourism development. The strongest positive influence was found between the dimensions of sociocultural development and tourism development experience with an impact coefficient of 0.770 ***.

For the analysis of the discriminant validity, correlation tests were performed based on the mean values between the factors. According to the results, the AVE values are greater than the maximum value of the absolute value of the correlation coefficients among the factors, which means that each dimension has good discriminant validity. For example, for the economic development dimension, the AVE square root value was 0.802, which was greater than the maximum value of the absolute coefficient of correlation between the other factors in this column, which means that the economic development dimension has good discriminant validity. Therefore, the results of the validity analysis indicate that the five design dimensions also provided a good overview of the influencing factors of each factor, and the data passed the CFA test requirements.

Table 4. Model fit test results of CFA.

Common Indicators	χ2/df	GFI	RMSEA	RMR	CFI	NFI	TLI (NNFI)
Judgment criteria	<3	>0.9	<0.10	<0.05	>0.9	>0.9	>0.9
Output values	1.340	0.962	0.029	0.044	0.990	0.962	0.988
Test results	√	√	√	√	√	√	√

Note: √ means the indicator passes the test.

Table 4. Model fit test results of CFA.

Common Indicators	χ2/df	GFI	RMSEA	RMR	CFI	NFI	TLI (NNFI)
Judgment criteria	<3	>0.9	<0.10	<0.05	>0.9	>0.9	>0.9
Output values	1.340	0.962	0.029	0.044	0.990	0.962	0.988
Test results	√	√	√	√	√	√	√

Note: √ means the indicator passes the test.

A model fit validity situation analysis was performed. The data of basic common indicators all met the judging criteria.

Table 5. Model path relationship/SEM test results.

Impact Path		Non-Standardized Coefficients		S.E.	C.R. (z)	p	Standardized Coefficients (β)	Results
ED	→	SA	0.169	0.065	2.600	0.009 ***	0.164	Valid
ED	→	TDE	0.157	0.036	4.411	0.000 ***	0.188
ED	→	TPI	0.227	0.049	4.596	0.000 ***	0.252
SCD	→	SA	0.392	0.072	5.423	0.000 ***	0.339
SCD	→	TDE	0.723	0.052	13.954	0.000 ***	0.770
SCD	→	TPI	0.585	0.059	9.867	0.000 ***	0.581
ED	→	ED 1	1	-	-	-	0.852	Valid
	→	ED 2	0.753	0.046	16.282	0.000 ***	0.782
	→	ED 3	0.711	0.046	15.431	0.000 ***	0.738
SCD	→	SCD 1	1	-	-	-	0.809	Valid
	→	SCD 2	0.966	0.05	19.136	0.000 ***	0.831
	→	SCD 3	0.853	0.051	16.678	0.000 ***	0.749
	→	SCD 4	0.91	0.051	17.893	0.000 ***	0.790
SA	→	SA 1	1	-	-	-	0.872	Valid
	→	SA 2	0.916	0.045	20.535	0.000 ***	0.839
	→	SA 3	0.906	0.043	20.855	0.000 ***	0.851
TDE	→	TDE 1	1	-	-	-	0.805	Valid
	→	TDE 2	0.904	0.05	18.148	0.000 ***	0.790
	→	TDE 3	0.888	0.05	17.790	0.000 ***	0.778
	→	TDE 4	0.911	0.05	18.395	0.000 ***	0.798
	→	TDE 5	0.921	0.05	18.520	0.000 ***	0.802
	→	TDE 6	0.91	0.05	18.302	0.000 ***	0.795
TPI	→	TPI 1	1	-	-	-	0.811	Valid
	→	TPI 2	0.925	0.054	17.195	0.000 ***	0.812
	→	TPI 3	0.851	0.051	16.769	0.000 ***	0.792

Note: → indicates the influence relationship; *** represents 1% (p < 0.01). Data source: authors’ calculation based on the questionnaire results using AMOS.

Table 5. Model path relationship/SEM test results.

Impact Path		Non-Standardized Coefficients		S.E.	C.R. (z)	p	Standardized Coefficients (β)	Results
ED	→	SA	0.169	0.065	2.600	0.009 ***	0.164	Valid
ED	→	TDE	0.157	0.036	4.411	0.000 ***	0.188
ED	→	TPI	0.227	0.049	4.596	0.000 ***	0.252
SCD	→	SA	0.392	0.072	5.423	0.000 ***	0.339
SCD	→	TDE	0.723	0.052	13.954	0.000 ***	0.770
SCD	→	TPI	0.585	0.059	9.867	0.000 ***	0.581
ED	→	ED 1	1	-	-	-	0.852	Valid
	→	ED 2	0.753	0.046	16.282	0.000 ***	0.782
	→	ED 3	0.711	0.046	15.431	0.000 ***	0.738
SCD	→	SCD 1	1	-	-	-	0.809	Valid
	→	SCD 2	0.966	0.05	19.136	0.000 ***	0.831
	→	SCD 3	0.853	0.051	16.678	0.000 ***	0.749
	→	SCD 4	0.91	0.051	17.893	0.000 ***	0.790
SA	→	SA 1	1	-	-	-	0.872	Valid
	→	SA 2	0.916	0.045	20.535	0.000 ***	0.839
	→	SA 3	0.906	0.043	20.855	0.000 ***	0.851
TDE	→	TDE 1	1	-	-	-	0.805	Valid
	→	TDE 2	0.904	0.05	18.148	0.000 ***	0.790
	→	TDE 3	0.888	0.05	17.790	0.000 ***	0.778
	→	TDE 4	0.911	0.05	18.395	0.000 ***	0.798
	→	TDE 5	0.921	0.05	18.520	0.000 ***	0.802
	→	TDE 6	0.91	0.05	18.302	0.000 ***	0.795
TPI	→	TPI 1	1	-	-	-	0.811	Valid
	→	TPI 2	0.925	0.054	17.195	0.000 ***	0.812
	→	TPI 3	0.851	0.051	16.769	0.000 ***	0.792

Note: → indicates the influence relationship; *** represents 1% (p < 0.01). Data source: authors’ calculation based on the questionnaire results using AMOS.

Overall, as can be seen from Table 5: Based on the test results, significance was shown at the level of the p-value for each factor of each dimension (significance p-value of 0.000 *** < 0.01). Standardized coefficients (β) are greater than 0.4. The significance p-value of 0.000 *** indicated high significance, which means that all 19 factors of the five dimensions in this study have passed the model path relation test and proved to be effective.

The data of basic common indicators χ²/df, GFI, RMSEA, and CFI were tested to verify the fitness of the model. As shown in Table 6, the data of χ²/df < 3 (=1.407), GFI > 0.9 (=0.960), RMSEA < 0.10 (=0.031), and so on met the determination criteria. The results of the software data analysis test indicated that the model of this design fits well, and the model had high reliability and passed the test requirements. Taken together, this indicated that the hypotheses for each dimensional factor were valid and significant. Therefore, based on the results of the above data validation analysis, the following final model coefficient analysis graph was obtained (Figure 6).

Table 6. Model fit test results of SEM.

Common Indicators	χ2/df	GFI	RMSEA	RMR	CFI	NFI	TLI (NNFI)
Judgment criteria	<3	>0.9	<0.10	<0.05	>0.9	>0.9	>0.9
Output values	1.407	0.960	0.031	0.332	0.988	0.960	0.986
Test results	√	√	√	√	√	√	√

Note: √ means the indicator passes the test.

Table 6. Model fit test results of SEM.

Common Indicators	χ2/df	GFI	RMSEA	RMR	CFI	NFI	TLI (NNFI)
Judgment criteria	<3	>0.9	<0.10	<0.05	>0.9	>0.9	>0.9
Output values	1.407	0.960	0.031	0.332	0.988	0.960	0.986
Test results	√	√	√	√	√	√	√

Note: √ means the indicator passes the test.

Table 7. Model fit R² summary results.

Model Fit R2 Summary Results
Item	R2
Factor3 (SA)	0.197
Factor4 (TDE)	0.774
Factor5 (TPI)	0.548
TPI3	0.627
SA3	0.724
SA2	0.704
SA1	0.760
SCD4	0.624
SCD3	0.560
SCD2	0.691
SCD1	0.654
TPI2	0.660
ED3	0.545
ED2	0.611
ED1	0.725
TPI1	0.658
TDE6	0.632
TDE5	0.643
TDE4	0.637
TDE3	0.606
TDE2	0.624
TDE1	0.648

Table 7. Model fit R² summary results.

Model Fit R2 Summary Results
Item	R2
Factor3 (SA)	0.197
Factor4 (TDE)	0.774
Factor5 (TPI)	0.548
TPI3	0.627
SA3	0.724
SA2	0.704
SA1	0.760
SCD4	0.624
SCD3	0.560
SCD2	0.691
SCD1	0.654
TPI2	0.660
ED3	0.545
ED2	0.611
ED1	0.725
TPI1	0.658
TDE6	0.632
TDE5	0.643
TDE4	0.637
TDE3	0.606
TDE2	0.624
TDE1	0.648

The results confirmed the importance of sustainable tourism as a means of preserving and promoting traditional culture and that sociocultural development is a crucial factor. They suggest that cultural details and intelligent service systems can enhance the tourism experience. These findings are consistent with previous research on the relationship between sociocultural development and sustainable tourism [36]. The results also emphasize the need to be aware of sociocultural development for tourism public infrastructure with an impact coefficient of 0.581 *** as well as the importance of community management, intelligent service systems, and government coordination and control for sustainable tourism development.

The key stakeholders had relatively consistent levels of concern and endorsement of sustainability awareness, tourism development experience, and tourism public infrastructure. The highest level of concern was for sustainability awareness (SA1) with a score of 0.872, followed closely by tourism product development (ED1) with a score of 0.852. Economic development and sociocultural development showed the most fluctuation among the stakeholders.

From Table 5 of the model path coefficients, according to the significance test analysis (p-value) to test whether there is an impact relationship between the model dimensions and to test the hypothesis: (1) The hypothesis of the economic development dimension H1a (ED→SA) had an impact coefficient of 0.164 with a significant p-value of 0.009 *** (p < 0.01). H1b (ED→TDE) had an impact coefficient of 0.188 with a significant p-value of 0.000 *** (p < 0.01). H1c (ED→TPI) had an impact coefficient was 0.252 with a significant p-value of 0.000 *** (p < 0.01). The total indicated that this dimension presented significance at the p-value level, so this path was valid, indicating that the H1 hypothesis passed the test and was confirmed, proving that the H1 hypothesis was established.

(2) The hypothesized impact coefficient of H2a (SCD→SA) for the social and cultural development dimension was 0.339 with a significant p-value of 0.000 *** (p < 0.01). The impact coefficient of H2b (SCD→TDE) was 0.770 with a significant p-value of 0.000 *** (p < 0.01). The impact coefficient of H2c (SCD→TPI) was 0.581 with a significant p-value of 0.000 *** (p < 0.01). The total indicated that this dimension presented significance at the p-value level, so this path was valid, indicating that the H2 hypothesis passed the test and was confirmed, proving that the H2 hypothesis was established.

According to the results of SEM, it was found that the ED1 tourism product development factor in the economic development dimension has the greatest influence on tourism destination management with a significance value of 0.852, surpassing SCD1 community management (significance value of 0.809) and SCD2 cultural heritage preservation (significance value of 0.831) in the social and cultural development dimension in promoting tourism destination management in Haikou. The influencing factors of tourism destination management are ranked according to the SEM results, as shown in Figure 7.

Previous studies have recommended focusing on tourism destination marketing strategies to achieve a systematic cycle of sustainable tourism development, which involves creating distinctive tourism-related products and relying on distinctive ecotourism branding to enhance competitiveness [46]. Hall [47] encouraged the government to improve local infrastructure to both encourage tourism and accommodate its growth [48].

Ultimately, based on the results of the SEM analysis, the relationship between the economic development of tourism destination management and sustainable tourism has a positive impact. As with the previous study findings, the economic development level encourages external infrastructure investment efforts; increases tourism and local product market development, such as cooperation with neighboring communications and other smart businesses; provides new tourism income sources for residents; promotes economic activity and growth in neighboring and remote poor areas; increases employment opportunities; and promotes economic diversification.

There is a positive impact relationship between sociocultural development and sustainable tourism. As with the previous study findings, the social and cultural development level provides an efficient, satisfying, and valuable visitor experience for tourists, respecting local communities, which can increase mutual understanding between tourists and residents, thus improving the quality of services in tourist communities. Active participation of relevant stakeholders in tourism decision making helps to promote gender equality and equitable development [36]. To better provide more comprehensive and comfortable services for tourists, tourism enterprises and related departments need to provide interrelated, interactive, and intelligent social service systems. Spatially, the tourism economy territorial complex drives social drivers [47].

Future Suggestions and Limitations

Due to the influence of factors such as the COVID-19 pandemic, this study can still make improvements in supplementing and summarizing previous studies, expand the direction of attention to subdivision of sustainable tourism on this basis, and focus on the importance of tourism destination management on sustainable tourism development. This study is more about the horizontal relationship between Haikou tourism destination management and sustainable tourism development, and future research can also be enriched to explore the role of different tourism infrastructure developments in Hainan and so on.

To promote sustainable tourism, the various stakeholders can take the following actions:

• Local residents: To mitigate overexploitation of limited natural resources, local residents should explore new directions of thinking and adjust the overall environmental impact. They should also focus on promoting local cultural resources while enhancing the competitiveness of tourism brands for balanced economic and social development.
• Tourists: Tourists can increase environmental awareness by participating in green and sustainable tourism activities. This can help reduce consumption while encouraging other stakeholders to focus on sustainable tourism development.
• Travel agencies: Travel agencies can make scientific evaluations on the impact of sustainable tourism development to help other stakeholders make informed decisions. By considering the impact of their activities on the environment and local community, travel agencies can help with developing sustainable tourism products and services that meet the needs of tourists while ensuring long-term survival.
• Government: It is important for relevant government departments to become aware of the need for sustainable tourism development, which can help them realize the importance of strengthening cooperation, communication, and data and information sharing to develop policies and regulations that promote sustainable tourism development. This will help create a favorable environment for the tourism industry to thrive while also protecting the environment and local communities.

4. Conclusions

The results of this study confirmed the strong importance of environmental awareness (SA1) at promoting sustainable tourism development, which is consistent with previous studies. Improving environmental awareness requires encouraging environmental education, ecological support, and sustainable management. Environmental education is important for changing perceptions and behaviors to promote sustainable tourism development by enhancing people’s knowledge and skills about the environment [40]. Tourism product development (ED1) is important for broadening the market for tourism-related and local products, and an ecofriendly approach can reduce economic costs on both the supply and demand sides. Volunteer work (SA2) was shown to be an important criterion for assessing the efficiency and effectiveness of environmental education, which is consistent with the results of previous studies [40]. Green tourism products (SA3) such as cycling and other experiential ecotourism products were also found to be important, which is in line with previous studies [39].

In respect of the tourism market, in order to alleviate the enormous pressure of over-exploitation of limited natural tourism resources, new thinking directions need to be explored, the overall environmental impact must be adjusted, and the relationship between tourism destination management and sustainable tourism development impact should be explored. In addition to inheriting and propagating the local characteristic cultural resources, it also promotes the tourism brand competitiveness. For helping tourists in the process of consumption, the awareness of sustainable tourism projects in Hainan, attitude experience, and green and other consumption need to be enhanced to urge the relevant stakeholders of sustainable development.

In conclusion, based on the analysis of the above results, the influential relationship and important factors of tourism destination management and sustainable tourism were explored. Based on this investigation, it was found that tourism destination management positively influences sustainable tourism from economic development, sociocultural development, and conservation of the ecosystem in terms of the magnitude of influence, but there are differences in the degree of influence. Among them, sociocultural development positively influences the tourism development experience of sustainable tourism the most, followed by the concern for the positive impact on tourism public infrastructure. These findings differ from previous studies in that only ecosystem conservation has a significant negative impact on the tourism development experience of sustainable tourism in Haikou. Future research can also be enriched to explore the role of different tourism infrastructure development in Hainan and so on.