Next Article in Journal
Bioluminescence Inhibition Bioassay for Estimation of Snow Cover in Urbanised Areas within Boreal Forests of Krasnoyarsk City
Previous Article in Journal
Effect of Planting Ground Treatments Using Artificial Rainfall Slope Simulating Degraded Forestland on Drought Stress Susceptibility of Pinus densiflora
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Tourism Crisis Events Affecting Intention towards Forest-Based Health Tourism: A Structural Equation Model

Rattanakosin International College of Creative Entrepreneurship, Rajamangala University of Technology Rattanakosin, Nakhon Pathom 73170, Thailand
*
Author to whom correspondence should be addressed.
Forests 2024, 15(8), 1324; https://doi.org/10.3390/f15081324
Submission received: 19 June 2024 / Revised: 26 July 2024 / Accepted: 28 July 2024 / Published: 30 July 2024
(This article belongs to the Special Issue Forest Therapy and Human Health)

Abstract

:
Since the beginning of the 21st century, various tourism crisis events have negatively impacted the global tourism industry. This study proposes a research model grounded in the Stimulus–Organism–Response theory to explore how external stimuli influence individuals and help identify factors influencing elderly individuals’ willingness to participate in forest-based health tourism during and after tourism crisis events, considering the global aging trend. From 20 December 2023 to 15 January 2024, we collected 429 valid questionnaires from Chinese older adult participants engaged in forest-based health tourism in Guizhou Province. Structural equation modelling (SEM) and bootstrapping techniques were employed to analyze data. The results indicate that tourism crisis events, primarily in the form of geological disasters, are significant antecedent variables influencing the willingness of Chinese older adults to engage in forest-based health tourism. Furthermore, destination image and perceived value serve as individual mediators and function as chained mediators. The results enhance our understanding of the complex relationship between tourism crisis events and the willingness of older Chinese adults to travel while also revealing deeper underlying mechanisms.

1. Introduction

The global health tourism market reached USD 639 billion as early as 2017, with the Asia-Pacific region exhibiting significant growth potential [1]. The COVID-19 pandemic, on the one hand, reminds us to focus on healthcare needs and related services [2], and on the other hand, prompts people to reconsider their relationship with the natural environment [3]. As a result, nature-based health tourism, primarily focusing on forest environments, is becoming increasingly popular [3]. Against this backdrop, forest-based health tourism has gradually emerged as a novel perspective for tourism marketing and communication in the post-pandemic era. Forests are rich in negative oxygen ions and phytochemicals, crucial in the prevention and adjuvant treatment of mental and chronic non-communicable diseases [4,5,6]. Consequently, individuals urgently desire to reconnect with nature and immerse themselves in the high-quality forest environments of forest-based health tourism [7].
Moreover, the global economic recession has triggered concerns regarding the potential consequences of crisis events in tourism [8]. Evidently, the causes of tourism crisis events are diverse, encompassing social and economic factors. These crises, varying in type and scale, impact tourism. Forests, regarded as assemblies of biogeographical communities [9], render health tourism based on them particularly vulnerable to geological disasters. Some forms of geological disasters, such as landslides, debris flows, and earthquakes, not only cause damage to tourism infrastructure and irreparable impacts on tourism scenes and landscapes, but even result in severe injuries and deaths [10,11,12]. Current evidence suggests that human-induced disasters, such as terrorism, political instability, and public health security incidents, can hurt destination images [13,14,15]. Therefore, we can infer that geological disasters might damage a destination’s image in the short term. Since destination image ultimately influences tourists’ future behavior [16,17,18,19], the significant impact of geological disasters on destinations deserves more attention, as discussions on this topic are rare in tourism literature.
Guizhou Province, situated in the subtropical humid monsoon climate zone, is rich in forest resources and serves as a vital ecological barrier in the upper reaches of the Yangtze and Pearl Rivers in China. It offers unique advantages for developing forest-based health tourism, a sector that generated a total output of CNY 19.657 billion in 2021, according to the National Forestry and Grassland Administration and the National Park Administration of China [20,21,22,23,24,25]. Despite this potential, Guizhou’s location at the junction of the Eurasian and Indian Ocean tectonic plates makes it susceptible to geological disasters. This geographical vulnerability necessitates a deeper investigation into how increasing natural disasters influence travelers’ perceptions and behaviors—a factor crucial for devising effective restoration strategies in forest-based health tourism [26].
However, an increasing number of older adults have become one of the most significant groups in the tourism industry [27]. The global proportion of people aged 60 and above will double between 2015 and 2050, making them the fastest-growing consumer group [28]. According to the National Economic and Social Development Statistics Bulletin of China for 2023, by the end of 2023, the population aged 60 and above accounted for 21.1% of the total population [29]. By around 2050, the population aged 60 and above in China will likely reach 500 million, constituting more than one-third of the total population [30]. Therefore, against the backdrop of global population aging, focusing on the travel behavioral intentions of Chinese older adults as a consumer group is necessary, as it significantly impacts destination visitation and local income changes.
In addition, perceived value is becoming a key concern for destination marketers [31]. Perceived value is an essential factor for behavioral intentions, and there has been increasing research examining the relationship between destination image, perceived value, and behavioral intentions [32,33,34]. However, researchers have not investigated the relationship between geological disasters and these variables. Given the suddenness and unpredictability of geological disasters, we cannot ignore their impact on tourism behavioral intentions. Therefore, studying the impact of geological disasters on tourism behavioral intentions can help us better understand the impact mechanism of geological disasters on the tourism industry and provide targeted suggestions and countermeasures for the tourism industry and relevant decision-makers to respond to the challenges of geological disasters. Given the current development prospects of forest-based health tourism and the negative impact of geological disasters on destinations, studying how they affect the travel behavioral intentions of older adults is a timely and important endeavor.
Therefore, this study aims to explore how the paths of geological disasters as tourism crisis events affect older adults’ travel intentions within the context of forest-based health tourism. Furthermore, it investigates the chain mediation role of destination image and perceived value between the tourism crisis events and travel intentions. These findings contribute both theoretically and practically to the sustainable development of tourism following geological disasters.

2. Literature Review and Development of Hypotheses

2.1. Stimulus–Organism–Response (SOR) Theory

The Stimulus–Organism–Response (SOR) theory suggests that external stimuli can trigger changes in individuals’ cognition and emotions, leading to approach or avoidance behaviors [35]. Hence, it can be utilized to investigate the impact of external stimuli on individuals’ cognitive and emotional responses and further predict corresponding behaviors [36]. Liang et al. (2024) applied the SOR theory to reveal that live streaming in tourism (S) positively affects viewers’ flow experience and trust (O), ultimately promoting impulsive travel intentions (R) [37]. Wang & Lan (2021) employed the SOR theory to identify how consumers’ perception of COVID-19’s severity (S) triggers nostalgia (O), leading to an increased desire for leisure travel (R) [38]. The SOR theory is widely used in tourism literature to study visitor behavior [36,37,38,39]. Therefore, this study builds on the foundation of SOR theory. Our model considers tourism crisis events as antecedent variables that influence older adults’ intentions for forest-based health tourism. These events primarily act as external stimuli (S) and affect their images and perceived value (O) of destinations, which ultimately lead to behavioral intentions for forest-based health tourism (R).

2.2. Health Tourism and Forest-Based Health Tourism

As defined by Mueller and Kaufmann [40], health tourism encompasses all related phenomena of temporarily leaving one’s residence to seek health-promoting services. It primarily relies on health-related resources and focuses on health-centered experiences [41]. Its beneficial effects on individuals’ physical and mental health have been empirically demonstrated [42]. Consequently, the increasing participation in wellness tourism has enormous potential to emerge as a globally growing industry [41]. Forests positively promote health, with activities such as resting and exercising in forests reducing hypertension and stress symptoms [4,5,6]. Forests have a direct and robust relaxing effect [43], leading to forest-based health tourism, which utilizes forest resources for health-related purposes. Li & Wen (2022) pointed out that current research on forest-based health tourism is primarily limited to development strategies and health benefits [44], with limited studies exploring the influencing factors of forest-based health tourism intention [45]. However, forest-based health tourism has become an integral part of health tourism and an inherent demand for healthy living among urban residents [44]. Therefore, this study focuses on exploring strategies to drive individuals’ intention to participate in forest-based health tourism.

2.3. Tourism Crisis Events as Stimuli (S)

Events that negatively impact destinations are called crisis events in tourism, and they can have short-term or long-term effects on the tourism industry [46]. Duan et al. (2022) identify economic recessions/financial crises, oil/energy issues, political problems, health issues, natural/environmental disasters, and terrorism as examples of tourism crisis events [47]. These events disrupt tourists’ search for recovery and relaxation during travel, affecting tourist mobility. Som et al. (2015) state that tourism crisis events hurt tourists’ perception of the destination, damage the overall safety, attractiveness, and comfort reputation of the destination, and disrupt the continuity of local tourism businesses by reducing the number of tourists and spending [48]. Beirman (2018) defines a tourism crisis as “an event or set of circumstances that seriously damages the marketability and reputation of a tourist destination or tourism business”, from a corporate and regional perspective [49]. Geological disasters belong to one kind of tourism crisis event. The occurrence of geological disasters will not only destroy the destination’s infrastructure but also cause an irreparable impact on the tourism landscape [10,11,12] and ultimately hinder the flow of tourists into the destination tourism market, resulting in a severe economic impact. Primarily, when destination economies heavily rely on tourism-related activities, they demonstrate greater vulnerability, and, thus, destinations must maintain a positive image to attract tourists and continue to achieve success [50].
However, Jamal and Budke (2020) point out that humans often fail to learn from past crisis events or become indifferent to them once the crisis is over [51]. Therefore, rational strategic crisis management plans may be necessary to mitigate the negative impacts following these tourism crisis events [52]. This study describes tourism crisis events as stimuli to explain their impact on the intention of forest-based health tourism among older adults.

2.4. Destination Image and Perceived Value as Organism (O)

In the fiercely competitive tourism market, destination image plays a crucial role in destination development and marketing. The importance of a destination image stems from its impact not only on word-of-mouth recommendations from tourists after their visit [53] but also on the behavior of future tourists [16]. Consequently, creating a favorable destination image can achieve its competitive edge over other destinations [31]. However, the destination image is complex, multifaceted, and dynamic [54]. Cognitive image and affective image are crucial dimensions that influence destination image formation [55,56]. The cognitive image represents tourists’ knowledge or beliefs about a destination’s characteristics and attributes, while the affective image explains individuals’ emotional reactions and feelings towards the destination [57]. However, Afshardoost & Eshaghi (2020) pointed out that researchers favor the composite nature of destination images [56]. Li et al. (2021) believe that overall feelings and impressions form the psychological picture (image) of the destination [58]. Therefore, this study defines the destination image as an overall psychological image associated with tourists’ destinations, namely, in this case, the overall impression of Guizhou as a forest-based health tourism destination among older adults.
Li et al. (2018) currently assess the relationship between tourism crisis events and destination images, mainly focusing on a discussion stream related to security-related crises [13]. Political instability and terrorist risks hurt tourists’ destination images [14]. Media coverage negatively influenced American tourists’ destination images of China [15]. Hence, this study posits the following:
H1. 
Tourism crisis events negatively impact the image of forest-based health tourism destinations.
Perceived value, which is closely related to consumer behavior, is a predictor of behavioral intentions [59] and refers to consumers’ overall assessment of a product or service’s utility, determined by their perception of what they receive and give [60]. In tourism, perceived value links to the sacrifices tourists make, of things such as time, money, threats to security, and effort to achieve possible financial, social, and personal benefits [61]. Given that perceived value is a person’s judgment of the balance between the cost and the benefit achieved, it can be measured after the experience to predict a tourist’s behavioral intent. However, the formation factors of perceived value come from many aspects, and there is still no consensus on the number and classification standards of its dimensions. Watanabe et al. (2020) measured perceived value through four dimensions: functionality, economy, society, and emotion [60]. Caber et al. (2020) evaluated young tourists’ perception of value in natural tourism experiences from the perspectives of functional value, social value, and cognitive value [32]. Meeprom & Silanoi (2020) judged the influence of perceived special event quality solely from three aspects of perceived value: social, economic, and emotional value [62]. Choi et al. (2015) studied the perceived value of spa visitors by evaluating functional and wellness values [63]. This study evaluates the perceived value of forest-based health tourism for older adults from the perspectives of functional value and wellness value. Functional value reflects the older adults’ perception of the benefits of forest-based health tourism products, services, and projects relative to their monetary costs. Meanwhile, wellness value is closely related to the older adults’ health aspirations and the expected physical and mental health benefits derived from the tourism experience.
The widespread studies suggest that positive perceived value arises when tourists’ cost assessments align with their travel goals. For instance, Jeong and Kim (2019) demonstrated that event quality influences perceived value, indicating that higher-quality sports events lead to better perceived value among tourists and vice versa [31]. Kan & Tang (2022) focused on the relationship between travel agencies and tourists’ perceived value, discovering that agencies with customer orientation, product advantages, and high service performance positively impact their perceived value [64]. Suhartanto et al. (2021) zeroed in on the perceived value of Muslim tourists, finding that tourism experiences significantly influence perceived value [65]. However, Abraham (2016) stated that tourism crisis events can hurt tourists’ perception of a destination [66]. Toklu et al. (2017) examined the relationship between carbon emission crises and the perceived value of green consumers in Turkey, revealing negative impacts [67]. Given the severe damage caused by geological disasters to destinations [10,11,12], it prompts the hypothesis given below:
H2. 
Tourism crisis events negatively impact the perceived value of forest-based health tourism.
Significant associations between destination image and perceived value have received empirical support [31,33,68,69]. Vinh et al. (2023) showed that destination image strongly influences perceived value [68]. Suhud et al. (2023) confirmed that in volcanic tourism, people’s image of a destination significantly affects its perceived value [69]. Therefore, based on scholarly discussions, this paper proposes H3:
H3. 
Destination image positively impacts perceived value.

2.5. Behavioral Intention of Forest-Based Health Tourism as Response (R)

Behavioral intentions often describe consumers’ willingness to visit and/or revisit a destination, spend money, and make word-of-mouth recommendations [70]. Tavitiyaman & Qu (2013) and Dean & Suhartanto (2019) assert that applying the SOR theory to forest-based health tourism can allow researchers to assess the strength of older adults’ future behavioral intentions [34,71]. In light of the negative impacts of tourism crisis events, including on the overall safety, attractiveness, and comfort reputation of a destination, many scholars have confirmed that tourists’ behavior will change as a result of different tourism crisis events. Golet et al. (2023) surveyed 1150 Brazilian participants regarding their travel intentions during the coronavirus pandemic, and found that over 56.32% of participants rearranged their travel plans, and 36.58% cancelled their trips [72]. Following the magnitude 9.0 earthquake in Japan on 11 March 2011, the number of inbound tourists decreased by 27.8% compared to the same period in 2010, the most significant recorded decline in Japan [73]. Dwyer et al. (2006) analyzed data to conclude that the Iraq War decreased inbound tourism to Australia and outbound travel [74]. As geological disasters can easily damage tourism resources and infrastructure in forest-based health tourism, which relies on natural resources, this study believes that geological disasters will affect the behavioral intentions of older adult individuals towards forest-based health tourism. Based on this, we proposed the following hypothesis:
H4. 
Tourism crisis events negatively impact the behavioral intentions of older adults towards forest-based health tourism.
The relationship between destination image and behavioral intention has been well established in tourism literature [17,18,19]. A positive destination image positively impacts behavioral intention [17]. Destination image positively affects behavior [18]. Similarly, destination image significantly influences the intention to revisit a destination or recommend participation in tourism experiences [19]. Hence, it prompts the hypothesis given below:
H5. 
The destination image positively impacts the behavioral intention of older adults towards forest-based health tourism.
Perceived value is beneficial for the effectiveness of tourism operators’ predictions of tourists’ intention to revisit [75] a destination. The positive effects of perceived value on behavioral intention have been confirmed by surveying water park visitors [76]. Similarly, perceived value is an important predictor of behavioral intention [62]. The relationship between perceived value and behavioral intention has been demonstrated in nature-based tourism, with an emphasis on the fact that perceived value significantly impacts future tourist behavior [32]. Based on the preceding discussions, this study proposed the following hypothesis:
H6. 
Perceived value positively impacts the behavioral intention of older adults towards forest-based health tourism.
Based on the SOR theoretical model, this study considers geological disasters manifesting as tourism crisis events as stimulus factors. Researchers regard destination image and perceived value as the organism. The response variable is forest-based health tourism behavioral intention (see Figure 1). Therefore, this study poses Hypothesis 7:
H7. 
Destination image and perceived value play a chained mediation role between tourism crisis events and forest-based health tourism behavioral intention.

3. Materials and Methods

3.1. Description of the Research Case

Data indicate that the contribution of Guizhou’s tourism industry to the province’s GDP increased from 23.48% in 2010 to 73.46% in 2019 [77]. At the same time, Guizhou is one of the most significant and critical forested areas in China, and its forest resources occupy a vital position in the tourism economy of Guizhou Province [78]. In particular, the total output value of Guizhou’s forest-based health tourism industry reached CNY 19.657 billion in 2021 [24]. Guizhou’s various advantages, including its livable environment, abundant forest resources, and extensive health market, contribute to this success [22,23]. Consequently, Guizhou has significant development potential in forest-based health tourism.

3.2. Questionnaire Design

The questionnaire consists of two parts: the first is about the participants’ socio-demographic characteristics, and the second measures the study variables. The items used to measure the variables were all derived from previously developed scales in existing research. In this study, we used scales developed by Luo et al. (2020) and Rasoolimanesh et al. (2021) to assess two aspects of tourism crisis events: Fear of Crisis and Crisis Management [79,80]. Li et al. (2021) developed the scale to evaluate destination images [58]. Choi et al. (2015) defined perceived value as comprising Functional and Wellness values [63]. Similarly, Jin et al. (2015) based the behavioral intentions of tourists on their research, including three items: intention to revisit, intention to recommend, and willingness to tell others positive things about the destination [76] (see Appendix A). In our empirical analysis, all variables were measured using a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).

3.3. Data Collection and Analysis

This study employed a structured questionnaire design to measure the research variables. Given the rich forest resources in Guizhou, China, the number of tourists engaging in forest-based health tourism has been continuously increasing, and the global influence of forest-based health tourism has been expanding. Therefore, this study selected elderly individuals participating in Guizhou forest-based health tourism itineraries as the target population for research. The field research was conducted from 20 December 2023 to 15 January 2024, at national-level scenic spots for forest-based health tourism in Guizhou. Before distributing the questionnaires, researchers explained the purpose of the survey to the respondents in detail and promised that the collected information would only be used for scientific research to ensure the respondents’ privacy. Subsequently, the researchers guided the survey process and helped the older adults who met the age range requirement (60 and above) to complete the questionnaires. If the respondents fell outside the targeted age range, the survey was terminated. The team distributed and collected questionnaires in two stages, collecting 481 questionnaires from Guizhou. After excluding ineligible questionnaires (such as incomplete or random answers), 429 valid questionnaires were retained, with an adequate sample recovery rate of 89.2%.
Researchers used data analysis software to analyze the data in this study. First, they conducted a descriptive statistical analysis of the population statistics of the sample. Next, they subjected the data to a series of tests to determine their reliability and validity, and performed a confirmatory factor analysis (CFA). Finally, they tested the structural model, examined the hypotheses, and analyzed the mediation effect.

4. Results

4.1. Description of the Demographic Characteristics

Table 1 introduces the valid questionnaires that were analyzed. Among the 429 respondents to the formal questionnaire survey, there were 240 males (55.9%) and 187 females (43.6%). In terms of age, 211 were aged 60–65 years old (49.2%), 106 were aged 66–70 years old (24.7%), 85 were aged 71–75 years old (19.8%), and 27 were over 75 years old and above (6.3%). Regarding education level, 164 had a primary school education or below (38.2%), 201 had a secondary school, vocational school, or college education (46.9%), 54 had a bachelor’s degree (12.6%), and 10 had master’s or doctoral degrees (2.3%). In terms of annual income, 63 earned less than CNY 1000 (14.7%), 112 earned CNY 1001–3000 (26.1%), 83 earned CNY 3001–5000 (19.3%), 55 earned CNY 5001–7000 (12.8%), 37 earned CNY 7001–9000 (8.6%), and 79 earned more than CNY 9001 (18.4%). There were 124 individual entrepreneurs (28.9%), and 305 worked in other professions (71.1%). Among the respondents, 199 travelled once a year (46.4%), 122 travelled twice a year (28.4%), 37 travelled three times a year (8.6%), and 71 travelled more than three times a year (16.6%).

4.2. Testing the Measurement Model

4.2.1. Reliability Test and Confirmatory Factor Analysis

The reliability analysis of the collected questionnaires revealed that the Cronbach’s Alpha values for the dimensions of tourism crisis events, destination image, perceived value, and behavioral intention regarding forest-based health tourism were 0.948, 0.949, 0.952, and 0.835, respectively, with all exceeding 0.8. Table 2 shows the results of the reliability test. The data indicated that the reliability of this study met the standards and could proceed to the next stage of analysis.
The factor loadings range from 0.66 to 0.92, exceeding the recommended threshold of 0.5. The composite reliability (C.R.) of each construct is between 0.84 and 0.95, exceeding the recommended threshold (C.R. > 0.60). The average variance extracted (AVE) values range from 0.63 to 0.76, exceeding the suggested cutoff value of 0.50. According to the method of Fornell and Larcker (1981), the scale has convergent validity [81] (see Table 3).

4.2.2. Validity Test

From the perspective of discriminant validity (see Table 4), the scale of this study has acceptable discriminant validity [82] because the square root of the AVE value of each factor is greater than the “maximum correlation coefficient between this factor and other factors”.

4.3. Structural Model and Hypotheses Testing

4.3.1. Confirmatory Factor Analysis

Confirmatory factor analysis (CFA) is a research method used to measure whether the corresponding relationships between factors and measurement items (scale items) are consistent with the researcher’s prediction [83]. Table 5 shows that the model fit indices are CMIN/DF = 2.496 (<5), standardized root mean square residual (RMESA) = 0.059 (<0.08), goodness of fit index (GFI) = 0.878, adjusted goodness of fit index (AGFI) = 0.856, TLI = 0.947, confirmatory fit index (CFI) = 0.951, and IFI = 0.951. The fitting index results of this questionnaire scale indicate that the model is acceptable [84].

4.3.2. Hypothesis Tests and the Analysis of the Mediating Effects

Hypothesis 1 suggests a negative relationship between tourism crisis events and destination image (coefficient = −0.415, p < 0.01). Similarly, Hypothesis 2 suggests a negative relationship between tourism crisis events and perceived value (coefficient = −0.47, p < 0.01). Meanwhile, Hypothesis 3 suggests a positive relationship between destination image and perceived value (coefficient = 0.337, p < 0.01). Hypothesis 4 suggests a negative relationship between tourism crisis events and behavioral intention (coefficient = −0.324, p < 0.01). Furthermore, Hypothesis 5 suggests a positive relationship between destination image and behavioral intention (coefficient = 0.202, p < 0.01). Additionally, Hypothesis 6 suggests a positive relationship between perceived value and behavioral intention (coefficient = 0.381, p < 0.01) (see Table 6 and Figure 2).

4.3.3. Analysis of Mediating Effects

To verify the significance threshold of indirect effects, the researchers analyzed the data in this study. This study continued to use the free bootstrapping method (with 2000 bootstrapping samples recovered from 408 samples) under the assumption of a multivariate normal distribution. The researchers tested the significance of indirect effects in the final path model at the 95% confidence interval level. Table 7 indicates that the total effect found in this study is c = −0.662, which is significant (p < 0.05). According to Table 7, the indirect effect of (tourism crisis events→destination image→behavioral intention) is −0.087, which is significant (p < 0.05), indicating significant indirect effects. Thus, the mediating effect is significant and partial. The analysis verifies the mediating role of destination image in the relationship between tourism crisis events and forest-based health tourism behavioral intentions. The indirect effect of (tourism crisis events→perceived value→behavioral intention) is −0.185, which is significant (p < 0.05), indicating significant indirect effects. Thus, the mediating effect is significant and partial. The results validate the mediating role of perceived value in the relationship between tourism crisis events and forest-based health tourism behavioral intentions. The indirect effect of (tourism crisis events→destination image→perceived value→behavioral intention) is −0.055, which is significant (p < 0.05), indicating significant indirect effects. Thus, tourism crisis events affect forest-based health behavioral intention by influencing destination image and then perceived value. This verifies the establishment of H7. The results of mediation effects are shown in Figure 3.

5. Discussions

5.1. Theoretical Implications

This study established a chained mediation model between tourism crisis events and behavioral intentions for forest-based health tourism, elucidating their inherent logic.
The paper empirically investigates the impact of geological disasters as tourism crisis events. As mentioned earlier, there are numerous types of tourism crisis events, yet the general focus of tourism literature is on economic crises and terrorist incidents [14], with limited discussion on the theme of geological disasters. Regarding tourism crisis events, scholars tend to pay less attention to the growing older adult consumer group [14,15,38,47,48,72,73,74]. Therefore, we aim to fill this gap by examining the impact of geological disasters on forest-based health tourism destinations from the perspective of older adults. This study aims to serve as a catalyst for further research on tourism crisis events in natural resource-based destinations and to draw the attention of tourism scholars to this research question.
Secondly, given the potential applicability of SOR theory in a broader context of health tourism [40], this study constructs a chained mediation model to describe the process of how older adults respond to tourism crisis events and develop a willingness to participate in forest-based health tourism, thereby expanding the scope of SOR theory. This paper explains how tourism crisis stimuli trigger reactions in destination image, perceived value, and willingness to engage in forest-based health tourism behavior (O, R). On the one hand, it validates the individual effects of destination image and perceived value on the relationship between tourism crisis events and willingness to engage in forest-based health tourism behavior. On the other hand, it verifies the effectiveness of the “Stimulus–Organism–Response” process in explaining the chained mediation role of tourism crisis events and willingness to engage in forest-based health tourism behavior.
Additionally, we found that tourism crisis events hurt both destination image and perceived value, consistent with the findings of previous studies [14,15,48,66]. However, our results reveal that the negative impact of tourism crisis events on perceived value exceeds its impact on destination image, indicating that perceived value is more vulnerable to damage from tourism crisis events. Furthermore, the study also found that, in the context of tourism crisis events, perceived value has a more vital driving force on willingness to engage in forest-based health tourism behavior than destination image, emphasizing the importance of perceived value in influencing willingness to engage in forest-based health tourism behavior.
Lastly, this study has explained the inherent mechanisms of variables, demonstrated the influence of destination image and perceived value on behavioral intention in forest-based health tourism in the context of geological disasters as tourism crisis events, and further enriched the research on forest-based health tourism. Specifically, the more severe the tourism crisis events are perceived to be by older adult tourists, the greater the damage to destination image and perceived value, ultimately leading to their negative willingness to engage in forest-based health tourism. This paper re-examines the formation mechanism of tourists’ behavioral intention from the perspective of older adult tourists, providing a valuable perspective that encourages paying attention to tourists’ behavioral intention in the era of rapid health tourism development.

5.2. Practical Implications

Firstly, this study found that tourism crisis events, dominated by geological disasters, hurt the behavioral intention of forest-based health tourism, especially for destinations that rely on natural resources for tourism development. Therefore, destination managers should attach great importance to the prevention of and response to tourism crisis events, such as geological disasters. Meanwhile, they should strengthen the dissemination and marketing of tourism information to enhance tourists’ understanding of destination characteristics and advantages. In particular, for the special group of older adult tourists, it is essential to fully consider their physiological and psychological characteristics in developing tourism products and providing services, offering suitable tourism products and services to attract more older adult tourists.
Secondly, the study also found that tourism crisis events can negatively affect the behavioral intention of forest-based health tourism through destination image and perceived value. Managers of tourist destinations should have various channels to create a positive perception of the image of the tourist destination. They should understand that tourism crisis events are not disasters that destroy destinations, but through practical measures, they can allow older adults to perceive Guizhou as a unique, safe, and healthy forest tourism destination. If older adults can gain forest-based health tourism experiences in Guizhou that are different from other destinations, they can perceive a more favorable destination image.
In addition, destination managers should support more healthcare facilities and activities to enhance the perceived value of older adults. This discovery is significant for the development of forest-based health tourism and is related to Guizhou’s background. These methods can make Guizhou stand out as a forest-based health tourism destination compared to other destinations, allowing older adults to gain more perceived value, positively affecting their behavioral intentions, and increasing their revisit rates and recommendation rates.

6. Conclusions

This study adds to the extant literature on tourists’ perceptions of the influence of natural disasters and their behavioral intention to travel. Specifically, it examines how geological disasters, when framed as tourism crisis events, uniquely affect older adult tourists. We found that such disasters can evoke significant tension and anxiety among them, intensifying fears related to their safety while traveling. This reaction is particularly pronounced due to the combined factors of physical vulnerability and the unfamiliar environment associated with tourism. Moreover, the management measures and responses of tourism destinations to these geological events critically influence older tourists’ perceptions and their decision-making regarding travel. Our findings suggest that tourism crisis events strongly impact older adults’ perceived value intentions and destination images. The influence of social media, destination management, and marketing strategies was found to be less significant in shaping behavioral intentions compared to the direct effects of crisis events. Given these insights, future research should delve into the role of destination management and marketing during tourism crises. Additionally, expanding the survey scope to include more potential older tourists will help ensure more comprehensive findings. Consequently, we suggest that future research should explore the recovery timelines and long-term resilience of tourism destinations following crises such as earthquakes, mass shootings, or tsunamis. Such studies should employ longitudinal data to assess how quickly and effectively tourism destinations rebound and the factors influencing these recovery processes.

Author Contributions

Conceptualization, C.X. and J.D.; methodology, S.J.; software, C.X.; validation, C.X., J.D. and S.J.; formal analysis, S.J.; investigation, C.X.; resources, J.D. and S.J.; data curation, C.X.; writing—original draft preparation, C.X., J.D. and S.J.; writing—review and editing, C.X., J.D. and S.J.; visualization, C.X.; supervision, S.J.; project administration, C.X., J.D. and S.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data are available on request.

Acknowledgments

The authors would like to acknowledge the helpful support received from the respondents during the collection of the field data.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Questionnaire for the investigation of the influencing mechanisms of older adults’ behavioral intention regarding forest-based health tourism in Guizhou Province, China.
Dear Sir/Madam,
Greetings! We sincerely appreciate your valuable time and participation in this questionnaire survey. Our research team comprises a PhD student from Rajamangala University of Technology Rattanakosin, Thailand, and students from Liupanshui Normal College. The purpose of this questionnaire is to investigate the influencing factors on the behavioral intention of the older adults in forest-based health tourism, particularly in the context of the geological disaster (Including: earthquake, collapse, landslide, mud-rock flow, flash flood and other types). Please rest assured that the questionnaire is anonymous, and all data collected will be used solely for academic research. Your privacy will be strictly protected, and no personal information will be disclosed.
There are no right or wrong answers to the questions provided. Please respond based on your personal experiences and circumstances. Once again, we express our gratitude for your participation. Your thoughtful responses will provide valuable insights for the development of forest-based health tourism in Guizhou. We wish you good health and a joyful life.
Part One: Basic personal information (Instructions for completion: Please answer the questions according to your specific situation by selecting the appropriate options. If none of the options are suitable for your answer, kindly provide the accurate information in the “Other” section.)
(1) Your gender: □Male; □Female; □Other
(2) Your age: □60~65 years old; □66~70 years old; □71~75 years old; □Over 75 years old
(3) Your educational background: □primary school and below; □Junior high school or technical secondary school; □High school or college; □Bachelor degree or above; □No educational experience
(4) Your annual social security amount or annual income is: □1000 yuan or less; □1001–3000 yuan; □3001–5000 yuan; □5001–7000 yuan; □7001–9000; □9001 and above
(5) Your occupation before retirement or now: □self-employed; □Staff of state organs and institutions; □A doctor or nurse; □farmer; □other
(6) Your average annual travel: □1 time; □2 times; □3 times; □more than 3 times
(7) Where are you from: □Beijing; □Shanghai; □Guangdong; □Guangxi; □Zhejiang; □Hunan; □Hubei; □Hong Kong, Macao and Taiwan; □Yunnan; □Guizhou; □Chongqing; □Chengdu; □Hainan; □other
Part two: Questionnaire on influencing factors of forest-based health tourism behavior intention (Instructions for completion: The following are scale questions. Please select the option that best represents your subjective perception of forest-based health tourism in Guizhou. Thank you for your thoughtful responses!)
In this scale, 1 point represents “strongly disagree”, 2 points represent “disagree”, 3 points represent “neutral”, 4 points represent “agree”, and 5 points represent “strongly agree”. The impact level increases gradually.
ScaleQuestion
Tourism crisis eventFear of CrisisTCE1I am most afraid of the geological disaster.
TCE2It makes me uncomfortable to think about geological disaster.
TCE3My hands become sweaty when I think about geological disaster.
TCE4I am afraid of losing my life because of geological disaster.
TCE5When watching news and stories about geological disaster on social media or any other media (i.e., TV, Radio), I become nervous or anxious.
TCE6I cannot sleep because I am worried about getting the geological disaster.
TCE7My heart races or palpitates when I think about getting geological disaster.
Crisis Management TCE8I admire the timely and early treatment of geological disaster by the authorities of Guizhou.
TCE9I admire the forceful and rapid response to geological disaster in Guizhou.
TCE10I admire the effective management of the supply chain risk and disruption (shortage of food and medicine) in Guizhou.
Destination ImageDI1Guizhou is an exciting forest-based health tourism site.
DI2Guizhou is a pleasant forest-based health tourism site.
DI3Guizhou is a forest-based health tourism site that can make people relax.
DI4Guizhou provides good quality ecotourism experience.
DI5The forest-based health tourism experience you are getting in Guizhou will be different from other place.
DI6Guizhou offers unforgettable forest-based health tourism.
Perceive valueFunctional ValuePV1Visiting Forest-based health tourism in Guizhou was economical.
PV2Considering the cost, Forest-based health tourism in Guizhou provided a lot of benefits.
PV3Forest-based health tourism in Guizhou offered a better value for the money than other places.
PV4The value of forest-based health tourism in Guizhou exceeded travel expense.
PV5Visiting forest-based health tourism in Guizhou was affordable.
Wellness ValuePV6Forest-based health tourism in Guizhou had value for improving my quality of life.
PV7Forest-based health tourism in Guizhou had beneficial value for my health.
PV8Visiting Forest-based health tourism in Guizhou evoked energy for living.
PV9Visiting Forest-based health tourism in Guizhou relieved my tension.
Behavioral Intention of Forest-Based Health TourismBI1I would like to return to Guizhou in the future.
BI2I would recommend Guizhou to my friends or other acquaintances.
BI3I Want To Tell Other People Positive Things About Guizhou.

References

  1. Global Wellness Institute. 2018 Global Wellness Tourism Economy. 2018. Available online: https://globalwellnessinstitute.org/ (accessed on 20 May 2023).
  2. Pu, B.; Du, F.; Zhang, L.; Qiu, Y. Subjective knowledge and health consciousness influences on health tourism intention after the COVID-19 pandemic: A prospective study. J. Psychol. Afr. 2021, 31, 131–139. [Google Scholar] [CrossRef]
  3. Agarwal, P.; Parashar, A. Forest-based Model:A Nature-based Health Tourism Practice at Tourism Destinations. Himal. J. Soc. Sci. Humanit. 2023, 18, 99–110. [Google Scholar]
  4. Ohe, Y.; Ikei, H.; Song, C.; Miyazaki, Y. Evaluating the relaxation effects of emerging forest-therapy tourism: A multidisciplinary approach. Tour. Manag. 2017, 62, 322–334. [Google Scholar] [CrossRef]
  5. Li, H.; Zhang, G. How can plant-enriched natural environments benefit human health: A narrative review of relevant theories. Int. J. Environ. Health Res. 2023, 34, 1241–1254. [Google Scholar] [CrossRef] [PubMed]
  6. Cvikl, D.; Avgustin, C.; Kreft, S. The Physiological and Psychological Effects Benefits of Forest Therapy (FT) on Tourists in the Kranjska Gora Destination. Forests 2022, 13, 1670. [Google Scholar] [CrossRef]
  7. Zoysa, M. Forest-based ecotourism in Sri Lanka: A review on state of governance, livelihoods, and forest conservation outcomes. J. Sustain. For. 2022, 41, 413–439. [Google Scholar] [CrossRef]
  8. Khan, N.; Hassan, A.U.; Fahad, S.; Naushad, M. Factors Affecting Tourism Industry and Its Impacts on Global Economy of the World. 2020. Available online: https://papers.ssrn.com/sol3/Papers.cfm?abstract (accessed on 10 June 2023).
  9. Vasil’yev, P.V. Questions of the Geographic Study and Economic use of Forests. Sov. Geogr. 1960, 1, 50–63. [Google Scholar] [CrossRef]
  10. Zhang, M.; Seyler, B.C.; Di, B.; Wang, Y.; Tang, Y. lmpact of earthquakes on natural area-driven tourism: Case study of China’sJiuzhaigou National Scenic Spot. Int. J. Disaster Risk Reduct. 2021, 58, 102216. [Google Scholar] [CrossRef]
  11. Chen, M.-L.; Hu, G.-S.; Chen, N.-S.; Zhao, C.-Y.; Zhao, S.-J.; Han, D.-W. Valuation of debris flow mitigation measures in tourist towns: A case study on Hongchun gully in southwestChina. J. Mt. Sci. 2016, 13, 1867–1879. [Google Scholar] [CrossRef]
  12. Dhakal, S.; Cui, P.; Rijal, C.P.; Su, L.-J.; Zou, Q.; Mavrouli, O.; Wu, C.-H. Landslide characteristics and its impact on tourism for two roadside towns along the Kathmandu Kyirong Highway. J. Mt. Sci. 2020, 17, 1840–1850. [Google Scholar] [CrossRef]
  13. Li, F.; Wen, J.; Ying, T. The influence of crisis on tourists’ perceived destination image and revisit intention:An exploratory study of Chinese tourists to North Korea. J. Destin. Mark. Manag. 2018, 9, 104–111. [Google Scholar]
  14. Assaker, G.; O’Connor, P. eWOM platforms in moderating the relationships between political and terrorism risk, destination image, and travel intent: The case of Lebanon. J. Travel Res. 2020, 60, 503–519. [Google Scholar] [CrossRef]
  15. Lu, Q.; Atadil, H.A. Do you dare to travel to China? An examination of China’s destination image amid the COVID-19. Tour. Manag. Perspect. 2021, 40, 100881. [Google Scholar] [CrossRef] [PubMed]
  16. Kraliková, A.; Peruthová, A.; Ryglová, K. Impact of destination image on satisfaction and loyalty. Acta Univ. Agric. Et Silvic. Mendel. Brun. 2020, 68, 199–209. [Google Scholar] [CrossRef]
  17. Tavitiyaman, P.; Qu, H.; Tsang, W.-S.L.; Lam, C.-W.R. The influence of smart tourism applications on perceived destination image and behavioral intention: Themoderating role of information search behavior. J. Hosp. Tour. Manag. 2021, 46, 476–487. [Google Scholar] [CrossRef]
  18. Nazir, M.U.; Yasin, I.; Tat, H.H. Destination image’s mediating role between perceived risks, perceived constraints, and behavioral intention. Heliyon 2021, 7, e07613. [Google Scholar] [CrossRef]
  19. Hahm, J.J.; Severt, K. Importance of destination marketing on image and familiarity. J. Hosp. Tour. Insights 2018, 1, 37–53. [Google Scholar] [CrossRef]
  20. Zhao, Y.; Shi, Y.; Feng, C.-C.; Guo, L. Exploring coordinated development between urbanization and ecosystem services value of sustainable demonstration area in China-take Guizhou Province as an example. Ecol. Indic. 2022, 144, 109444. [Google Scholar] [CrossRef]
  21. Cui, D.; Chen, X.; Xue, Y.; Li, R.; Zeng, W. An integrated approach to investigate the relationship of coupling coordination between social economy and water environment onurban scale—A case study of Kunming. J. Environ. Manag. 2019, 234, 189–199. [Google Scholar] [CrossRef]
  22. Fan, C.; Zhou, L.; Gai, Z.; Shen, S.; Liu, C.; Li, S. Multi-Dimensional Evaluation Framework for the Sustainable Development of Forest Health Bases and Site Selection for Application in China. Forests 2022, 13, 799. [Google Scholar] [CrossRef]
  23. Wang, J.; Zhong, L.; Chen, T. Ecotourism Resources Assessment and Development Strategy for Guizhou Province, China. J. Resour. Ecol. 2017, 8, 648–654. [Google Scholar]
  24. Guizhou Forestry Bureau, China. More than 10 Million People Have Taken Part in Forest Health Care in Guizhou Province 2023. Available online: https://lyj.guizhou.gov.cn/gzlq/slky/202311/t20231117_83095918.html (accessed on 20 December 2023).
  25. Liu, Y.; Zhang, J. An IoT-Based Intelligent Geological Disaster Application Using Open-Source Software Framework. Sci. Program 2022, 2022, 9285258. [Google Scholar] [CrossRef]
  26. Park, K.; Reisinger, Y. Differences in the perceived influence of natural disasters and travel risk on international travel. Tour. Geogr. 2010, 12, 1–24. [Google Scholar] [CrossRef]
  27. Hua, C.; Cole, S.; Xu, N. Rethinking trust in tourism apps: The moderating effect of age. J. Hosp. Tour. Technol. 2021, 12, 548–562. [Google Scholar] [CrossRef]
  28. Euromonitor International. Old Is the New Young. 2017. Available online: http://www.euromonitor.com/old-is-the-new-young-how-global-consumers-are-challenging-ageing/report (accessed on 15 March 2023).
  29. National Bureau of Statistics of China. Statistical Bulletin on National Economic and Social Development of the People’s Republic of China in 2023. 2024. Available online: https://www.stats.gov.cn/sj/zxfb/202402/t20240228_1947915.html (accessed on 8 February 2024).
  30. China Development Research Foundation. China Development Report 2020: Trends and Policies of Population Aging in China. 2020. Available online: http://js.people.com.cn/n2/2020/0613/c359574-34084353.html (accessed on 10 May 2023).
  31. Jeong, Y.; Kim, S. A study of event quality, destination image, perceived value, tourist satisfaction, and destination loyalty among sport tourists. Asia Pac. J. Mark. Logist. 2020, 32, 940–960. [Google Scholar] [CrossRef]
  32. Caber, M.; Albayrak, T.; Crawford, D. Perceived value and its impact on travel outcomes in youth tourism. J. Outdoor Recreat. Tour. 2020, 31, 100327. [Google Scholar] [CrossRef]
  33. Asgarnezhad, N.B.; Nemati, V.; Abbasgholizadeh, N. The effect of perceived value on the destination image, satisfaction and loyalty of medical tourists: A case study in Ardabil. J. Health 2019, 10, 34–49. [Google Scholar] [CrossRef]
  34. Dean, D.; Suhartanto, D. The formation of visitor behavioral intention to creative tourism: The role of push-Pull motivation. J. Tour. Res. 2019, 24, 393–403. [Google Scholar] [CrossRef]
  35. Mehrabian, A.; Russell, J.A. An Approach to Environmental Psychology; MIT Press: Cambridge, UK, 1974. [Google Scholar]
  36. Zhu, L.; Li, H.; Wang, F.-K.; He, W.; Tian, Z. How online reviews affect purchase intention: A new model based on the stimulus-organism-response (S-O-R) framework. Aslib J. Inf. Manag. 2020, 72, 463–488. [Google Scholar] [CrossRef]
  37. Liang, X.; Huo, Y.; Luo, P. What drives impulsive travel intention in tourism live streaming? A chain mediation model based on SOR framework. J. Travel Tour. Mark. 2024, 41, 169–185. [Google Scholar] [CrossRef]
  38. Wang, J.; Xia, L. Revenge travel:Nostalgia and desire for leisure travel post COVID-19. J. Travel Tour. Mark. 2021, 38, 935–955. [Google Scholar] [CrossRef]
  39. Kim, M.J.; Lee, C.-K.; Jung, T. Exploring consumer behavior in virtual reality tourism using an extended stimulus-organism-response model. J. Travel Res. 2020, 59, 69–89. [Google Scholar] [CrossRef]
  40. Chen, K.-H.; Huang, L.; Ye, Y. Research on the relationship between wellness tourism experiencescape and revisit intention: A chain mediation model. Int. J. Contemp. Hosp. Manag. 2023, 35, 893–918. [Google Scholar] [CrossRef]
  41. Jiang, L.; Wu, H.; Song, Y. Diversified demand for health tourism matters: From a perspective of the intra-industry trade. Soc. Sci. Med. 2022, 293, 114630. [Google Scholar] [CrossRef] [PubMed]
  42. Buckley, R. Tourism and mental health: Foundations, frameworks, and futures. J. Travel Res. 2023, 62, 3–20. [Google Scholar] [CrossRef]
  43. Bachinger, M.; Rau, H. Forest-Based Health Tourism as a Tool for Promoting Sustainability: A Stakeholder-Based Analysis of Supply-Side Factors in Tourism Product Development; Springer: Cham, Switzerland, 2019; pp. 87–104. [Google Scholar]
  44. Li, Y.; Wen, T. Impact of cognition and social trust on forest-based health tourism intention during COVID-19. Sustainability 2022, 15, 714. [Google Scholar] [CrossRef]
  45. Li, Y.; Han, Q.; Wen, T. Effect of frugality and cognition on forest health tourism intention-a mediating effect analysis based on multigroup comparison. Front. Psychol. 2022, 13, 844628. [Google Scholar] [CrossRef] [PubMed]
  46. Jin, X.; Qu, M.; Bao, J. Impact of crisis events on Chinese outbound tourist flow: A framework for post-events growth. Tourism Management. Tour. Manag. 2019, 74, 334–344. [Google Scholar] [CrossRef] [PubMed]
  47. Duan, J.; Xie, C.; Morrison, A.M. Tourism crises and impacts on destinations: A systematic review of the tourism and hospitality literature. J. Hosp. Tour. Res. 2022, 46, 667–695. [Google Scholar] [CrossRef]
  48. Som, A.P.M.; Aun, O.C.; AlBattat, A.R. Tourists’ perception of crisis and the impact of instability on destination safety in Sabah, Malaysia. Tour. Environ. Soc. Manag. Sci. 2015, 5, 96–103. [Google Scholar]
  49. Beirman, D. Tourism Crisis and Safety Management; SAGE: Los Angeles, CA, USA, 2018. [Google Scholar]
  50. Santana, G. Crisis management and tourism: Beyond the rhetoric. J. Travel Tour. Mark. 2004, 15, 299–321. [Google Scholar] [CrossRef]
  51. Jamal, T.; Budke, C. Tourism in a world with pandemics: Local-global responsibility and action. J. Tour. Futures 2020, 6, 181–188. [Google Scholar] [CrossRef]
  52. Ulak, N. A preliminary study of novel coronavirus disease (COVID-19) outbreak: A pandemic leading crisis in tourism industry of Nepal. J. Tour. Hosp. Educ. 2020, 10, 108–131. [Google Scholar] [CrossRef]
  53. Widayati, C.C.; Ali, H.; Permana, D.; Nugroho, A. The role of destination image on visiting decisions through word of mouth in urban tourism in Yogyakarta. Int. J. Innov. Creat. Change 2020, 12, 177–196. [Google Scholar]
  54. Eid, R.; El-Kassrawy, Y.A.; Agag, G. Integrating destination attributes, political (in) stability, destination image, tourist satisfaction, and intention to recommend:A study of UAE. J. Hosp. Tour. Res. 2019, 43, 839–866. [Google Scholar] [CrossRef]
  55. Zhang, H.; Fu, X.; Cai, L.A.; Lu, L. Destination image and tourist loyalty: A meta-analysis. Tour. Manag. 2014, 40, 213–223. [Google Scholar] [CrossRef]
  56. Afshardoost, M.; Eshaghi, M.S. Destination image and tourist behavioural intentions: A meta-analysis. Tour. Manag. 2020, 81, 104154. [Google Scholar] [CrossRef]
  57. King, C.; Chen, N.; Funk, D.C. Exploring destination image decay: A study of sport tourists’ destination image change after event participation. J. Hosp. Tour. Res. 2015, 39, 3–31. [Google Scholar] [CrossRef]
  58. Li, T.T.; Liu, F.; Soutar, G.N. Experiences, post-trip destination image, satisfaction and loyalty: A study in an ecotourism context. J. Destin. Mark. Manag. 2021, 19, 100547. [Google Scholar] [CrossRef]
  59. Abbasi, G.A.; Kumaravelu, J.; Goh, Y.-N.; Singh, K.S.D. Understanding the intention to revisit a destination by expanding the theory of planned behaviour (TPB). Span. J. Mark. 2021, 25, 282–311. [Google Scholar] [CrossRef]
  60. Watanabe, E.A.M.; Alfinito, S.; Curvelo, L.C.G.; Hamza, K.M. Perceived value, trust and purchase intention of organic food: A study with Brazilian consumers. Br. Food J. 2020, 122, 1070–1184. [Google Scholar] [CrossRef]
  61. Al-Adamat, A.M.; Al-Gasawneh, J.A.; Sourak, N.A. The mediating effect of perceived value on the relationship between online promotion and travel intention. Test Eng. Manag. 2020, 83, 14911–14920. [Google Scholar]
  62. Meeprom, S.; Silanoi, T. Investigating the perceived quality of a special event and its influence on perceived value and behavioural intentions in a special eventin Thailand. Int. J. Event Festiv. Manag. 2020, 11, 337–355. [Google Scholar] [CrossRef]
  63. Choi, Y.; Kim, J.; Lee, C.-K.; Hickerson, B. The role of functional and wellness values in visitors’ evaluation of spa experiences. Asia Pac. J. Tour. Res. 2015, 20, 263–279. [Google Scholar] [CrossRef]
  64. Kan, T.C. Perceived value, inter-functional coordination, and strategic adaptation: The perspective on selecting travel agencies from school travel plan. J. Tour. Serv. 2022, 13, 236–255. [Google Scholar] [CrossRef]
  65. Suhartanto, D.; Dean, D.; Wibisono, N.; Astor, Y.; Muflih, M.; Kartikasari, A.; Sutrisno, R.; Hardiyanto, N. Tourist experience in halal tourism: What leads to loyalty? Curr. Issues Tour. 2021, 24, 1976–1990. [Google Scholar] [CrossRef]
  66. Avraham, E. Destination marketing and image repair during tourism crises: The case of Egypt. J. Hosp. Tour. Manag. 2016, 28, 41–48. [Google Scholar] [CrossRef]
  67. Toklu, I.; Kucuk, H. The impact of brand crisis on consumers green purchase intention and willingness to pay more. Int. Bus. Res. 2017, 10, 22–33. [Google Scholar] [CrossRef]
  68. Vinh, N.Q.; Hien, L.M.; Thanh, T.D. The Effect of Destination lmage and Perceived Value on the Loyalty of lnternational Tourists to Cultural Heritage Tourism in Hanoi. Adv. Decis. Sci. 2023, 27, 87–114. [Google Scholar]
  69. Suhud, U.; Allan, M.; Fauzi, A.A.; Kurniawan, R. Tourists’ intentions to revisit a geothermal site: The case of Kawah Putih. Geoheritage 2023, 15, 44. [Google Scholar] [CrossRef]
  70. Kock, F.; Josiassen, A.; Assaf, A.G. Advancing destination image: The destination content model. Ann. Tour. Res. 2016, 61, 28–44. [Google Scholar] [CrossRef]
  71. Tavitiyaman, P.; Qu, H. Destination image and behavior intention of travelers to Thailand: The moderating effect of perceived risk. J. Travel Tour. Mark. 2013, 30, 169–185. [Google Scholar] [CrossRef]
  72. Golets, A.; Farias, J.; Pilati, R.; Costa, H. COVID-19 pandemic and tourism: The impact of health risk perception and intolerance of uncertainty on travel intentions. Curr. Psychol. 2023, 42, 2500–2513. [Google Scholar] [CrossRef]
  73. Wu, L.; Hayashi, H. The impact of disasters on Japan’s inbound tourism demand. J. Disaster Res. 2014, 9, 699–708. [Google Scholar] [CrossRef]
  74. Dwyer, L.; Forsyth, P.; Spurr, R.; Van Ho, T. Economic effects of the world tourism crisis on Australia. Tour. Econ. 2006, 12, 171–186. [Google Scholar] [CrossRef]
  75. Zhang, B.; Niyomsilp, E. The relationship between tourism destination image, perceived value and post-visiting behavioral intention of Chinese tourist to Thailand. Int. Bus. Res. 2020, 13, 96–105. [Google Scholar] [CrossRef]
  76. Jin, N.; Lee, S.; Lee, H. The effect of experience quality on perceived value, satisfaction, image and behavioral intention of water park patrons: New versus repeat visitors. Int. J. Tour. Res. 2015, 17, 82–95. [Google Scholar] [CrossRef]
  77. Luo, W.; Wu, S. The influence of transportation on regional tourism economic development under the environment of sustainable development: Taking Guizhou Province in China as anexample. Glob. Nest J. 2023, 25, 106–112. [Google Scholar]
  78. Lu, Z.; Peters, C.; Ashton, M.; Feng, J.; Xue, D. The effect of forest tenure on forest composition in a miao area of guizhou, China. Mt. Res. Dev. 2016, 36, 193–202. [Google Scholar] [CrossRef]
  79. Luo, J.M.; Lam, C.F. Travel anxiety, risk attitude and travel intentions towards “travel bubble” destinations in Hong Kong: Effect of the fear of COVID-19. Int. J. Environ. Res. Public Health 2020, 17, 7859. [Google Scholar] [CrossRef]
  80. Rasoolimanesh, S.M.; Seyfi, S.; Rastegar, R.; Hall, C.M. Destination image during the COVID-19 pandemic and future travel behavior: The moderating role of pastexperience. J. Destin. Manag. 2021, 21, 100620. [Google Scholar] [CrossRef]
  81. Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981, 1, 39–50. [Google Scholar] [CrossRef]
  82. Hair, J.F.; Ringle, C.M.; Sarstedt, M. PLS-SEM: Indeed a silver bullet. J. Mark. Theory Pract. 2011, 19, 139–152. [Google Scholar] [CrossRef]
  83. Brown, T.A. Confirmatory Factor Analysis for Applied Research; Guilford Press: New York, NY, USA, 2015. [Google Scholar]
  84. Hu, L.-T.; Bentler, P.M. Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychol. Methods 1998, 4, 424–453. [Google Scholar] [CrossRef]
Figure 1. The conceptual framework of this study.
Figure 1. The conceptual framework of this study.
Forests 15 01324 g001
Figure 2. The results of testing the hypotheses.
Figure 2. The results of testing the hypotheses.
Forests 15 01324 g002
Figure 3. The results of mediation effects.
Figure 3. The results of mediation effects.
Forests 15 01324 g003
Table 1. Demographic characteristics.
Table 1. Demographic characteristics.
Demographic Characteristics (%)
GenderMale55.9
Female43.6
Age60–65 years old49.2
66–70 years old24.7
71–75 years old19.8
Over 75 years old6.3
Education levelPrimary school education or below38.2
Secondary school, vocational school, or college education46.9
Bachelor’s degree12.6
Master’s or doctoral degree2.3
Annual incomeLess than CNY 100014.7
CNY 1001–300026.1
CNY 3001–500019.3
CNY 5001–700012.8
CNY 7001–90008.6
More than CNY 900118.4
OccupationIndividual entrepreneurs28.9
Other professions71.1
Annual average frequency of tripsOnce a year46.4
Twice a year28.4
Three times a year8.6
More than 3 times a year16.6
Table 2. Analysis of reliability.
Table 2. Analysis of reliability.
VariablesCronbach’s AlphaNumber of Terms
Tourism Crisis Events (TCI)0.94810
Destination Image (DI)0.9496
Perceived Value (PV)0.9529
Behavioral Intention of Forest-Based Health Tourism (BI)0.8353
Table 3. Analysis of convergent validity.
Table 3. Analysis of convergent validity.
PathEstimateS.E.C.R.AVEC.R.
TCE 6<---Tourism Crisis Events0.833 0.650 0.949
TCE 5<---0.7950.0519.885
TCE 4<---0.8860.04723.718
TCE 3<---0.7810.05219.369
TCE 2<---0.7460.05118.104
TCE 1<---0.6630.05215.402
TCE 7<---0.8930.04624.045
TCE 8<---0.8270.04921.174
TCE 9<---0.7640.04718.728
TCE 10<---0.8470.04721.983
DI 6<---Destination Image0.841 0.756 0.949
DI 5<---0.8860.04524.072
DI 4<---0.8860.04424.084
DI 3<---0.8640.04623.036
DI 2<---0.8580.04222.77
DI 1<---0.8820.04523.891
PV 4<---Perceived Value0.828 0.690 0.952
PV 5<---0.8120.05220.427
PV 6<---0.8370.04821.422
PV 7<---0.8070.05120.213
PV 8<---0.8460.04921.788
PV 9<---0.8010.04920.022
PV 3<---0.9190.04625.072
PV 2<---0.8130.04420.455
PV 1<---0.8060.04620.195
BI 1<---Behavioral Intention
of Forest-Based Health
Tourism
0.851 0.634 0.838
BI 2<---0.7920.04917.788
BI 3<---0.7420.04916.478
Table 4. Analysis of discriminant validity.
Table 4. Analysis of discriminant validity.
TCEDI PV BI
TCE0.806
DI−0.389 **0.87
PV−0.582 **0.505 **0.831
BI−0.582 **0.484**0.620 **0.796
** Correlation is significant at the 0.01 level (2-tailed).
Table 5. Fitting index analysis.
Table 5. Fitting index analysis.
Observation IndexEvaluation IndexResults
AcceptableGoodness
CMIN/DF<5.00<32.496
RMESA<0.08<0.050.059
GFI[0.7, 0.9]>0.90.878
AGFI[0.7, 0.9]>0.90.856
TLI[0.7, 0.9]>0.90.947
CFI[0.7, 0.9]>0.90.951
IFI[0.7, 0.9]>0.90.951
Table 6. Results of hypothesis testing.
Table 6. Results of hypothesis testing.
PathEstimateStd.
Estimate
S.E.C.R.pHypotheses Testing
DI<---TCE−0.486−0.4150.059−8.305***supported
P.V.<---TCE−0.504−0.470.051−9.924***supported
P.V.<---DI0.3090.3370.0417.481***supported
B.I.<---PV0.3670.3810.0556.683***supported
B.I.<---TCE−0.335−0.3240.054−6.197***supported
B.I.<---DI0.1790.2020.0424.226***supported
*** represents a significant change in p at the 0.001 level of significance.
Table 7. Results of testing chain mediation effects.
Table 7. Results of testing chain mediation effects.
PathEstimateS.E.LowerUpperp
TCE→DI→BI−0.0870.029−0.147−0.0360.001
TCE→PV→BI−0.1850.038−0.261−0.1110.001
TCE→DI→PV→BI−0.0550.016−0.091−0.0290.001
TCE→BI−0.3350.063−0.462−0.2160.001
Total mediating effect−0.3270.046−0.417−0.2350.001
Total Effect−0.6620.051−0.759−0.5550.001
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Xiao, C.; Deeprasert, J.; Jiang, S. Tourism Crisis Events Affecting Intention towards Forest-Based Health Tourism: A Structural Equation Model. Forests 2024, 15, 1324. https://doi.org/10.3390/f15081324

AMA Style

Xiao C, Deeprasert J, Jiang S. Tourism Crisis Events Affecting Intention towards Forest-Based Health Tourism: A Structural Equation Model. Forests. 2024; 15(8):1324. https://doi.org/10.3390/f15081324

Chicago/Turabian Style

Xiao, Chan, Jirawan Deeprasert, and Songyu Jiang. 2024. "Tourism Crisis Events Affecting Intention towards Forest-Based Health Tourism: A Structural Equation Model" Forests 15, no. 8: 1324. https://doi.org/10.3390/f15081324

APA Style

Xiao, C., Deeprasert, J., & Jiang, S. (2024). Tourism Crisis Events Affecting Intention towards Forest-Based Health Tourism: A Structural Equation Model. Forests, 15(8), 1324. https://doi.org/10.3390/f15081324

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop