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Assignment Requirmetns-
Introduction
In the wake of the global upheaval caused
Assignment Requirmetns-
Introduction
In the wake of the global upheaval caused by the COVID-19 pandemic, the Asian travel and tourism industry has emerged as a beacon of resilience, displaying a steady recovery. According to the latest insights from the World Travel & Tourism Council (WTTC), the region is anticipated to experience a substantial boost in travel revenue, contributing 32% more to its GDP by 2025 compared to the pre-pandemic era. This surge is surpassed only by the Middle East, with a projected increase of 30%. Equally significant is the WTTC’s foresight into the global travel industry, estimating the creation of 126 million new jobs in the coming decade. What makes this forecast particularly noteworthy is that approximately 65% of these new employment opportunities are expected to materialize in the Asia-Pacific region. Clearly, the Asian travel and tourism sector is set to play a leading role in shaping the employment landscape of the future.
The purpose of this article analysis is to investigate the current issues and challenges faced by Asian countries in the realm of travel and tourism. We will also explore the sustainable tourism practices being employed in the region, as identified through academic research articles. Through this examination, we aim to gain a comprehensive understanding of the factors influencing the industry’s growth, the hurdles it confronts, and the strategies employed to ensure sustainability in the face of evolving global dynamics. Embark on this academic journey with a curious mind, ready to dissect and understand the intricacies of the Asian travel and tourism industry as we navigate through contemporary research findings. Your engagement with this analysis will not only enhance your understanding of the subject but also contribute to a broader discourse on the future of travel in one of the most dynamic regions of the world.
The guidelines below outline the steps for analyzing and reporting on each research article, as well as formatting the paper you will be submitting by the due date. Following these guidelines will help you achieve the best outcome for your assignment. If you have any questions about the instructions, feel free to reach out to me anytime.
Analyzing Article Guidelines
1. Clearly Define Research Questions/Issues – Introduction section:
• Begin your report by clearly stating the research questions or issues that the article aims to address.
• Provide a brief rationale for why these questions are both interesting and essential in the context of travel and tourism.
2. Summarize Previous Studies – Literature Review section
• Study Findings
a) Provide a concise summary of relevant literature, highlighting key findings from previous studies;
b) Discuss how these findings contribute to the existing knowledge in the field.
• Identify Business Problems/Issues/Challenges
a) Clearly outline the business problems or issues addressed in the reviewed literature;
b) Emphasize the gaps or limitations in previous research that the article seeks to address.
3. Describe the Results and Conclusion – Results and Conclusion Sections
• Clearly articulate the key outcomes and insights obtained from the study.
• Clearly communicate the implications of the results and conclusion, avoiding unnecessary technical details.
4. Study Implications
• Analyze Strategic Implications for Travel and Tourism
a) Discuss practical applications of the study’s results for the development of the travel and tourism sector;
b) Consider how industry stakeholders can leverage these findings for decision-making;
c) Analyze the broader strategic implications of the research on the travel and tourism industry;
d) Explore potential challenges and opportunities that may arise based on the study.
Passage-
When destination attractiveness shifts in response to climate change: tourists’ adaptation intention in Taiwan’s Kenting National Park
Wei-Ching Wang, Chung-Hsien Lin, Wen-Bor Lu and Su-Hsin Lee
ABSTRACT
We tested a structural model that integrates protection motivation theory with the individual’s (farmer’s) climate change adaptation process. The model helps us grasp the effects of climate change perception and hypothetical shifts in destination attractiveness, as well as threat and coping appraisals in light of tourists’ adaptation intentions in coastal destinations. We collected a total of 333 on-site valid questionnaires from domestic tourists at Kenting National Park in Taiwan and analysed the structural relationships in the aforementioned study constructs using structural equation modelling. Our findings show that when tourists have a higher level of perception regarding global climate change, they believe that destination attractiveness will decrease. When presented with scenarios of hypothetical shifts in destination attractiveness, tourists with higher levels of adaptation intention will perceive greater levels of threat to tourism behaviours, as well as higher effectiveness in adaptive measures. We confirmed that the proposed theoretical framework for tourists’ adaptation intention toward climate change is useful; the framework also sheds light on tourists’ acknowledgement of hypothetical alterations in destination attractiveness caused by climate change, in addition to their psychological adaptations. We discuss theoretical and practical implications.
Introduction
As climate change awareness grows, tourism systems stakeholders’ perception toward adapting to climate change has become an important research topic (Hopkins, 2014; Morrison & Pickering, 2013). Climate change, as defined by the Intergovernmental Panel on Climate Change (IPCC) refers to ‘any change in climate over time, whether due to natural variability or as a result of human activity’ (IPCC, 2007, p. 871). The IPCC defines adaptation as the ‘adjustment in natural or human systems in response to actual or expected climatic stimuli or their effects, which moderates harm or exploits beneficial opportunities’ (IPCC, 2007, p. 869). In Southeast Asian countries like Taiwan, Japan, and Korea, the most popular tourist and outdoor recreation destinations are coastal and marine environments (United Nations World Tourism Organization, 2013). Extreme weather events, along with major changes in climate frequency and intensity, have been observed in Taiwan (Hong, 2012; Yeh, 2014; Zhuo & Lu, 2014). Such events in the near future, such as rising sea levels and seawater temperature, could impact the country’s coastal regions (Dai, 2002; Lee, 2008).
For coastal destination management organizations (DMOs), understanding tourists’ adaptation behaviour in response to climate change is becoming increasingly important (Martinez et al., 2014; Schliephack & Dickinson, 2017). Weather is a situational variable that can influence tourists’ choice of destination (Woodside & Lysonski, 1989). Furthermore, climate change may cause tourists’ behaviours to shift, like by substituting their tourist destination for another one, engaging in other activities, or reducing the length of their trip (Dawson, Havitz, & Scott, 2011). In the existing tourism literature, psychological factors influencing tourists’ adaptation to climate change have been neglected, and our understanding of their adaptation behaviour remains limited (Cocolas, Walters, & Ruhanen, 2016; Jopp, DeLacy, & Mair, 2010). The impact of climate change on the sustainable development of numerous tourist destinations has been evaluated to understand tourists’ adaptive behaviours (Gössling, Scott, Hall, Ceron, & Dubois, 2012).
By reviewing the literature on climate change in other fields, we can see that researchers have applied the individual’s (farmer’s) climate change adaptation process (Bryant et al., 2000) or protection motivation theory (PMT) (Lam, 2015) to investigate people’s adaptive behaviours and intentions. The form of PMT proposed by Rogers (1975) states that when individuals receive information on threats (e.g. climate change), they go through the cognitive mediating process before engaging in adaptive/maladaptive coping actions, which are then determined by their adaptation intention (i.e. protection motivation). Conversely, intention can be predicted using threat appraisals and coping appraisals. Dang, Li, and Bruwer (2012) successfully applied PMT to model the farmer’s adaptation intention toward climate change. In their vulnerability assessment of coastal tourism, Moreno and Becken (2009) revealed that most studies on the individual’s adaptive behaviours to climate change fail to consider climate change’s impact on attributes of concern (e.g. destination attractiveness in tourism systems), which in turn affects the system’s sensitivity (e.g. destination attractiveness in tourism systems).
Bryant et al. (2000) suggested that the adaptation process toward climate change includes characteristics of stress (e.g. climate change perception), the system’s scale (e.g. destination, region, country), and other components that could affect the final adaptive response (e.g. crop insurance, crop choice). Bryant et al. (2000) believe that a better understanding can be gleaned by examining the relationships among factors that influence adaptation intention. Lam’s (2015) study on the farmer’s adaptation intention toward climate change has verified this view. However, this research on the process of adaptation intention does not consider the individual’s psychological and cognitive factors (Bujosa, Riera, & Torres, 2015; Landauer, Haider, & Pröbstl-Haider, 2014).
We believe that the current understanding of tourists’ adaptation intention toward climate change is limited for two reasons. First, tourism researchers have not yet adequately expressed the importance of tourists’ adaptation intention process toward climate change; some evidence suggests that adaptation intention could encourage adaptive behaviours (Horng, Hu, Teng, & Lin, 2014). The notion of adaptation intention must be expanded to other systems (e.g. tourism systems) and contexts (e.g. coastal destinations) to deepen our understanding of the individual’s adaptation behaviour (Gössling et al., 2012; Moreno & Becken, 2009). Second, past studies have conducted scenario analyses to explore whether hypothetical shifts in destination attractiveness that are induced by climate change within tourism systems contribute to tourists’ climate change adaptation. Findings indicate that coastal destination attributes have been among the determining factors of tourists’ climate change adaptation (Bujosa et al., 2015). However, these studies have called for further research on coastal destinations in different climate zones for a broader understanding of the effects of destination-managed realignment for tourist responses (Schliephack & Dickinson, 2017).
PMT and the individual’s climate change adaptation processes have been examined separately. In light of our knowledge, we believe that PMT and the abovementioned process have not yet been integrated. The use of a comprehensive framework in this study is desirable for the following reasons. First, the characteristics of systems in an individual’s process of adapting to climate change, and the cognitive mediating factors of PMT, can mutually compensate for the respective shortcomings in these two theories. Second, past studies on tourist behaviour commonly use the influential relationship among different psychological factors to predict future behaviour (e.g. Fishbein & Ajzen, 1975; Woodside & Lysonski, 1989). This will address concerns raised previously by numerous researchers. Therefore, we believe that the formation of tourists’ adaptation intention regarding destinations must be determined by the characteristics of stress (i.e. climate change perception), the features of tourism systems (i.e. hypothetical shifts in destination attractiveness), and the cognitive mediating process (i.e. threat and coping appraisals) (Wang, 2015).
Past research has revealed how tourism stakeholders recognize the potential impacts of climate change and their adaptation strategies (Hopkins, 2014; Morrison & Pickering, 2013). Previous studies have also enhanced our understanding of the factors that influence adaptation intention toward climate change (Cocolas et al., 2016; Dawson et al., 2011; Jopp et al., 2010). Few studies have explored the structural relationships among tourists’ adaptation intention, climate change perception, and hypothetical shifts in destination attractiveness, as well as threat and coping appraisals. Moreover, the climate change adaptation process may occur on different scales, including the individual, regional, national and international levels (Bryant et al., 2000). The adaptation process for each scale has its own qualities. Hence, the aforementioned structural relationships must be tested at a given destination. In this study, we focus on individual coastal destinations in order to expand our understanding of tourists’ climate change adaptation intention and the underlying factors. We propose a structural model that integrates PMT with the individual’s climate change adaptation process in order to examine the impact of climate change perception, hypothetical shifts in destination attractiveness and threat and coping appraisals on tourists’ adaptation intention (see Figure 1).
Figure 1. Proposed theoretical model for the study. Revised from farmer’s climate change adaptation process (Bryant et al., 2000). PMT (Floyd et al., 2000).
The contributions of this study are two-fold. First, this study expands the literature on tourists’ climate change adaptation intention, thereby clarifying the formation process of their adaptation intention by providing empirical evidence for relationships among the concerned factors. Second, this study clarifies the roles played by a hypothetical shift in tourism systems’ destination attractiveness and the psychological factors of threat and coping appraisals in tourists’ adaptive behaviours to climate change. The results can serve as a reference for coastal DMOs in the formation and design of strategies for economic, social and environmental sustainable development.
Literature review
An integrated framework of tourists’ climate change adaptation process
Previous studies on adaptation to climate change in the tourism industry have mostly stressed strategies (e.g. Schliephack & Dickinson, 2017; Scott, de Freitas, & Matzarakis, 2009), measures (e.g. Bujosa et al., 2015), and influencing factors of adaptation (e.g. Cocolas et al., 2016). These studies have rarely discussed the formation of tourists’ adaptation intention. A literature review of research in other fields indicates that past research has already explored the farmer’s adaptation intention toward climate change using PMT. Bryant et al. (2000) reviewed the literature on the farmer’s adaptation intention toward climate change in Canada, then collated and proposed a process for farmers’ adaptation intention toward climate change, with the following components: (1) characteristics of stress; (2) features of agricultural systems; (3) scales; (4) adaptive responses. ‘Characteristics of stress’ refers to climatic disruptions to which agricultural systems are sensitive, long-term changes in average climatic variables or elements of extreme weather events (e.g. type, size, frequency). ‘Features of agricultural systems’ refers to factors that can influence the sensitivity, adaptive capacity and responses of agricultural systems (e.g. local biophysical, cultural, and economic aspects). ‘Scale’ refers to the scale at which adaptive responses to climate change are analysed (i.e. farms and regional, national and international levels). ‘Adaptive responses’ refers to the different types of adaptations, including autonomous responses (e.g. delaying travel time to destinations and purchasing insurance) and conscious adaptation (e.g. introducing new technology, enhancing public facilities, and other public policy interventions).
The adaptation intention process described above is similar to past studies on climate change, which have mostly focused on physical environments and resources, but have not acknowledged the importance of cognitive factors in the adaptation process (Bujosa et al., 2015; Jopp et al., 2010). This process has increasingly received the attention of tourism researchers. Dawson et al. (2011) verified the importance of cognitive factors and found that, in poor snow conditions, highly committed skiers were more likely to change their skiing behaviour than less committed skiers.
PMT has previously been used as a socio-cognitive model to investigate individual adaptive behaviours and is among the main research theories on health protection behaviours (Floyd, Prentice-Dunn, & Rogers, 2000). Originally established to explain the connection between appeals to fear and attitude change, PMT proposes that people alter their attitudes out of fear to avoid the consequences of a threat or to prevent the occurrence of a threatening event (e.g. disease) (Rogers, 1975). Aside from PMT’s application in health risks, it has also been used to explain other behaviours such as consumer marketing communication (Cismaru & Lavack, 2006), farmer’s adaptation behaviours to climate change (Dang et al., 2012), and energy saving and carbon reduction behaviours in tourism (Horng et al., 2014). PMT is a general decision-making theory used to assess various types of threats (Maddux, 1993); it includes sources of information, the cognitive mediating process, and coping modes. ‘Sources of information’ refers to the environment that can be observed by individuals (e.g. friends and others) or their internal information (e.g. past experiences). Individuals engage in the cognitive mediating process when they are aware of information on a threatening event; this process involves a threat appraisal of event severity and the probability of occurrence, in addition to a coping appraisal of the individual’s ability to deal with and avoid the threat. Finally, based on the outcomes of the cognitive mediating process, people choose to perform adaptive or maladaptive behaviours. Moreno and Becken (2009) pointed out that tourism is an indispensable factor when considering climate change adaptation. Although PMT has been applied successfully to climate change adaptation in agriculture (e.g. Dang et al., 2012), PMT has not yet incorporated the concept of a tourism system. Moreover, PMT has not yet been applied to verify and explore tourists’ adaptive behaviours to climate change.
The present study integrates PMT and the individual’s climate change adaptation process, and presents a framework for tourists’ adaptation process. This framework is composed of the following: (1) characteristics of stress/sources of information (e.g. climate change perception); (2) features of systems (e.g. a shift in destination attractiveness); (3) cognitive mediating process (e.g. threat and coping appraisals); (4) adaptive responses/coping behaviour (tourist adaptation intention). Integrating the two theories allows a simultaneous consideration of the potential transformations induced by climate change in light of the qualities of tourism systems and possible cognitive mediating factors that these changes may generate from tourists. This helps us understand the formation process of tourists’ adaptation intention toward climate change. We conducted a literature review for the study constructs of this integrated framework.
Tourist adaptation intention (adaptive responses/coping behaviour)
Both PMT and the farmer’s climate change adaptation processes mention concepts that are similar to adaptation intention. For example, according to the adaptation process proposed by Bryant et al. (2000), adaptive responses include autonomous responses, such as the coping measures of individual tourists (e.g. delaying travel time to a destination, purchasing insurance) and conscious adaptations, such as government or public policy interventions for climate change. Similar to autonomous responses, in the form of PMT proposed by Floyd et al. (2000), ‘coping behaviors’ refers to the individual’s selection of adaptive responses. Within the context of this study, ‘adaptation intention’ is a type of autonomous response or coping behaviour that refers to an individual’s autonomous choice to conduct tourism behaviours involving climate change adaptation.
Reser, Bradley, Glendon, Ellul, and Callaghan (2012) defined ‘adaptation’ as the adjustments and adaptive responses or actions generated after individuals go through internal assessments, judgements, and processing when faced with environmental changes and threats. Many scholars have found that when investigating an individual’s behavioural occurrence/changes, behavioural intention can be used to predict the actual behavioural occurrence. If behavioural intention can be measured appropriately, the results obtained can approximate most actual behaviours (Fishbein & Ajzen, 1975). Woodside and Lysonski (1989) defined ‘behavioural intention’ as the individual’s subjective judgement of the probability that he/she would engage in a given behaviour, thus reflecting his/her willingness or desire to invest effort in that behaviour. Within the context of this study, ‘tourists’ adaptation intention’ refers to the potential adjustments made by individuals to their activities or behaviour during travel, in order to adapt to the probability of environmental changes in a destination caused by climate anomalies. A review of past literature related to climate change adaptation in the field of tourism indicates that most scholars accept that adaptation is a multidimensional concept. The substitution behaviour theory has been used to explain adaptation, divided into psychological and behavioural aspects (Dawson et al., 2011). ‘Psychological adaptation’ encompasses internal psychological processes (risk assessment, motivation response, coping decisions) that occur when individuals are faced with threats. These threats often relate to the harm caused by climate change to tourism systems (e.g. destination attractiveness) or people’s direct experience of extreme weather in their daily lives. ‘Behavioral adaptation’ refers to behavioural changes in tourists caused by climate change, including activity, spatial, or temporal substitution.
Climate change as a multidimensional notion has been explored by scholars from three angles: (1) technology, (2) management, and (3) behavioural adaptations (Scott et al., 2009). ‘Technological adaptation’ refers to coping methods for climate change and technology innovations to address vulnerabilities; it encompasses the costs and complexity of adaptive technologies and often requires government intervention (Jopp et al., 2010). Studies have found that tourists have opposing views of adaptive technologies used by destination operators. For example, in response to beach restoration in a coastal landscape, some tourists did not feel that beach replenishment was incongruous with the original landscape and were only concerned with the beach’s recreational value (e.g. sunbathing); other tourists were aware of the incongruity but could understand that the hotel was coping with the possible erosion of the beach owing to climate change, and thus were in favour of beach restoration measures (Buzinde, Manuel-Navarrete, Yoo, & Morais, 2010). ‘Management adaptation’ indicates attempts by stakeholders in tourism systems to alter their marketing methods, like reducing or increasing demand during specific tourism periods or re-directing tourists to different destinations and participate in different tourism activities (Schliephack & Dickinson, 2017). ‘Behavioral adaptation’ relates to tourism activities in which tourists decide to participate or the destinations they visit. However, behavioural adaptation is frequently influenced by technological and management adaptation (Jopp et al., 2010). Dawson et al. (2011) found that highly-involved tourists were more likely to engage in activity and temporal substitution; less involved tourists would engage in spatial substitution and choose a different skiing destination. Researchers have focused on different behavioural constructs, and climate change adaptation is commonly measured using multidimensional approaches.
Threat appaisals and coping appraisals (the cognitive mediating process)
Threat and coping appraisals are key psychological factors that influence adaptation intention toward climate change. They are also the main adaptation appraisal in the cognitive mediating process of PMT (Floyd et al., 2000). Scholars have defined ‘threat’ as an emotion generated when individuals face danger, or a motivation that drives them to avoid certain things (Tolman, 1923). In PMT, this concept is regarded as a relational construct that can evoke an individual’s responses to threatening stimuli and self-protection. It is necessary to formulate adaptation strategies for specific attributes of destinations that are undergoing alterations (Bujosa et al., 2015; Wall, 1998). As destination attractiveness might undergo changes because of the impacts of climate change, these changes can be viewed as threat in tourists’ adaptive behaviours (Schliephack & Dickinson, 2017). ‘Threat appraisal’ refers to the trade-off between the severity of the potential threat and vulnerability if the individual does not employ any protective measures. Within the context of this study, ‘threat appraisal’ refers to tourists’ perceived severity of the impact or interference by climate change on their tourism activities, and the probability or inconvenience of being affected. ‘Coping appraisal’ is the individual’s assessment of his/her ability to cope with or avoid threats, which includes response efficacy and self-efficacy. ‘Response efficacy’ refers to the individual’s ability to successfully reduce the threat if recommended measures to improve the situation are adopted (Rogers, 1975). Within the context of this study, ‘response efficacy’ refers to tourists’ willingness to follow recommendations to reduce or alter climate change in their tourism activities. Horng et al. (2014) recommended that by saving energy and water when travelling, tourists can reduce the threat of climate change. ‘Self-efficacy’ refers to the perceived ability of an individual to use adaptive responses. Within the context of this study, it refers to tourists’ perception that they can adopt recommendations to respond better to how climate change may affect their tourism activities. One example is the ability to employ eco-friendly tourism behaviours, as recommended by Jopp et al. (2010).
Hypothetical shifts in destination attractiveness (the characteristics of systems)
Destination attractiveness is among the main components of tourism systems (Gunn, 1993). Tourists travel to different destinations to enjoy the attractions or natural features (Uyarra et al., 2005). Researchers have found that weather is among the attractions of tourist destinations (Hu & Ritchie, 1993). However, because of the probability of abnormal changes in weather and climate, the climatic variables of numerous destinations have been reconfigured, leading to changes in destination attractiveness (Tervo-Kankare, Hall, & Saarinen, 2013). Hence, changes in destination attractiveness can be regarded as system features that are sensitive to the climate or are responses to climate change. ‘Destination attractiveness’ is defined as the combination between ‘the relative importance of individual benefits and the perceived ability of the destination to deliver individual benefits’ (Hu & Ritchie, 1993, p. 25). ‘Destination attractiveness’ can be understood as tourists’ perception of the ability of a destination to satisfy their holiday needs. The relative importance of different destination attributes will determine the evaluation of destination attractiveness. Based on the above definition, this study defines the hypothetical shifts in destination attractiveness as a possible alteration in a destination’s environmental attributes owing to the effects of climate change; these may mitigate the destination’s ability to satisfy tourists’ specific destination or holiday needs.
According to the views of Thach and Axinn (1994), destination attractiveness is composed of core and augmented attributes. In previous studies related to possible alterations in the features of coastal destinations due to climate change, the core dimensions of coastal destination attractiveness include terrestrial and marine attributes such as natural settings, scenery, beaches, and water (e.g. Uyarra et al., 2005). In contrast, the augmented dimensions encompassed functional/essential attributes that can influence tourists’ assessment of the core attributes, including general and niche facilities (e.g. Williams, 2011) such as the proximity of toilets and café amenities, beach access from car parks, and the availability of beach huts. However, the hypothetical shift in coastal destination attractiveness has been viewed as the collection of effects on tourism functions. Within the context of climate change, this viewpoint might be too limited because changes in destination vulnerability would cause tourists to form different levels of psychological threat according to different climatic variables (Moreno & Becken, 2009). Many researchers have also supported this idea (Scott, Hall, & Gössling, 2012), even though the functions of essential destination attributes remain crucial among certain tourists (Williams, 2011).
Since climate change involves persistent accumulation during a long period of time (U.S. EPA, 2013), past studies have commonly employed scenario analysis based on climate change’s negative impacts on the environmental attributes of a destination, so as to understand changes in visitors’ opinions to hypothetical shifts in destination attractiveness. Uyarra et al. (2005) presented tourists with hypothetical changes involving severe coral bleaching and mortality, and a large disappearance of beach land owing to a rise in sea level. They found that if the environmental attributes preferred by tourists (e.g. coral reefs and beaches) were affected by climate change, their willingness to revisit tropical islands would lessen drastically. Their study is similar to those that have examined adaptive behaviours using hypothetical changes in destination attributes, or attractiveness due to climate change; for example, the vulnerability of coastal sites (Moreno & Becken, 2009) or the willingness to revisit skiing destinations (Tervo-Kankare et al., 2013).
Climate change perception (the characteristics of stress/sources of information)
Climate change perception is another acknowledged determinant of tourist adaptation (Morrison & Pickering, 2013). ‘Weather’ refers to atmospheric conditions within a specific location or time and includes atmospheric temperature and pressure, wind speed and direction, and precipitation. Climate is the concept of average weather and is a generalized phenomenon (Gómez-Martín, 2005). Climate change refers to significant variations in the climate over the course of an extended period (U.S. EPA, 2013). Spence, Poortinga, Butler, and Pidgeon (2011) defined ‘climate change perception’ as people’s beliefs, ideas, and impressions toward the climatic features of extreme weather events, or climatic interferences that are greater than long-term changes in the average climatic variables. In general, tourists can experience climate change via mass media (newspapers and magazines), friends and family, or in person to obtain information on significant long-term shifts in weather attributes or climatic features at a tourist destination. The formation of tourists’ climate change perception involves the information processing of abnormal atmospheric temperature, rainfall, humidity, or other climate indicators at a tourist destination (Smith, 1993).
Belle and Bramwell (2005) say that tourists all hope to engage in tourism activities in ‘good weather’. Also, temperature and other climatic variables are key influencing factors in tourists’ decision-making; these factors affect their choice of destination (Jeuring & Peters, 2013; Woodside & Lysonski, 1989). For some tourists, identified desired climatic variables is a major reason to visit a given destination (e.g. Williams, 2011). Due to the differences in tourists’ personal characteristics or views on weather or climatic variables, they might use various methods to assess climate change and hence have different climate change perceptions (Spence et al., 2011; Tervo-Kankare et al., 2013). Denstadli, Jacobsen, and Lohmann (2011) suggested that thermal, aesthetic, and physical sensations support the perception of summer weather in Scandinavia. In addition, the perception of most tourists is formed by their experiences of local weather when engaging in activities and experiences at the destination. Gómez-Martín (2005) found that different tourist activities led to varying climate needs. Interestingly, Landauer et al. (2014) believe that the people’s climate change concept is a social construct; it could be developed based on potential conflicts in society or opposing methods and other forms of discourse to establish adaptive strategies or behaviours. Hence, although the difference in tourists’ climate change perception is a type of subjective assessment, its presence is fairly important for climate change adaptation (Reser et al., 2012). Gonzalez (2012) and Tervo-Kankare et al. (2013) advocate that more research is needed to understand tourists’ climate change perception of destinations or activities in different climate zones.
Methodology
Proposed theoretical model
Based on the theories and review of empirical studies mentioned above, we developed an integrated model using perception of climate change as the exogenous construct; tourists’ adaptation intention as the endogenous construct; and hypothetical shifts in destination attractiveness, threat appraisals, and coping appraisals as the mediating constructs. Six hypotheses were proposed, in support of this model (see Figure 1).
The relationship between climate change and hypothetical shifts in destination attractiveness has been examined in many previous studies. Nyaupane and Chhetri (2009) found that rich biodiversity and natural landscapes were the main attractions for tourists who engaged in mountain tourism; the attractiveness of mountrainous regions has altered because of changes in the climatic characteristics. Moreno and Becken (2009) and Scott et al. (2012) had similar findings. Therefore, we put forward the following hypothesis:
H1: Climate change perception has a significant positive relation with hypothetical shifts in destination attractiveness.
In the literature on climate change and tourism, evidence supporting the relationship among hypothetical shifts in destination attractiveness, threat appraisal, and coping appraisal are reported. However, certain researchers have observed that climate change could lead to changes in destination attractiveness (Nyaupane & Chhetri, 2009), and could thus be used to assess threat and coping appraisals in tourist adaptation (Schliephack & Dickinson, 2017). Based on the observations from the above studies, we inferred the following hypotheses:
H2: Hypothetical shift in destination attractiveness has a significant positive relation with threat appraisal.
H3: Hypothetical shift in destination attractiveness has a significant positive relation with coping appraisal.
Studies have explored the relationships among threat appraisal, fear appraisal, and tourists’ adaptation intention toward climate change. However, many scholars have attempted to verify these relationships in other fields. Prentice-Dunn, Mcmath, and Cramer (2009) found that, when college women understood the severity and coping methods of threats (how skin cancer can harm or threaten their lives), they transitioned from pre-contemplation to contemplation of healthy sun behaviours. Horng et al. (2014) found that a coping appraisal was better than a threat appraisal in predicting the subsequent energy-saving behavioural intention among tourists. Additionally, when tourists are presented with the threat of climate change, as well as actual adjustments and responses to environmental impacts, they often adjust their subsequent behaviours due to mediation in their internal psychological processes (Scott et al., 2009). Prentice-Dunn et al. (2009) proposed that, in threatening situations, people’s attitudes might be reinforced, causing coping strategies to become more prominent. The relationship between threat appraisals and coping appraisals has not been verified. According to the results and recommendations of empirical studies on the relationships among threat appraisals, coping appraisals, and adaptation intention in PMT, we formulated the following hypotheses.
H4: A threat appraisal has a significant positive relation with a coping appraisal.
H5: A threat appraisal has a significant positive relation with tourists’ adaptation intention.
H6: A coping appraisal has a significant positive relation with tourists’ adaptation intention.
Study site and subjects
The data of previous studies, which have focused on tourists’ adaptations to the possible effects of climate change on a destination’s attributes, have been collected mostly from Western tourists travelling in Western countries (Landauer et al., 2014; Scott et al., 2012). Less attention has been paid to the hypothetical shifts in destination attractiveness of domestic and international tourist destinations in Asian countries. This is a large gap in the tourism literature. Currently, the Asian tourism market is the world’s fastest growing outbound market; it has increased by 27% from 2015 to 2016 (United Nations World Tourism Organization, 2016). A better understanding of cross-cultural differences in the field is not only important (Gössling et al., 2012) – it is imperative that scholars gradually begin to include non-Western views in their research.
The study sample was from Kenting National Park in southern Taiwan (Figure 2). From 2001 to 2016, the number of local tourists who were over 18 at the time and had spent at least one night at the destination was 5,834,294–6,341,160 person-time. It is among the most representative domestic tourist destinations in Taiwan (Kenting National Park, 2014a). The Guanshan sunset spot is among the 12 superb sunset spots around the world (CNN, 2017). In addition to its weather, the region also has coral reefs, sea-eroded and cliff terrains, and other geographical landscapes. It has a tropical climate that has nurtured its rich ecological morphology, and a large number of migratory birds arrive from the north for winter each year. Destinations with diverse tourism activities can mainly be divided into marine and terrestrial activities. Marine activities include sunbathing, recreational water activities, snorkelling and surfing. Terrestrial activities involve cultural, natural, and eco-environmental educational activities such as observing coral reefs, limestone terrains, or visiting lighthouses.
Figure 2. Study site.
Kenting National Park has a tropical climate, with an annual average temperature of 20°C to 28°C, and annual rainfall of about 2,200 mm. The rainy season is between May and October, while the dry season is between November and April (Kenting National Park, 2014b). There were two reasons for choosing this region as our study site. First, the tourism type of this region is predominantly coastal or ecological, and scholars have found that coastal or ecological resources are more susceptible to the effects of climate change (Moreno & Becken, 2009; Schliephack & Dickinson, 2017); for example, climate change has caused coral bleaching (Dai, 2002) and loss of coastline (Ministry of the Interior of Taiwan, 2017). Second, the impression of tourists about this region is clearly a summer destination (Taiwan Tourism Bureau, 2017). According to data on temperature and rainfall collected between 2001 and 2016 from the regional climate monitoring stations (Taiwan Central Weather Bureau, 2017a), the average temperature rises by 2.5°C in summer (June–August), and the average rainfall decreases by 25% in autumn and winter (September–February). A comparison of the climate data with the distribution of monthly tourists in the same period (Figure 3) indicates that tourists to Kenting National Park advance or postpone their time of travel depending on the increase in temperature and decrease in rainfall. For coastal destination management, knowing tourists’ adaptation to climate change in advance will allow them to prepare for future responses. Hence, this region is a representative study site.
Figure 3. Average month temperatures (in centigrades) and precipitation in kenting. 2001–2016.
Data collection
We collected data during randomly selected time periods (e.g. daytime, nighttime, weekdays and holidays) for three months, from July–October 2014. The survey period coincided with the seventh month of the traditional Taiwanese lunar calendar, known as the Ghost Month, during which tourists generally avoid water-based locations (e.g. Kenting). In addition, because of the gas explosions in Kaohsiung (a city that tourists may pass when travelling to the Kenting National Park) that led to several casualties, the intentions of tourists passing through Kaohsiung may be affected (Lee, 2014). All research interviewers wore name tags and carried their student IDs. They were located at sites where tourists engaged in water activities. The tourists closest to the interviewers were asked whether they would be willing to participate in our survey. If the participants were not willing, the interviewer approached the next participant. (Note that a limitations of the study is that the reasons for not participating were not collected.) If the participants were unclear regarding the questionnaire’s content, the interviewers explained the questionnaire and guided them on how to fill it out.
The research tool was an on-site self-administered questionnaire. The questionnaire included four major parts (Wang, 2015). First, climate change perception, which sought participant’s views on climate change. The items were based on the results of a study by Tiller and Schott (2013) on the contributions of tourism within a destination to global climate change. Twelve items were developed, and each item was scored on a five-point Likert scale (5 = strong agreement; 1 = strong disagreement). Second, hypothetical shifts in Kenting’s destination attractiveness. It comprised 12 items and was developed in a two-stage process that combined structured and non-structured methods. Since the effects of climate change may alter various destinations differently (Bujosa et al., 2015; Wall, 1998), we reviewed relevant literature to identify the key changes in the environmental or resource features of Kenting National Park that could be induced by climate change (Dai, 2002) and its main destination attractiveness (Kenting National Park, 2014b, 2014c; Pan, 2014; Yeh, 2014). Fifteen items were collected in this first stage. In the second stage, we gathered destination attributes important to tourists, and asked 30 local tourists, ‘What are the features of Kenting National Park that satisfy your tourism or activity needs?’ Sixteen items were collected in this stage. In order to compile a comprehensive list of hypothetical shifts in destination attractiveness, we combined the interview results and literature review and reference was made to the scenario analysis on the negative impact of climate change on destination attractiveness (Uyarra et al., 2005). The list was then modified based on a panel discussion by three tourism researchers. They removed repeated items and revised the appropriateness of the statements to fit the context of Taiwan. Thus, we formulated twelve items. When conducting the survey, we asked the participants: ‘Given the following changes in tourism characteristics of Kenting National Park due to climate change, how attractive would Kenting be to you as a destination for tourism?’ This part was measurement based on prior literature (Hu & Ritchie, 1993) and scored on a five-point Likert scale (5 = strong unattractiveness, 1 = strong attractiveness).
Third, threat and coping appraisals. We asked the participants for their views on threat and coping appraisals, given the changes in Kenting National Parks’ destination attractiveness (tourism features or characteristics). The items were based on studies by Plotnikoff and Higginbotham (1995); Cox, Koster, and Russell (2004); Kellstedt, Zahran, and Vedlitz (2008); and Reser et al. (2012), and included nine and seven items on threat and coping appraisals, respectively. Fourth, tourists’ adaptation intention. This part was created referring to the studies by Dawson et al. (2011); Denstadli et al. (2011); and Reser et al. (2012). We compiled 10 items, which were measured on a five-point Likert scale (5 = strong agreement, 1 = strong disagreement). The final part involved collecting data on the participants’ socioeconomic background (i.e. gender, age, marital status, education level, and average monthly household income) and personal experiences (i.e. main tourism activities in which they engaged and source of information on climate change). The research tool was written in Taiwan’s official language – traditional Mandarin Chinese. As the scales used were obtained from English studies, two colleagues who were fluent in both Mandarin Chinese and English, and who were familiar with the relevant literature, evaluated the face validity of the scales. The items in this study reflect those items that have been back translated from Chinese into English.
These constructs have rarely been explored in past tourism research, and specific items were based on pioneering research results and references from other fields. To ensure that the survey questionnaire could be read and understood easily by the general population, a pretest was conducted with 30 local tourists in the Kenting Coastal Destination who were selected by convenience sampling. The textual descriptions of a few items were revised based on the pretest results. In addition, previous studies on climate change perception, hypothetical shifts in destination attractiveness, and tourists’ adaptation intention have mostly remained a conceptual discourse and rarely mentioned the composition of its theoretical constructs. Hence, this study conducted a second questionnaire survey using convenience sampling. The survey was conducted in July 2014, including holidays and weekdays. Of the 350 questionnaires distributed, 320 valid questionnaires were returned. An exploratory factor analysis was performed to analyse and identify the latent factors of climate change perception, hypothetical shifts in destination attractiveness, and tourists’ adaptation intention. The factors obtained were used as indicators to measure these constructs. Implementing this procedure helped resolve the possible issues with multicollinearity among the indicators, or correlation among the indicator error variances during structural equation modelling (Bollen, 1989). After the data analysis, two cross-factor variables were removed from climate change perception. Two dimensions were extracted, namely ‘indirect perception’ (six items; α = 0.82) and ‘direct perception’ (four items; α = 0.75); the total variance explained was 55.93%. The hypothetical shift in destination attractiveness comprised two dimensions: ‘changes in terrestrial attractiveness (eight items; α = 0.85) and ‘changes in marine attractiveness’ (four items; α = 0.87). Tourists’ adaptation intention comprised three dimensions: ‘behavioural adaptation’ (five items; α = 0.78), ‘physical adaptation’ (three items; α = 0.74), and ‘psychological adaptation’ (two items; α = 0.60).
The theoretical model used to test the relationships proposed above was structural equation modeling (SEM), and the sample for analysis was limited to participants who: a) have perceived climate change; b) believed that if the destination attractiveness of Kenting Coastal Destination were to be altered by climate change, they would not travel there; and c) if they were to experience the hypothetical shifts in destination attractiveness (threat), they would adjust their tourism behaviours related to the Kenting Coastal Destination. Samples that had no concept of climate change, or did not meet the precondition of perceiving climate change as a tourism threat, were eliminated because adaptation is not possible in these participants.
Results
Of the 600 tourists who participated in this study, 556 agreed to complete the on-site survey, yielding a participation rate of about 93%. However, among the 556 questionnaires, 223 did not meet the qualification criteria for data analysis (e.g. did not perceive climate change, believed that the hypothetical shift in Kenting destination attractiveness would not affect tourism, no possibility of adaptation); thus, 333 questionnaires were analysed (60%). Among the valid samples, the gender distribution indicated that there were more women (58.4%) than men (41.6%); 66.4% of the sample were aged 22–40 years; marital status was almost the same between single (49.2%) and married (50.8%) participants. Most participants had university (undergraduate) education (64.8%), and their average monthly personal income was between TWD 30,000 and TWD 60,000 (47.1%). The demographic profile of the participants was consistent with the profile of domestic tourists visiting Kenting Coastal Destination (Hsu, Yeh, & Lin, 2013; Liu, Chia, & Chang, 2009; Wang, 2015). In addition, regarding the tourists’ sources of information on climate change, the most commonly used channels were television (45%), the internet (26.8%), and newspapers/magazines (25.7%). Most tourism activities in Kenting Coastal Destination were enjoying natural landscapes (42.2%) and engaging in recreational water activities (32.1%).
Measurement model testing
A confirmatory analysis was performed on the measurement structure for each latent construct of climate change perception, hypothetical shifts in destination attractiveness, threat appraisal, coping appraisal, and tourists’ adaptation intention, before analysing the measurement model (see Table 1). The measurement model’s adequacy was evaluated, based on its fitness indicators and the reliability and validity of construct components (discriminant and aggregation validities). The fitness indicators showed that all latent constructs had acceptable data fitness: climate change perception (2 dimensions, 10 indicators), hypothetical shifts in destination attractiveness (2 dimensions, 12 indicators), threat appraisal (2 dimensions, 9 indicators), coping appraisal (2 dimensions, 7 indicators), and tourists’ adaptation intention (3 dimensions, 10 indicators). The results showed that all latent constructs had a reliability above 0.7. Moreover, aggregation validity can be ensured if the factor loading of each indicator is two times higher than the standard error (Anderson & Gerbing, 1988). The target loadings in this study had significant t-values, ranging from 7.74 to 14.96, thus, verifying the aggregation validity of each latent construct. Moreover, the discriminant validity is established when the estimated variance among any group of variables is greater than the square of the correlation between two of the variables. The results demonstrated there was discriminant validity (Jöreskog & Sörbom, 1993).
Table 1. Means, factor loadings, and reliabilities for climate change perception, hypothetical shift in destination attractiveness, threat appraisal, coping appraisal, and tourists’ adaptation intention.
Scale Item Mean Factor loading Explained variance Cronbach’s Alpha
Climate change perception
Indirect perception (6 items)
0.81
Changing snow cover/glacier retreat
4.03
0.47
–
Significant change in the direction of ocean (sea) currents
3.72
0.82
11.17
Erosion/landslides
3.86
0.73
10.75
Rising sea level
4.04
0.74
10.81
Typhoons, significant changes in the number of typhoons
4.16
0.62
9.95
Change in air quality
4.19
0.58
9.64
Direct perception (4 items)
Change in weather patterns/temperature
4.44
0.75
–
0.75
Sun becoming more “dangerous”
4.45
0.72
14.23***
Significant change in rainfall
4.19
0.59
12.26***
Change in seasons
4.29
0.55
11.61***
Hypothetical shift in destination attractiveness
Changing attractiveness of land (8 items)
0.88
Less seafood available at higher prices
4.11
0.42
–
More rainy days and fewer chances for outdoor activities
4.27
0.71
9.46***
Poorer holiday atmosphere
4.12
0.61
8.95***
Poorer sand quality
4.37
0.69
9.40***
Smaller beach size
4.16
0.72
9.53***
High speed of downslope wind or higher temperature of foehn wind
4.25
0.68
9.33***
Hotter summer temperatures
4.04
0.56
8.63***
Poorer terrestrial landscape attractiveness
4.00
0.64
9.14***
Changing attractiveness of ocean (4 items)
0.87
Poorer coral cover
3.93
0.59
–
Lower fish abundance
4.00
0.80
14.96***
Lower fish diversity
3.97
0.87
14.39***
Poorer marine landscape attractiveness
4.18
0.79
14.28***
Threat appraisal
Severity (4 items)
0.72
I feel that the effects of climate change will severely alter the destination attractiveness of Kenting.
3.91
0.61
–
Changes in the destination attractiveness of Kenting is a bad thing.
3.85
0.54
10.42***
The destination attractiveness of Kenting will interfere with the tourism behaviour in Kenting.
3.67
0.70
12.50***
I feel that changes in the destination attractiveness will severely affect the tourism behaviour in Kenting.
3.59
0.63
11.68***
Vulnerability (4 items)
0.74
I believe that changes in the attractiveness of Kenting has a high chance of affecting my tourism behaviour in Kenting.
3.71
0.65
–
I believe that changes in destination attractiveness will easily affect my tourism behaviour in Kenting.
3.74
0.65
12.47***
Compared with other tourists, my tourism behaviour in Kenting is easily affected by changes in destination attractiveness.
3.58
0.49
9.87***
Because of changes in destination attractiveness, I am worried that the season or method of travel to Kenting will change.
3.66
0.55
10.97***
Coping appraisal
Response-efficacy (3 items)
0.75
Green tourism will reduce the changes in the destination attractiveness of Kenting.
3.84
0.49
–
Green tourism will improve the changes in the destination attractiveness of Kenting.
3.72
0.54
8.56***
Public tourism could change the destination attractiveness of Kenting to be more severe.
3.90
0.54
8.61***
Self-efficacy (4 items)
0.70
My green tourism behaviours in Kenting will reduce the changes in the destination attractiveness.
3.98
0.54
–
I can adjust my tourism behaviours in Kenting to reduce the changes in the destination attractiveness.
3.66
0.43
7.74***
I believe my tourism behaviours have an influence on the changes in the attractiveness of Kenting.
3.67
0.55
9.17***
Human beings are responsible for changes in the destination attractiveness of Kenting.
4.20
0.53
8.94***
Tourist’s adaption intention
Behavioural adaption intention (5 items)
0.76
I left Kenting sooner than planned.
3.61
0.53
–
Stop tourism activities in Kenting for some seasons
3.34
0.63
9.69***
Engage in substitute tourism activities in this destination
3.62
0.46
8.11***
Engage in tourism activities less often in Kenting
3.43
0.70
10.08***
Engage in tourism activities elsewhere (in Taiwan)
3.80
0.50
8.51***
Physical adaption intention (3 items)
0.76
Find shaded areas in Kenting to engage in tourism activities
3.98
0.49
–
Bring sunshade items (e.g. hats, umbrellas) when travelling to Kenting
4.03
0.86
10.23***
Bring items to adjust body temperature when travelling to Kenting (sweat-wicking clothes, cooler clothes)
3.99
0.76
10.69***
Psychological adaption intention (2 items)
0.72
Media reports have made me think of the impacts of changes to the attractiveness of Kenting.
3.74
0.74
–
I think of the impact that the changes to the destination attractiveness of Kenting will have on its sustainable development.
3.84
0.67
8.04***
Note: p < .05; **p < .01; ***p < .001.
According to the two-step procedure recommended by Anderson and Gerbing (1988), we used the LISREL 8.52 software (Jöreskog & Sörbom, 1993) to test the hypothesized relationships among the variables influencing tourists’ adaptation intention. The first step required the validation of the measurement model comprising climate change perception (two composite indicators), hypothetical shifts in destination attractiveness (two composite indicators), threat appraisal (two composite indicators), coping appraisal (two composite indicators), and tourists’ adaptation intention (three composite indicators). The adequacy assessment of the measurement model indicated that the model had rational data fit (χ2 = 70.62, df = 34, χ2/df = 2.08, p < .01, SRMR = 0.027, RMSEA = 0.042, NNFI = 0.98, CFI = 0.99). The composite reliability of climate change perception, hypothetical shifts in destination attractiveness, threat appraisal, coping appraisal, and tourists’ adaptation intention were 0.72, 0.73, 0.79, 0.75, and 0.75, respectively. The values were all above 0.7, indicating an acceptable level of reliability. In terms of validity, the t-values for the loadings of each indicator reached statistical significance (p < .001) and were all above 0.5, thus, providing evidence for aggregation validity (Anderson & Gerbing, 1988). In addition, discriminant validity was tested; the results supported the discriminant validity of the five latent constructs. The measurement model has thus been validated and be utillised in subsequent structural model analysis.
Structural model testing
The second step was to conduct a path analysis of the research model. The results indicated χ2 = 108.81, df = 38, χ2/df = 2.86, SRMR = 0.055, RMSEA = 0.056, NNFI = 0.97, and CFI = 0.98. A composite evaluation of the fitness of all indicators showed that the sample data provided a good fit with the structural model; all path coefficients were significant and positive (see Figure 4). The results of the analysis supported the hypothesized relationships of climate change perception, hypothetical shift in destination attractiveness, threat appraisal, and coping appraisal with tourists’ adaptation intention. Hence, the six hypotheses were accepted: climate change perception has a significant positive relation to hypothetical shifts in destination attractiveness (β = 0.63; H1); hypothetical shifts in destination attractiveness has a significant positive relation to threat appraisal (β = 0.50; H2); hypothetical shifts in destination attractiveness has a significant positive relation to coping appraisal (β = 0.30; H3); threat appraisal has a significant positive relation to coping appraisal (β = 0.69; H4); threat appraisal has a significant positive relation to tourists’ adaptation intention (β = 0.48; H5); and coping appraisal has a significant positive relation to tourists’ adaptation intention (β = 0.32; H6) (Table 2). Overall, the results indicated that climate change perception, hypothetical shifts in destination attractiveness, and threat and coping appraisals are important determinants of tourists’ adaptation intention. Moreover, hypothetical shifts in destination attractiveness, and threat and coping appraisals were mediating variables in the relationship between perception of climate change and tourists’ adaptation intention. The squared multiple correlation (R2) was 58% of our target construct, that is, adaptation intention, which implies that significant constructs in the model can explain the more than 58% of variance in adaptation intention.
Figure 4. Structural model with estimated path coefficients.
Table 2. Summary of structural model.
Hypothetical shift indestination attractiveness Threat appraisal Coping appraisal Tourist’s adaption intention
Climate Change Perception
Direct effect
0.63
–
–
–
Indirect effect
–
–
–
Total effect
0.63
0.32
0.41
0.28
Hypothetical shift in destination attractiveness
Direct effect
–
0.50
0.30
–
Indirect effect
–
–
0.35
0.45
Total effect
–
0.50
0.65
0.45
Threat appraisal
Direct effect
–
–
0.69
0.48
Indirect effect
–
–
–
0.22
Total effect
–
–
0.69
0.70
Coping appraisal
Direct effect
–
–
–
0.32
Indirect effect
–
–
–
–
Total effect
–
–
–
0.32
Conclusion and implications
Conclusion
The aim of this study was to develop and validate a structural model with a theoretical basis that integrates PMT with individual’s (farmer’s) adaptation process within the context of climate change. The model’s purpose was to explain the adaptation intention of tourists and the interrelationships of tourists’ adaptation intention with climate change perception, hypothetical shifts in destination attractiveness, and threat and coping appraisals. The results suggest that (a) there are two direct effects on tourists’ adaptation intention: threat and coping appraisals; (b) threat appraisal had one indirect effect on tourists’ adaptation intention: coping appraisal; (c) hypothetical shifts in destination attractiveness had two indirect effects on tourists’ adaptation intention: threat and coping appraisals; (d) climate change perception had three indirect effects on tourists’ adaptation intention: destination attractiveness, threat, and coping appraisals; and (e) climate change perception and hypothetical shifts in destination attractiveness were both multidimensional constructs. These results support the findings of the existing literature, emphasizing the importance of climate change perception, hypothetical shifts in destination attractiveness, and threat and coping appraisals in the formation of tourists’ adaptation intention. However, these results also reveal that existing studies have neglected the complexity of tourists’ adaptation intention towards coastal destinations within the context of climate change. In this study, threat appraisal and hypothetical shifts in destination attractiveness were the most important predictors of adaptation intention. Additionally, vulnerability was the most significant dimension of threat appraisal, while changes in terrestrial and marine attractiveness were the most important dimensions in the hypothetical shifts in destination attractiveness. Therefore, future understanding of the process of t
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