what is tourist knowledge

57 UNDERSTANDING TOURIST BEHAVIOR IN A CHANGING ENVIRONMENT – Contributions by Astrid Kemperman

The travel and tourism industry is among the most affected sectors by the Covid-19 pandemic, with a massive fall in international tourism demand. While the industry is currently recovering, the World Tourism Organization argues that this fall in demand offers the opportunity to rethink the tourism sector and build back better towards a more sustainable, inclusive, and resilient sector that ensures that the benefits of tourism are enjoyed widely and fairly (UNWTO, 2021). Over the last decades, it has become clear that the growth of tourism brings significant challenges with it and is itself also influenced by for example climate change, pollution, decreasing natural resources, growing populations, and local and cultural differences. The negative environmental impacts of tourism are substantial: tourism puts stress on local land use, can lead to increased pollution, and more pressure on endangered species and the natural habitat. A more sustainable tourism approach would mean taking into account the current and future economic, social and environmental impacts, the preferences and needs of visitors, the industry, the environment, and host communities (UNWTO, 2021).

At the same time, recent technological and digital innovations also change the way people live, work, travel, interact with one another, and how they spend their free time. The borders between the digital, social, and physical environment are more and more intertwined. Technological advances, information dissemination, the influence of social networks, and increasing available free time and monetary budgets have further strengthened the need to create sustainable development opportunities for the tourism industry to support and improve efficient destination planning, management, and local community empowerment and inclusiveness. Moreover, as argued by Gretzel and Koo (2021), these technological developments lead to a convergence of urban residential and touristic spaces, and there is value in merging so-called smart tourism and smart city planning and management development goals to serve both residents and tourists in the best possible ways.

Research is needed to test the possible impact of new technology on tourists, their needs, preferences and activities, social relationships, and interaction with the environment. These considerations drive my general research aim: to develop a deeper understanding of individuals’ needs, preferences, and spatial activity patterns within the context of the digital, social, and physical environment to help find solutions for these challenging problems. In this chapter, a concise overview of my research, from the past to present and some new ideas are presented and discussed, as shown in figure 1:  investigating tourist choice behavior within a changing digital, social and physical environment to support planning and design of environments that enhance tourist experiences and quality of life.

Facets of tourist choice behavior

Central in my research over the years is understanding and adding to knowledge on tourist choice behavior, and I have been doing so taking a quantitative research approach using advanced data collection methods (e.g., dynamic stated choice experiments) and modeling approaches (e.g., discrete choice modeling, Bayesian Belief Network models). Tourists make a variety of choices including whether or not to travel, destination choice (e.g., Kemperman, Borgers & Timmermans, 2002b), transport mode choice (e.g., Grigolon, Kemperman & Timmermans, 2012c), accommodation choice (e.g., Randle, Kemperman & Dolnicar, 2019), trip duration choice (e.g., Kemperman, Borgers, Oppewal & Timmermans, 2003), and what activities to undertake while at a specific destination (e.g., Kemperman, Joh, & Timmermans, 2004). However, when explaining and predicting tourist choice behavior a variety of unique properties need to be taken into account. Over the years I have investigated some of these aspects.

First, compared to other types of choices like transport mode choice, tourists are inclined to show variety-seeking behavior in their choices over time, meaning that a time-invariant preference function is not reasonable (Kemperman, 2000). Variety seeking behavior in tourists may be influenced by a variety of factors such as availability of choice alternatives or changes in their characteristics, differences in decision-making contexts, different choice motivations, different travel party group composition or travel companions, and in general a basic desire for novelty (Kemperman, Borgers, Oppewal and Timmermans, 2000). Specifically, a discrete choice model of theme park behavior including seasonal and variety-seeking effects is proposed and estimated and the external validity of the model is assessed leading to accept the hypothesis that tourists differ in their preferences for theme parks by season and show variety-seeking behavior over time (Kemperman, Borgers & Timmermans, 2002b).

In general, tourist choices, certainly compared to for example commuter choices, are made less frequently, represent high-involvement decisions, often include multiple choice facets, the decision process may take longer, and they might be based on well-established long-term agendas (Grigolon, 2013).  A portfolio choice experiment concerning the combined choice of destination type, transport mode, duration, accommodation, and travel party for vacations is developed (Grigolon, Kemperman & Timmermans, 2012b). Specifically, the influence of low-fare airlines on the portfolio of vacation travel decisions of students is investigated. The findings confirm earlier studies that conclude that travel-related decisions for tourists, in general, are multi-faceted and not only related to the destination itself (e.g., Dellaert, Ettema, & Lindh, 1998; Jeng & Fesenmaier, 1997; Woodside & MacDonald, 1994).

In another study, based on revealed data about vacation history in terms of the long holidays of a sample of students, interdependencies in the vacation portfolios and their covariates are explored using association rules (Grigolon, Kemperman & Timmermans, 2012a). The portfolios include joint combinations of destination, transport mode, accommodation type, duration of the trip, length of stay, travel party, and season. Results show and confirm dependencies between vacation portfolio choice facets and their covariates. These insights provide a better understanding of tourist choice behavior and the context in which choices are made and can support policy and planning decision-making.

Tourist activity choices

When tourists are at a destination or in a city there is the timing and sequencing of tourists’ activity choices. Over-usage and congestion of specific attractions or facilities are difficult to avoid and may cause severe problems for a destination or city. For destination planning and management, it is important to understand how tourists behave in time and space, how the demand for various activities and attractions fluctuate over time, and how they can be accommodated and directed.

One of my first studies on this topic (Kemperman, Borgers & Timmermans, 2002a) introduces a semi-parametric hazard-based duration model to predict the timing and sequence of theme park visitors’ activity choice behavior that is estimated based on observations of tourist activity choices in various hypothetical theme parks. The activities include a description of the activity/attraction as well as their waiting time, activity duration, and location. The main findings support the prediction of how the demand for various activities is changing during the day and how the visitors are distributed over the activities in the park during the day. This information is relevant for visitor use planning to optimize the theme park experience.

In another study on visitors’ activities undertaken while tourists are at a destination, we focus on interrelated choices of tourists, multi-dimensional activity patterns as opposed to particular isolated facets of such patterns (Kemperman, Joh, & Timmermans, 2004). Moreover, in this study, it is tested whether activity patterns of first-time visitors tend to differentiate from the activity patterns of repeat visitors, mediated by their use of information. Differences between the two groups are assumed to be reduced when first-time visitors use information about the available activities and the spatial layout of the theme park. Specifically, the sequence alignment method is applied to capture the sequence of conducted activities. We conclude that the activity patterns of the two groups do differ, first-time visitors follow a very strict route in the park as indicated by the theme park, while repeat visitors have a more diverse order in their activity pattern. However, the difference between the two groups is reduced when first-time visitors use information about the available activities and the spatial layout of the park.

In an aim to measure and predict tourists’ preferences for combinations of activities to participate in during a city trip, a personalized stated choice experiment is developed and binary mixed logit models are estimated on the choice data collected (Aksenov, Kemperman & Arentze, 2014). An advantage of this approach is that it allows estimation of covariances between city trip activities indicating whether they would act as complements or substitutes for a specific tourist in his/her city trip activity program. The model provides information on combinations of activities and themes that tourists prefer during their city trip and that can be used to further fine-tune the recommendations of city trip programs and optimize the tourist experience.

As shopping is one of the most important activities for tourists, we also investigate shopping route choice behavior in a downtown historic center, including the motivation for the shopping trip, familiarity with the destination, and whether the shopping route through the downtown area is planned or not before the visit (Kemperman, Borgers, & Timmermans, 2009).  A model of tourist shopping behavior is proposed and estimated to investigate differences in route choice behavior of various types of tourist shoppers. The results indicate that shopping supply and accessibility, some physical characteristics, and the history of the route followed are important factors influencing route choice behavior. Furthermore, it can be concluded that shopping motivations, familiarity with the area, and planning of the route affect tourist route choice behavior. The model allows investigating the effects of environmental characteristics on route choice behavior and assessing various future planning scenarios, such as changes in physical aspects in the downtown area, or changes in the supply of shops to optimize visitors’ shopping trips.

Social and physical environment and tourist choice behavior

The social environment including the social relationships and cultural milieus within which tourists interact and make their choices is intertwined with the physical, natural, and built environment in which tourists travel and their activities take place.

First, a study in which we explore children’s choices to participate in recreational activities and the extent to which their choices are influenced by individual and household socio-demographics, and characteristics of the social and physical environment (Kemperman & Timmermans, 2011). Travel and activity diaries of a large sample of children aged 4-11 years old in the Netherlands are used to collect data on out-of-home recreational activity choices and this data is merged with measures describing the social and physical living environment.  A Bayesian belief network modeling approach is used to simultaneously estimate and predict all direct and indirect relationships between the variables.  Results indicate that recreational activity choices are, among others, directly related to the socio-economic status of the household, the perceived safety of the neighborhood, and the land use in the neighborhood. Planners and designers are recommended to find a good land use mix, and specifically, make sure that they focus their attention on safety issues to stimulate children’s recreational activity choices.

In a more recent study, we investigate with a stated choice experiment how different presentations of cause-related corporate social responsibility (CSR) initiatives affect holiday accommodation choices, with a specific focus on the relative importance of tourist involvement, the message-framing, and the donation proximity (Randle, Kemperman, & Dolnicar, 2019). In a tourism context, we see that an increasing number of organizations implement so-called social corporate responsibility (CSR) initiatives, meaning they give some of their benefits back to the local community, society and, or the environment and it is of interest to see whether tourists take these initiatives into account when making their choices and how messages are valued. We found that different market segments are affected differently by these SCR initiatives when choosing their holiday accommodation.  Specifically, there is one CSR-sensitive segment that cares about nature and the natural landscape, experiencing nature intensely, and efforts to maintain unspoiled surroundings and scores higher on community involvement than other segments. In general, it is found that negative message framing is the most promising option in terms of positively influencing tourist choices. It is concluded that although CSR initiatives do not appear to have a consistently positive effect on all tourist accommodation choice behavior, neither do they negatively affect demand. Specifically, it is advised to tailor CSR messages such that they are most effective in influencing the SCR-sensitive tourist segment.

Tourism can have an enormous environmental impact, and specifically, air travel negatively contributes to global carbon emissions. A voluntary carbon offset program supports airlines to take proactive measures to reduce the environmental impact. We have tested, using a stated choice experiment, the effectiveness of different communication messages to increase voluntary purchasing of carbon offsets by air passengers (Ritchie, Kemperman, & Dolnicar, 2021). Results indicate that tourists who book their flights prefer carbon offset schemes that fund local programs over international ones, that are effective in mitigating emissions, and are accredited. The willingness to pay for carbon offsets when booking for a group is lower than when booking an individual flight for oneself. Moreover, the tourist market can be divided into different segments with their characteristics, including age, employment status, frequent flyer membership, and flight behavior. Therefore, it is important to target the segments for aviation carbon offsetting by matching certain types of attributes and present an optimal program to each of the segments.

Integration of the digital environment in tourist choice behavior

Nowadays digital technologies can support tourists in making their choices, planning their trips, and optimizing their experiences (e.g., Buhalis, 1998; Gretzel, Mitsche, Hwang & Fesenmaier, 2004; Kemperman, Arentze, & Aksenov, 2019; Rodriguez, Molina, Perez & Caballero, 2012; Steen Jacobsen & Munar, 2012). We introduce this concept of ‘smart routing’ in the development of a recommender system for tourists that takes into account the dynamics of their personal user profiles (Aksenov, Kemperman, & Arentze, 2016). This smart routing concept relies on three levels of support for the tourist: 1) programming the tour (selecting a set of relevant activities and points of interests to be included in the tour, 2) scheduling the tour (arranging the selected activities and point of interests into a sequence based on the cultural, recreational and situational value of each) and 3) determining the tour’s travel route (generating a set of trips between the activities and point of interests that the tourist needs to perform to complete the tour). This approach aims to enhance the experience of tourists by arranging the activities and points of interest together in a way that creates a storyline that the tourist will be interested to follow and by reflecting on the tourists’ dynamic preferences.

For the latter, an understanding of the influence of a tourist’s affective state and dynamic needs on the preferred activities is required (Arentze, Kemperman, & Aksenov, 2018). Finally, the activities and points of interest are connected by a chain of multimodal trips that the tourist can follow, also in relation to their preferences and dynamic needs. Therefore, each tour can be personalized in a ‘smart’ way optimizing the overall experience of the trip. In the study, the building blocks of this concept are discussed in detail and the data involved, and finally, a prototype of the recommender system is developed.

C onclusion and future research

This chapter gives an overview of research that I have worked on over the years in collaboration with other researchers to develop a deeper understanding of tourists’ choice behavior and to generate insights and provide support for policy, planning, and managerial decision making in finding answers to the challenges the tourism industry and environment are facing. Specifically, examples of research are presented that tested in different ways facets of tourists’ needs, preferences, and spatial activity patterns within the context of a changing digital, social and physical environment.

Based on this overview some avenues for future research, in line with the presented framework in Figure 1, can be given. First, the studies presented show how tourist choices are influenced by their social and physical environment and that in understanding these choices it is important to take these aspects into account. Specifically, the social environment or social influence by family members, peers, or colleagues might also be an important additional explanatory facet in explaining tourist choices, for example in understanding and promoting the choice for sustainable tourist behavior. Research has also indicated that role of social media, online reviews, and social influencers have become increasingly important in the choices tourists make, and including the influence of someone’s social network, colleagues, peers, and family members in predicting tourist choice behavior is an interesting research opportunity (Kemperman, 2021).

The digital and technological developments support and improve other ways of data collection, for example by using virtual reality, simulators, or eye-tracking (e.g., Cherchi and Hensher, 2015; Kemperman, 2021).  Tourists are often unfamiliar with a specific destination or tourist service, and therefore presenting them with more visual, virtual reality or interactive choice options might be of interest to better measure their preferences and choice behavior. Moreover, virtual or augmented reality environments also allow testing the effects of interventions on tourist preferences and behavior before they are actually implemented. This is an advantage, specifically when high investments are involved.

Moreover, technological innovations support the collection of more and more types of so-called big data and this data can be very useful in tourism research (Li, Xu, Tang, Wang, & Li, 2018). Big data sources for tourism research come in a variety of forms, such as user-generated data (e.g.,  tweets, online photos), device data (e.g., GPS data, mobile phone data), and transaction data (e.g., online booking data, customer cards). These types of smart big data sources might be used to understand how inner-city visitors’ activity choices emerge and evolve in space and time to provide city managers and planners with important information for future management and planning such as visitor flows and clusters, and interesting locations (e.g., Beritelli, Reinhold & Laesser, 2020).

Finally, to conclude, there is a challenge for more research and evidence to further expand knowledge on tourist choice behavior and support optimizing tourists’ experiences and quality of life.

Written by Astrid Kemperman, Eindhoven University of Technology, The Netherlands

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Women’s voices in tourism research Copyright © 2021 by The University of Queensland is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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ORIGINAL RESEARCH article

How tourists’ perception affects travel intention: mechanism pathways and boundary conditions.

• 1 College of Economics, Southwest Minzu University, Chengdu, China
• 2 College of Historical Culture & Tourism, Southwest Minzu University, Chengdu, China
• 3 College of Earth Sciences, Chengdu University of Technology, Chengdu, China
• 4 Department of Anthropology, University of Wisconsin-Madison, Madison, AL, United States

Tourist subjectivities have an important effect on behavioral intentions. Under the background of normalization, tourism decision-making manifests primarily in tourists’ individual preferences, which has led much research to ignore the importance of other subjective factors, as well as objective environmental factors. In the COVID-19 era, tourism behavior’s social attributes have become more prominent; the effect of important others or organizations’ attitudes toward tourism behavior, as well as personal knowledge, ability, and experience in preventing and controlling tourism risks, are evident. This study integrates knowledge-attitude-behavior (KAB), Theory of Perceived Risk (TPR), Social Identity Theory (SIT), and Theory of Planned Behavior (TPB), along with a comprehensive framework method, to construct an integrated model exploring the impact of knowledge, identity, and perceived risk on travel intention, to analyze its pathways and effects, to resolve the issue of mechanism, to analyze the moderating effect of past travel experience, and to answer the problem of boundary conditions. It finds that knowledge, perceived risk, and identity have a significant positive impact on travel intention; travel attitudes, subjective norms, and perceived control mediate the influence of knowledge, perceived risk, and identity on travel intention; these mechanism pathways do not always exist. The positive adjustment of past travel experiences shows that repeat visitors have a greater impact than newcomers and potential tourists.

Introduction

When assuming normalized circumstances, travel intention primarily arises from a combination of tourists’ personal preferences, expectations, motivations, and satisfaction, as well as destination marketing and other factors. However, existing research has tended to ignore other important influences, including subjective factors and objective environmental factors. Meanwhile, a variety and repetition of crisis events over many years have only underlined the social attributes of travel behavior. That is, whether a person engages in travel—and where to—depends not only on personal preferences, but also their knowledge regarding and ability to prevent and control tourism risks, their past travel experience, and the attitudes of other key persons or organizations regarding travel behavior at the time of decision-making. Following the initial outbreaks and rapid global spread of COVID-19, domestic and international tourism have stagnated; hospitality and other tourism-related industries have had to suspend work accordingly; no part of the industry has been unaffected ( Figure 1 ). Despite explosive growth in the global tourism industry over the past 40 years, establishing it as one of the major engines driving global economic development, employment, and industrial transformation, the COVID-19 pandemic has hit the brakes and stalled the engines. The enormity of the pandemic’s impact on global tourism is still coming to light. This reflects not only the tight bonds within tourism production and consumption networks in the age of globalization but also the vulnerability of the industry at large. At this moment there is an urgent need for tourism scholars and industry experts to examine the relationship between tourism and the global public health crisis from a variety of perspectives. Thus far scholars have measured the impact of relevant cognitive factors on travel intention in terms of knowledge, perceived risk ( Zhu and Deng, 2020 ), and psychological distance ( Li et al., 2020 ). However, the literature mostly approaches behavioral intention from the perspective of individual tourists rather than groups and tends to employ one or two different theories to account for cognitive factors’ influence on travel intention. Lee and Jan (2018) believe that an integrated framework provides researchers and managers with critical insights and a more accurate grasp of the factors influencing ecotourism behavior. Thus, they construct an integrated model combining multiple theories and previously neglected factors to survey complex relations within structures, explain working mechanisms, and enhance explanatory and predictive power.

Figure 1. China’s annual domestic tourist volume, 2012 to 2021.

To this end, this research deepens the study of tourists’ travel intention in two aspects: integrating key factors and concepts and testing these against a moderating variable. For the former, the three factors are knowledge (as in knowledgeattitude-behavior, or KAB theory), identity (as in social identity theory, SIT), and perceived risk (as in theory of perceived risk, TPR). These are integrated to build a more comprehensive model of travel intention factors, to explore the path and effect of tourists’ action, and to answer the question of mechanism pathways. As for the latter, past travel experience is used as a moderating variable to test for changes in the relations of the abovementioned variables with varying levels of past travel experience. When considering the impact of past travel experience on current travel intention, previous papers have mainly employed binary variables to compare whether travel intention was affected by past travel experience (potential tourists and actual tourists; first-time visitors and repeat visitors) for their assessments, but the current study increases precision by dividing tourists into three graded categories—potential tourists, first-time visitors, and re-visitors—to assess the impact of past travel experience on the path of this mechanism and solve the problem of boundary conditions.

Theoretical Background and Hypothetical Development

Theory of planned behavior.

The TPB is typically used to explain the relationship between attitudes and planned, intentional behavior when people have enough time to think about their attitudes. According to this theory, behavioral attitudes, subjective norms, and perceived behavioral control are the three key factors that affect behavioral intentions. Behavioral attitude is an individual’s personal evaluation of a behavior; subjective norms refer to the perception of whether important others agree with the behavior or not. These “important others” may be members of families, private networks, community organizations, work units, party organizations, and so on ( Duan and Jiang, 2008 ). Perceived behavioral control is the sense of control an individual believes he or she has over behavior as well as the perceived difficulty of performing that behavior. Generally, tourists with better professional knowledge and who are secure in their time and monetary resources have greater perceived control and thus stronger travel intention ( Zhu and Deng, 2020 ).

Theory of planned behavior and its extensions are often used to illustrate the mechanism behind tourists’ behavior intentions, and exhibit good explanatory and predictive power. Boguszewicz-Kreft et al. (2020) have verified the TPB model’s applicability to medical tourism and compared the differential willingness among consumers of different nationalities to use medical tourism services. Hu et al. (2021) have found that attitudes, perceived behavioral control, environmental awareness, and perceived moral obligations are significantly and positively correlated with young people’s intent for low-carbon travel behavior, while subjective norms are not. Chen et al. (2019) have applied TPB to a study of pro-environmental tourism behavior among urban residents, finding that intentions and habits are the key influential factors, while attitudes have the most significant impact on behavioral intention. Joo et al. (2020) , meanwhile, have found that perceived behavioral control and subjective norms have a significant positive impact on rural tourism intention; among these two, subjective norms have a greater effect, while attitudes have no significant effect on travel intention.

Knowledge-Attitude-Behavior

The KAB model divides human behavior into three processes: acquiring knowledge, generating belief, and forming behavior. According to this theory, attitude is the best predictor of behavior, knowledge is the basis of changes in attitude, and the degree of knowledge mastery affects the consistency of attitude and behavior. Thus tourism knowledge is the key to the development of attitudes and travel behavior, but this “knowledge” is different from knowledge in the objective sense; rather, it is an abstracted perception of knowledge that directly affects tourists’ psychology and decision-making practices, as through the arousal of confidence and willingness to act ( Quintal et al., 2010 ; Sharifpour et al., 2014 ). Zhu and Deng (2020) define such knowledge perception as a tourist’s mental assessment of his or her ability to identify and understand the risks of tourism and COVID-19, the danger these pose to humans and the tourism industry, as well as countermeasures and other related issues. Psychologically, having more knowledge can increase an individual’s personal control over uncertain scenarios ( Zhang et al., 2021 ). When travelers think that they have more knowledge than others, and thus a greater ability to prevent and control risks, they are more likely to participate in tourism activities ( Tassiello and Tillotson, 2020 ). Therefore, considering the above analysis, this study puts forth the following hypotheses:

H1: Knowledge (a: knowledge of tourism; b: knowledge of COVID-19) has a direct and indirect positive impact on travel intention through attitudes.

H2: Knowledge has a direct and indirect positive impact on travel intention through subjective norms.

H3: Knowledge has a direct and indirect positive impact on travel intention through perceived behavioral control.

Social Identity Theory

Social identity theory focuses on individual behavior in group settings. It suggests that group belonging (regardless of that group’s size or distribution) is, to a large extent, an individual mental state, but one that is totally distinct from that person’s independent mental state outside of the group setting. Belonging to a group gives one social identity, or a shared collective answer to the question “who am I?”, along with a set of behaviors appropriate to that identity ( Abrams and Hogg, 2006 ). According to SIT, “identity” includes both self-identity, social identity, etc.; while self-identity is an individual’s perception of self-consistency and continuity ( Erikson, 1968 ); social identity is an individual’s awareness of belonging to a specific social group ( Tajfel, 1982 ). Such identification can work to depersonalize an individual’s self-perception and social actions.

In their research on the relationship between identity and past travel experience, Gieling and Ong (2016) find that attitudes and behaviors are affected by important social relationships. Likewise, Forsyth et al. (2015) suggest that a sense of community can influence individual behavior. Canovi (2019) , meanwhile, finds that winemakers’ identities are moderated by the local community, which ultimately affects their attitudes toward diversified tourism development. It is clear that travel intention is inseparable from larger social contexts. Researchers must move beyond understandings of individual intention and formulate their studies to account for communities’ collective consciousnesses, individual respect for collective interests, and the association of individual behavior with important social members or organizations. In light of this, the following hypotheses are put forward:

H4: Tourism self-identity has a direct and indirect positive impact on travel intention through attitudes.

H5: Tourism self-identity has a direct and indirect positive impact on travel intention through subjective norms.

H6: Tourism self-identity has a direct and indirect positive impact on travel intention through perceived behavioral control.

Theory of Perceived Risk

The basic principles of TPR are based on the theory of bounded rationality and satisfaction. Bauer (1960) believes that when consumers make decisions, they do not seek to “maximize utility” as economists call it, but to minimize the associated risk. According to TPR, perceived risk is one’s expectation that he or she may suffer losses. This subjective take is important because if a tourist does not perceive risk, it may not affect his or her travel decisions; conversely, even in the absence of objective risk, a tourist’s perception of its presence may affect decision-making nevertheless ( Khan et al., 2019 ).

Initial research on perceived risk tended to suggest that the greater tourists’ perceived risk—in terms of time, economy, physical and mental health, etc.—the more likely they are to lower their travel intention in avoidance of said risk ( Fischer et al., 1991 ; Roehl and Fesenmaier, 1992 ; Zhu and Deng, 2020 ). As research has deepened, perceived risk’s positive effect on behavioral intention has received much attention. Scholars have found that perceived risk can enhance public attention to risk, crisis awareness, risk recognition and understanding, the ability to interpret risk information in a calm manner, to participate in discussions on risk, and to form reasonable perceptions and attitudes in relation to risk—important outcomes beneficial to the reduction of perceived risk and formation of positive behavioral attitudes ( Cui et al., 2016 ). And, as novel phenomena inevitably inspire some people’s curiosity, a certain level of perceived risk may actually inspire more adventurous attitudes and a willingness to face challenges. Reisinger and Mavondo (2005) find that backpackers have higher risk tolerance than group tourists and will seek out moderately high levels of risk to increase the excitement of travel. Vespestad et al. (2019) , meanwhile, propose that higher risk perception in adventure tourism is a point of attraction for its potential consumers. Thus, considering that perceived risk can also stimulate a person’s intent to travel, this study puts forth the following hypotheses:

H7: Perceived risk has a direct and indirect positive impact on travel intention through attitudes.

H8: Perceived risk has a direct and indirect positive impact on travel intention through subjective norms.

H9: Perceived risk has a direct and indirect positive impact on travel intention through perceived behavioral control.

Moderating Role of Past Travel Experience

Past travel experience refers to individuals’ prior instances of personal participation in tourism activities. Such experience can increase willingness to revisit ( Roehl and Fesenmaier, 1992 ; Sönmez and Graefe, 1998 ; Vespestad et al., 2019 ). When it comes to behavioral intention, past travel experience has greater explanatory power than other variables in TPB, and when it comes to tourism behavior, in particular, past travel experience is considered a key determinant ( Ajzen, 2002 ). Tourists with different past travel experiences will differ significantly in cognitive levels and emotional attitudes, so past travel experience is often regarded as an important moderating factor ( Hammond et al., 1998 ; Ajzen, 2002 ). Deutsch and Krauss (1965) find that compared to indirect experience, personal experience can affect more consistency in attitude and behavior. For a more specific illustration, Beldona et al. (2005) find that earlier (i.e., more experienced) users of online travel sites are more likely to purchase online travel products than later users. Murodjon et al. (2021) also found that past personal experience had a significant impact on tourists’ behavioral intention in their study of Uzbekistan’s Silk Road tourism. Kim and Chen (2021) , when comparing two groups of interviewees, find that those with firsthand experience expressed higher destination loyalty and stronger behavioral intention. In view of these findings, this study puts forward the following hypotheses:

H10: Past travel experience moderates the impact of (a) knowledge, (b) tourism self-identity, (c) perceived risk, (d) attitude, (e) subjective norms, and (f) perceived behavioral control on travel intention.

H11: Past travel experience moderates the impact of (a) knowledge, (b) tourism self-identity, and (c) perceived risk on attitude.

H12: Past travel experience moderates the impact of (a) knowledge, (b) tourism self-identity, and (c) perceived risk on subjective norms.

H13: Past travel experience moderates the impact of (a) knowledge, (b) tourism self-identity, and (c) perceived risk on perceived behavioral control.

Lepp and Gibson (2003) indicate past travel experience as an important factor affecting tourists’ perceived risk. Likewise, Fuchs and Reichel (2011) find differences in risk perception between first-time and repeat visitors. As repeat visitors generally have more experience preventing and controlling tourism risks, their risk perception is lowered, and it is easier for them to form positive travel attitudes. At the same time, repeat visitors’ perceived control has a more pronounced effect on their travel intention; experienced tourists will even ignore the risks involved. They are also more familiar with the variety of travel activities and applicable precautions, more inclined to support the unified management of communities and destinations, and feel more in control of their behavior during travel. Accordingly, it may be deduced that the mediating role of attitudes, subjective norms, and perceived behavioral control on knowledge, tourism self-identity, and perceived risk’s impact on travel intention may be yet further regulated by past travel experience. Therefore, it is proposed that:

H14: Past travel experience moderates the mediation of (a) attitudes, (b) subjective norms, and (c) perceived behavioral control between knowledge and travel intention.

H15: Past travel experience moderates the mediation of (a) attitudes, (b) subjective norms, and (c) perceived behavioral control between tourism self-identity and travel intention.

H16: Past travel experience moderates the mediation of (a) attitudes, (b) subjective norms, and (c) perceived behavioral control between perceived risk and travel intention.

By combining these hypotheses, this study proposes a comprehensive theoretical model ( Figure 2 ).

Figure 2. Conceptual diagram of a final integrated model.

Materials and Methods

Questionnaire design and variable measurement.

The main body of the questionnaire utilizes the 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). To ensure the reliability and validity of results, its design draws upon well-established scales, with adjustments to fit the specific context and goals of the study. With reference to Zhu and Deng (2020) , knowledge is measured in two aspects—knowledge of tourism, and knowledge of COVID-19—across eight items, while the perceived risk is measured across 10 items and in four dimensions: physical, cost, performance, and equipment risk. Tourism self-identity, subjective norms, and perceived behavioral control draw on the well-established scales of Lee and Jan (2018) and are measured by four to five items each, while travel intention is measured by three items. As categorical variables cannot accurately measure the degree of impact the environment exerts during a certain experience, this study selects graded variables to measure past travel experience, dividing the respondents into three categories—potential tourists, first-time visitors, and repeat visitors—to analyze the moderating effect of past travel experience. A pre-test of reliability finds that after deleting the item “(KP1) I know the original cause of COVID-19”, the reliability coefficient improves significantly; this item was thus deleted during the revision of the questionnaire ( Table 1 ).

Table 1. Results of exploratory factor analysis (EFA).

Survey Sampling and Data Collection

The sample size formula designed by Yamane (1967) is as below.

Where n represents sample size, N stands for the population, and e represents the precision level. Usually, e was at a 95% confidence level. In this study, in accordance with the figure 3.25 billion domestic person-trips for China in 2021, the formula yielded an n of 399.9 as the minimum acceptable sample size.

This study, using convenience sampling, collected data using the professional survey application ‘‘Questionnaire Star’’, 1 whose paying customers to cover more than 30,000 companies and 90% of universities in China. The official questionnaire was open from 26 December 2020 to 26 January 2021. After applying the “Questionnaire Recommendation Service” through Questionnaire Star, the online system randomly invited people from its 2.6-million-sample database to fill in their responses. Beyond that, members of the research team and the surrounding community were invited to respond to the survey as well—via weblink, QR code, or WeChat message.

The average time for each questionnaire is 487 s. The questionnaires with an answering time of less than 1 min or a missing proportion of more than 70% are considered invalid questionnaires. After the invalid questionnaires were deleted, a total of 405 valid questionnaires were obtained. Among the valid questionnaires, 69.8% of respondents are men and 30.2% are women; in terms of age structure, the largest group is 18–25 years (67.57%), followed by 26–30 years (18.81%) and 31–40 years (10.64%); as for educational attainment, the most common level is college or post-secondary professional schooling (55.56%), followed by high school or vocational schooling (25.68%), then masters or doctoral study (15.8%). Respondents come from 89 cities in 27 provinces and cover 15 occupations in 24 industries. Potential tourists, first-time visitors, and repeat visitors account for 20.15, 13.18, and 66.67% of respondents, respectively. In the first year of COVID (23 January 2020 to 26 January 2021), 80.3% of tourists did not participate in tourism, while 19.7% of tourists did participate in tourism activities.

Analysis Methods

For data analyses, the SPSSAU data scientific analysis platform ( https://spssau.com/ ) developed by Changsha Ranxing Information Technology Co., Ltd., location in Changsha, China, was used to run reliability and validity tests, descriptive statistics, and correlation coefficient checks. Building on that, hierarchical regression analysis was employed to test the main effect, mediated effect, and moderating effect, while a bias-corrected non-parametric percentile method (bootstrapping) was used to test for mediating and moderated mediating effects.

Reliability and Validity Analysis

First is index classification analysis. Thirty-six items were enriched through exploratory factor analysis (EFA) and rotated with maximum variance rotation. During factor analysis, KMO values were 0.88 > 0.6, indicating that the data can be used for factor analysis ( Kaiser, 1974 ). The final condensation into eight factors is shown in Table 1 . Cumulative variance is 78.41%, meaning that these eight factors are able to extract 78.41% of information from the total 36 items; variance (rotated)—that is, the amount of information extracted—for the eight factors following rotation are 15.91, 11.59, 9.68, 9.39, 9.38, 8.37, 8.2, and 5.9, respectively. This distribution is sufficiently uniform to demonstrate the comprehensive soundness of factor analysis results. Moreover, the 36 items fit well with professional expectations. Integrating the congruence between factors and analysis items, the eight condensed factors are ultimately named: “perceived risk,” “subjective norms,” “knowledge of COVID-19,” “knowledge of tourism,” “attitudes,” “tourism self-identity,” “perceived behavioral control,” and “travel intention.”

The second is the reliability test, which employs reliability analysis. The data involves eight dimensions: perceived risk, subjective norms, knowledge of COVID-19, knowledge of tourism, attitudes, tourism self-identity, perceived behavioral control, and travel intention. Cronbach’s alpha (α) measures the quality of data reliability. If the value of α is higher than 0.8, the data is highly reliable; if α is between 0.7 and 0.8, reliability is good; a value between 0.6 and 0.7 indicates acceptable reliability, and a value of 0.6 or below indicates poor reliability ( Eisinga et al., 2013 ). As shown in Table 2 , the questionnaire’s total score is 0.921 and all eight dimensions have a Cronbach’s alpha value higher than 0.8, with the lowest dimension scoring 0.831. Data reliability is thus of high quality, and the data is considered credible and true.

Table 2. Results of reliability analysis.

The third is the convergent validity analysis. Confirmatory factor analysis (CFA) is conducted for a total of eight factors and 36 analysis items, as shown in Table 2 . The effective sample size is 405—more than ten times the number of analysis items, and within the moderate range ( Everitt, 1975 ). The study finds that all measurement items are significant to the.001 level ( p < 0.001). The scale of the study is represented by eight condensed factors. As shown in Table 3 , the factors’ average variance extracted (AVE) values are all greater than 0.6, with a minimum value of 0.634, significantly exceeding the standard of 0.5, while composite reliability (CR) values are all greater than.8, significantly exceeding the respective standard of 0.7. The study scale thus demonstrates excellent convergent validity ( Gim Chung Ruth et al., 2004 ). Moreover, the standardized factor loading coefficients for all 36 items corresponding to the eight factors, given in Table 4 , are greater than or equal to 0.7, comprehensively indicating the excellent convergent validity of scale data in this study.

Table 3. Results of confirmatory factor analysis.

Table 4. Standardized factor loading.

The fourth is discriminant validity testing. Discriminant validity is measured by comparing the square root of AVE—representing that factor’s convergence—with factors’ correlation coefficients, which express the degree of correlation. If a factor’s convergence is very strong (significantly stronger than the “correlation coefficient between this factor and other factors”), then it is considered to have discriminant validity. In this study, Pearson correlation analysis is performed first to determine the interfactor correlation coefficients. Next, the square root of each factor’s AVE value is compared against the interfactor correlation coefficients. The results of this analysis are given in Table 5 . The square roots of AVE for “knowledge of COVID-19” is 0.891, which is greater than the correlation coefficients between “knowledge of COVID-19” and all seven other factors (the highest is 0.547); similarly, the square roots of AVE for “knowledge of tourism” is 0.887, which is greater than all its correlation coefficients with other factors (the highest is 0.627); indeed, all eight factors have AVE root values that are higher than their interfactor correlation coefficients. Therefore, the study’s scale data has good discriminant validity ( Gim Chung Ruth et al., 2004 ).

Table 5. Means, standard deviations, and correlation coefficients for study variables.

Multicollinearity, Autocorrelation, and Normality Tests

Linear regression analysis is used to assess how perceived risk, subjective norms, knowledge of COVID-19, knowledge of tourism, attitudes, tourism self-identity, and perceived behavioral control relate to “travel intention”. The study finds that the model passes the F -test ( p < 0.001); in other words, the model is meaningful, and at least one of the seven factors will have an impact on travel intention. As the model’s R 2 value is 0.79, these seven factors should explain 79% of the variation in travel intention. In addition, the model’s multicollinearity test results in a maximum VIF value of 1.79, which means that all factors’ VIF values are less than 5, indicating that there is no collinearity, and the model is satisfactory ( Hauke and Kossowski, 2011 ).

The Kolmogorov-Smirnov test is used to analyze the data’s distribution normality. It finds the skewness coefficient’s absolute value to fall between 0.12 and 1.05 and the kurtosis coefficient’s absolute value to fall between 0.12 and 2.15—well below the critical values of 3 and 8, respectively. The sample thus passes the normality test ( Drezner et al., 2010 ).

Descriptive Statistical Analysis

Pearson correlation analysis is used to verify correlation and the strength of the relationships between variables. The study finds a significant positive correlation between the following factors ( Table 5 ): knowledge of tourism and attitudes ( r = 0.39, p < 0.001), knowledge of COVID-19 and attitudes ( r = 0.55, p < 0.001), knowledge of tourism and subjective norms ( r = 0.38, p < 0.001), knowledge of COVID-19 and subjective norms ( r = 0.13, p < 0.01), knowledge of tourism and perceived behavioral control ( r = 0.49, p < 0.001), knowledge of COVID-19 and perceived behavioral control ( r = 0.18, p < 0.001), tourism self-identity and attitudes ( r = 0.46, p < 0.001), tourism self-identity and subjective norms ( r = 0.5, p < 0.001), tourism self-identity and perceived behavioral control ( r = 0.49, p < 0.001), perceived risk and attitudes ( r = 0.32, p < 0.001), perceived risk and perceived behavioral control ( r = 0.48, p < 0.001), knowledge of tourism and travel intention ( r = 0.43, p < 0.001), knowledge of COVID-19 and travel intention ( r = 0.15, p < 0.01), tourism self-identity and travel intention ( r = 0.56, p < 0.001), perceived risk and travel intention ( r = 0.31, p < 0.001), attitudes and travel intention ( r = 0.45, p < 0.001), subjective norms and travel intention ( r = 0.71, p < 0.001), perceived behavioral control and travel intention ( r = 0.51, p < 0.001). These results provide preliminary evidence for subsequent hypothesis testing.

Model Comparison Analysis

The study selects the most commonly used fitting indexes such as GFI, NNFI, CFI, RMR, RMSEA, etc. in order to analyze the fit of the model. As shown in Table 6 , compared with the KAB, SIT and TPB models, the integrated model has better fitting conditions and more reliable results.

Table 6. The model indices of the four theoretical models.

According to Jöreskog and Sörbom (1996) , χ 2 can test whether there is a statistically significant difference between the two competing models in their ability to explain covariance. Therefore, the study compares three competitive models (TPB model, SIT model, and KAB model) to determine the optimal model (integrated model). The fitting indexes of the four theoretical models in Table 6 show that the integrated model is better. The explanatory power of the integrated model and the competitive model showed a significant difference ( p < 0.001).

Hypothesis Testing

Main effect test.

After controlling for demographic and travel behavior characteristics—such as gender, age, marital status, educational attainment, industry, occupation, tourist origin, etc., regression analysis is used to verify the influence of independent variables on dependent variables. The study finds significant positive influences on travel intention for the following factors: knowledge (second-order) (β = 0.32, p < 0.001), knowledge of tourism (β = 0.35, p < 0.001), knowledge of COVID-19 (β = 0.11, p < 0.05), perceived risk (β = 0.24, p < 0.001), tourism self-identity (β = 0.58, p < 0.001). This means that knowledge, perceived risk, and tourism self-identity can increase travel intention.

Mediation Effect Test

After controlling for demographic and behavioral characteristics, the Bootstrap sampling method is used to test the mediating effect. The Bootstrap test for the sampling method refers to whether the 95% CI for the regression coefficient a*b contains the number 0; if it does not include the number 0, it means a mediating effect is present; if it does include the number 0, then there is no mediating effect. The results after sampling 5,000 times are shown in Table 7 . In total there are five independent variables, three mediator variables, and 15 mediation paths—among these, nine paths are fully mediated; four paths are partially mediated, and two paths are not significantly mediated.

Table 7. Results of mediation analysis.

The 95% CIs corresponding to the mediating effect (on travel intention) of attitudes, subjective norms, and perceived behavioral control in knowledge (second-order), knowledge of tourism, and knowledge of COVID-19 do not contain 0, indicating a significant mediation path, and the effect sizes were all 100%. This means that the effect of knowledge on travel intention works through attitudes, subjective norms, and perceived behavioral control. That is to say, the findings support Hypotheses 1-3: knowledge can both directly influence travel intention and indirectly promote travel intention when mediated by attitudes, subjective norms, and perceived behavioral control.

The 95% CIs respectively corresponding to the mediating effects of subjective norms and perceived behavioral control in tourism self-identity’s effect on travel intention are [0.16,0.31] and [0.01,0.1], not containing 0, indicating a significant mediating effect. This validates Hypotheses 5 and 6: tourism self-identity can both directly influence travel intention and indirectly promote travel intention through the mediation of subjective norms and perceived behavioral control. In the two groups, the indirect effects of subjective norms and perceived behavioral control are 41.17 and 8.78%, respectively.

The 95% CIs respectively corresponding to the mediating effect of attitudes and perceived behavioral control in perceived risk’s effect on travel intention are [0.00,0.05] and [0.01,0.11], not containing 0, indicating a significant mediating effect. Thus Hypotheses 7 and 9 hold: that perceived risk can both directly influence travel intention and indirectly promote travel intention through the mediation of attitudes and perceived behavioral control. In the two groups, the indirect effects of attitudes and perceived behavioral control are 8.96 and 17.94%, respectively.

As for the two remaining paths, however, (TI←ATT←TID and TI←SN←PR), the 95% CIs are [−0.00,0.07] and [−0.04,0.13], and contain the number 0, meaning that the mediating effect is not significant. Thus perceived risk does not affect travel intention indirectly via subjective norms, and tourism self-identity does not affect travel intention indirectly via attitudes; Hypotheses 4 and 8 do not hold.

Test of the Moderating Effect

After centering the independent and moderator variables and controlling for demographic and travel behavior characteristics, the moderating effect is tested. This analyzes the effect of independent variables on dependent variables and whether or not the moderator comes into play—that is, when the level of past travel experience varies, whether there is a significant difference in the magnitude of influence.

The study finds that when the level of past travel experience varies, the impact of knowledge, knowledge of COVID-19, tourism self-identity, perceived risk, attitude, and subjective norms on travel intention are the same ( p > 0.05). Therefore, H10b–H10e do not hold, the effects of knowledge, knowledge of COVID-19, tourism self-identity, perceived risk, attitude, and subjective norms on travel intention were completely consistent regardless of the subject’s status as a first-time visitor, repeat visitor, or potential tourist. Generally speaking, the influence that knowledge exerts over travel intention is unperturbed by the factor of past travel experience; however, this is not always the case. While past travel experience does not interfere with the effect of knowledge of COVID-19 on travel intention, it does interfere with the effect of knowledge of tourism on travel intention ( p = 0.001). The strength of interference varies as follows: repeat visitors > first-time visitors > potential tourists ( Figure 3A ). Therefore, H10a holds in part. As shown in Figure 3B , the effect of perceived behavioral control on travel intention is positively moderated by the interference of past travel experience ( p = 0.036). The more travel experience, the greater the effect. That is, repeat visitors > first-time visitors > and potential tourists. H10f is therefore supported.

Figure 3. (A,B) The moderating effect of past travel experience on travel intention. (C–F) The moderating effect of past travel experience on attitudes. (G–I) The moderating effect of past travel experience on subjective norms. (J–L) The moderating effect of past travel experience on perceived behavioral control.

As shown in Figures 3C–F , the impact of knowledge (second-order) ( p = 0.013), knowledge of tourism ( p = 0.000), knowledge of COVID-19 ( p = 0.022), and perceived risk ( p = 0.002) on attitude are significantly different, indicating past travel experience regulates the impact of these factors on attitude. The richer the past travel experience, the more positive the attitude. H11a and H11c thus hold. When the level of past travel experience varies, the impact of tourism self-identity on attitude is the same ( p > 0.05). H11b is not supported.

As shown in Figures 3G–I , the impact of knowledge (second-order), knowledge of tourism, and tourism self-identity on subjective norms vary with the level of past travel experience. When past travel experience is richer, the respective impact of the three abovementioned factors on subjective norms is greater. H12b thus holds while H12c is not supported. H12a partially holds. Past travel experience tends to interfere with the effect of knowledge on subjective norms, but not invariably; it moderates the effect of knowledge of tourism (as shown in Figure 3H : repeat visitors > first-time visitors > potential tourists) but does not moderate the effect of knowledge of COVID-19 on subjective norms ( p > 0.05).

As shown in Figures 3J–L , the impact of knowledge (second-order), knowledge of tourism, and tourism self-identity on perceived behavioral control vary with the level of past travel experience. When past travel experience is richer, the impact of the three abovementioned factors on perceived behavioral control is greater. H13b thus holds while H13c is not supported. H13a holds in part. Past travel experience generally does moderate the effect of knowledge on perceived behavioral control, but not always; while the effect of knowledge of tourism is affected by past travel experience (as shown in Figure 3K : repeat visitors > first-time visitors > potential tourists), the effect of knowledge of COVID-19 on behavioral control is not thus affected ( p > 0.05).

Moderated Mediation Model Test

In the moderated mediation model, the independent variable affects the dependent variable through a moderator variable such that the process of mediation is moderated by it. the moderated mediation model is used to analyze whether there are significant differences in the mediating effect with varying levels of a moderator variable. The test results for this study are given in Table 8 . When there is a high level of past travel experience, the mediating effect of knowledge (second-order) and knowledge of COVID-19 on travel intention through attitudes is not significant (i.e., BootCI contains the number 0), but when there is a low or average level of past travel experience, the mediating effect is significant (i.e., BootCI does not contain the number 0). When there is either a low or high level of past travel experience, the mediating effect of knowledge of tourism on travel intention through attitudes is not significant (BootCI contains 0), but where there is an average level of past travel experience, the mediating effect becomes significant (BootCI does not contain 0). This suggests a lack of consistency regarding the mediating impact of attitudes across the three levels and that a conditional mediating effect exists for the three paths TI←ATT←K, TI←ATT←KT, and TI←ATT←KC. Therefore, H14a holds: past travel experience moderates the mediation of attitudes between knowledge and travel intention.

Table 8. Results of a moderated mediation analysis.

When there is a low level of past travel experience, then the mediating effects of knowledge, knowledge of tourism, and knowledge of COVID-19 on travel intention through subjective norms and perceived behavioral control, respectively, are not significant (BootCI contains 0); however, at average or high levels of past travel experience, the mediating effect becomes significant (BootCI does not contain 0). This indicates that subjective norms and perceived behavioral control each have inconsistent mediating effects across the three levels. Therefore, for the six pathways TI←SN←K, TI←SN←KT, TI←SN←KC, TI←PBC←K, TI←PBC←KT, and TI←PBC←KC, conditional mediation exists; H14b and H14c hold.

For the mediation path TI←ATT←TID, the mediating effect of attitude is not significant regardless of the level of past travel experience (BootCI contains 0); H15a does not hold. In contrast, subjective norms do significantly mediate (BootCI does not contain 0) for the TI←SN←TID path, regardless of the level of past travel experience. At all three levels, subjective norms play a mediating role, and the size of the effect is always greater than 0. This indicates no moderation because the mediating effect is consistently the same. Thus, H15b does not hold. As for the TI←PBC←TID path, when past travel experience is at a low level, perceived behavioral control does not play a mediating role (BootCI contains 0), but it does play a mediating role at average or high levels (BootCI does not contain 0). This inconsistency in mediation across the three levels suggests conditional mediation, such that H15c holds.

For the path TI←ATT←PR, the mediating effect of attitude is not significant when past travel experience is at either a low or high level (BootCI contains 0). Here, the difference is that the effect value is negative (−0.003) at a low level and positive (0.016) at a high level. The mediating effect of attitude is, however, significant when past travel experience is at an average level (BootCI does not contain 0). Evidentially, the mediating effect of attitudes is inconsistent across the three levels; thus conditional mediation is present and H16a holds. As for TI←SN←PR, subjective norms do not play a mediating role regardless of the level of past travel experience (BootCI contains 0). There is no significant conditional mediation, and H16b does not hold. Regarding path TI←PBC←PR, perceived behavioral control does not mediate at a low level of past travel experience (BootCI contains 0) but does mediate at average or high levels (BootCI does not contain 0). This inconsistency points to perceived behavioral control’s conditional mediating role, effectively supporting H16c.

Perhaps no event in modern tourism has had (and continues to have) a more significant impact on travel desire, perceived travel risk, and the hospitality industry at large than the 2020 outbreak and global spread of COVID-19. As tourism destinations and management continue to grapple with the threat of outbreaks or case surges, control, and prevention measures, changing policies and various closures, the quality of knowledge on tourist subjectivities and behavior will only become more valuable. Although this study is not specifically focused on the impact of COVID-19 on risk perception (cf. Nazneen et al., 2020 ; Sánchez-Cañizares et al., 2021 ; Chi et al., 2022 ; Jiang et al., 2022 ), the pandemic is still a crucial element and inseparable background to its findings. Until the virus is defeated on the global scale, the subjective and objective effects of COVID-19 must be integrated into tourist psychology research to some degree. At the same time, it is important not to set the scope of research too narrowly and over-focus on individual reactions in the present moment, as new information is always filtered through past experiences, and potential behavior is mentally screened against the anticipated opinions and reactions of key social others. This study provides a comprehensive framework for understanding travel intention outcomes that are both adequately unique to “post-COVID” reality and sufficiently holistic for wide application.

Consistent with the conclusions of Quintal et al. (2010) and Sharifpour et al. (2014) , this study finds that knowledge has a significant positive impact on travel intention. If travelers suspect that their knowledge is insufficient, they may mitigate uncertainty by abstaining from tourism activities. This, however, does not mean that the acquisition of knowledge can immediately change attitudes and affect behavioral intentions. In practice, if 40% of people exhibit a behavior, then 60% of people must have a positive attitude toward engaging in the behavior; 80% of people believe in a kind of behavior, and more than 90% must have the necessary knowledge in order for the behavior to change ( Wang and Cheng, 2018 ). Related research has also found that more knowledge is not necessarily better, because there are negative effects associated with “information overload”. Some of the main reasons that tourists visit where they do are heterogeneity and curiosity, so when they become too familiar with a destination, curiosity weakens, as does that destination’s attractive force ( Park and Jang, 2013 ; Hadar and Sood, 2014 ; Hu and Krishen, 2019 ). Zhu and Deng (2020) find that the greater tourists’ knowledge of tourism, the higher they will evaluate their own abilities in tourism risk management, and the stronger their travel intention will be. However, this article proposes that due to the characteristics of COVID-19—high transmissibility, a long incubation period, rapid mutation, and novelty (that is, a lack of previous experience in its prevention and control)—individual tourists will not have significantly improved perceived behavioral control with greater knowledge of COVID-19.

It is typically assumed that perceived risk undermines confidence and reduces perceived control over a situation. Conversely, this study conforms with Reisinger and Mavondo (2005) ; Hajibaba et al. (2017) , and Vespestad et al. (2019) , finding that perceived risk has a significant positive impact on travel intention. There are three possible explanations for this result: (1) Perceived risk allows individuals to understand potential threats and thus appropriately determine the level of risk, take scientific precautions, actively respond, and lessen adverse effects. (2) The situation with COVID-19-related risks is somewhat different but to a similar end. COVID-19 has yet to be completely eliminated, and threats of new outbreaks are ongoing. Even the cancellation of tourism activities may not be enough to avoid the risk of infection. Still, due to new structures or feelings of social isolation, people are eager to release psychological pressure through tourism behavior, including “getting close to nature”. Thus, the pandemic has amplified travel desires. (3) Moderate risks can actually increase the excitement of travel. In moderation, risks stimulate tourists’ adventurous spirit and drive to face challenges, which will stimulate their desire to travel as well. Some tourists will even seek out a highly volatile destination for travel ( Fuchs and Reichel, 2011 ). The effect of perceived risk on travel intention is thus two-sided, in some contexts actually enhancing the intention to travel. This study finds that perceived risk negatively affects tourism attitudes among potential tourists, but positively affects the travel attitudes of first-time and repeat visitors. Perhaps this is because with an increase in past travel experience, tourists’ knowledge and ability to prevent and control tourism risks have been continuously enhanced, and tolerance of tourism risks has increased accordingly as well. These conclusions enrich the systematic understanding of how perceived risk affects travel attitudes and travel intention.

The study has added important concepts to the model—such as tourism self-identity and subjective norms—and put the study of individual behavioral intention into its social context, exploring how group psychological states affect an individual’s social perception, social attitude, and social behavior. Similar to Lee and Jan (2018) , in this study tourism self-identity has a significant positive influence on travel intention. Compared with other influencing factors, tourism self-identity and subjective norms have a greater impact on travel intention. Therefore, tourism marketing after COVID-19 must not only focus on tourists, but also on the attitudes of potential tourists, important others, and important groups.

The study divides tourists into three categories—potential tourists, first-time visitors, and repeat visitors—to verify the moderating effect of past travel experiences. Consistent with previous findings ( Sönmez and Graefe, 1998 ; Ajzen, 2002 ; Tassiello and Tillotson, 2020 ), when tourists have more past travel experience, there is positive moderation of the indirect effects on travel intention—through travel attitudes, subjective norms, and perceived control, perceived risk through travel attitudes, and tourism self-identity through subjective norms and perceived control. Generally speaking, the more past travel experience, the greater the effects. Similar to Ramkissoon and Mavondo (2015) , which identify gender as a strong moderator of tourists’ place satisfaction and pro-environmental behavioral intention, this study’s introduction of past travel experience substantially improves explanatory power as well as the multi-dimensionality and holism of tourism behavioral modeling. Tourist psychology has much more to do with social roles and ties formed prior to or outside of the defined tourism context than is generally appreciated, and understanding the interplay of those forces requires the application of more nuanced moderated mediation models.

Conclusion and Limitations

This study integrates TPR, TPB, SIT, and KAB models to simultaneously investigate multiple influences on travel intention, including cognitive factors and environmental factors. It builds a comprehensive model for analyzing the mechanisms by which multiple cognitive factors affect travel intention, explores the associated boundary conditions, and uses past travel experience as the moderating variable. In accounting for travel intention, the comprehensive model’s explanatory power comes to 79%, thus outperforming the TPR, TPB, SIT, and KAB models, respectively. This work verifies the combined influence of internal subjective and external objective factors on travel intention, which extends and strengthens the overall psychological-sociological framework for researching travel intention. One key finding is that subjective norms—i.e., the approval of important others—have a greater impact on travel intention than more strictly personal factors such as perceived risk and perceived behavioral control. This points to the importance of contextualizing individual tourists’ intentions within their social relations, an approach that has previously been neglected. The study also finds that, overall, knowledge can have a direct influence on travel intention as well as an indirect influence through attitudes, subjective norms, or perceived behavioral control. Identity, meanwhile, can have a direct influence on travel intention, but indirectly only works through subjective norms or perceived behavioral control, and not through attitudes. As for perceived risk, it can have a direct influence on travel intention, but only influences it indirectly through attitudes and perceived behavioral control, and not through subjective norms.

Study findings indicate that past travel experience moderates the following twelve effects: knowledge of tourism and perceived behavioral control on travel intention; knowledge, knowledge of tourism, knowledge of COVID-19 and perceived risk on attitudes; knowledge, knowledge of tourism, and identity on subjective norms; and of knowledge, knowledge of tourism, and identity on perceived behavioral control. In addition, it also positively moderates the mediating effects of attitudes, subjective norms, and perceived behavioral control. The richer a tourist’s past travel experience, the greater the effect (repeat visitors > first-time visitors > potential tourists). In that sense, this study tests the influence of practical knowledge on tourists’ perceptions and travel decisions. Compared with indirect experience (knowledge of tourism and knowledge of COVID-19), the direct, practical experience of past travel has a greater impact on tourists’ perceptions and travel decisions. This shows that the source of knowledge is important, leading to different cognitive and behavioral outcomes. Therefore, research on the relationship between tourists’ cognitive factors and tourism attitudes or behavioral decisions will benefit greatly from the introduction of the independent variable “past travel experience.”

This study’s comprehensive model lays the groundwork for better decision-making in tourism management. Finding that subjective norms are the most important factor influencing travel intention, implies that post-COVID tourism marketing must focus not only on the tourists themselves but on the attitudes of potential tourists, important others, and important groups as well. Analysis of subjective norms’ antecedent variables finds that knowledge and self-identity significantly improve tourists’ evaluation of important others’ travel behavior approval, whereas perceived risk does not lead to an improvement in subjective norms. Therefore, tourism destinations can improve tourists’ evaluation of subjective norms by various routes including promoting knowledge of tourism risks and enhancing tourism self-identity. At the same time, these methods can improve tourists’ sense of perceived behavioral control, which in turn reinforces travel intention. Because perceived risk positively affects travel intention, the development of abundant and stimulating experiential tourism products is crucial to improving travel intention. In comparing the specific dimensions of perceived risk, this study finds that potential tourists are most concerned about cost risks; therefore, tourist receiving locations should actively mitigate the risks of economic and time costs that tourists face—by setting reasonable prices, by better-publicizing traffic, tour route and tourism product information and by improving the quality of tourism services. Moreover, in light of the current epidemic situation and tourists’ concomitant psychological fluctuations, destinations must implement normalized epidemic prevention measures to create a safe and comfortable tourism environment.

This study does have its limitations. First, although the predictive power of the comprehensive model exceeds that of competing models, it still falls short of completely explaining travel intention, indicating that there are other factors at play. This study only selected typical cognitive factors to verify their influence on travel intention. In reality, tourists’ behavioral decisions may also be affected by emotional factors (e.g., worry) and other cognitive factors (perceived value, satisfaction, etc.). Follow-up studies may construct a more complete theoretical model. Second, the study finds that knowledge has a significant positive impact on travel intention, but it is known that information overload reduces the attractiveness of destinations to tourists, in turn reducing their travel intention ( Hadar and Sood, 2014 ; Hu and Krishen, 2019 ). Resolution of this apparent paradox will require follow-up studies to compare the effect boundaries for different levels of knowledge affecting behavioral intentions in greater detail, thereby identifying the thresholds at which knowledge changes from a positive to a negative factor for travel intention.

Data Availability Statement

The original contributions presented in this study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

Ethics Statement

The studies involving human participants were reviewed and approved by College of Economics, Southwest Minzu University. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.

Author Contributions

XJ conceived and designed the concept, collected the data, and wrote the manuscript. JQ provided technical support and supervision. JG was responsible for investigation, data collection, and validation. MG reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

This research was funded by “Structural adjustment strategy in the tourism endowment industry: a supply-side reform perspective”, grant number 17BJY157 and supported by “the Innovative research project of Southwest Minzu University”, grant number CX2020BS20.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords : psychology, tourists’ perception, tourism, travel intention, integrated model

Citation: Jiang X, Qin J, Gao J and Gossage MG (2022) How Tourists’ Perception Affects Travel Intention: Mechanism Pathways and Boundary Conditions. Front. Psychol. 13:821364. doi: 10.3389/fpsyg.2022.821364

Received: 06 December 2021; Accepted: 09 May 2022; Published: 16 June 2022.

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Copyright © 2022 Jiang, Qin, Gao and Gossage. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Xiufang Jiang, [email protected] ; Jianxiong Qin, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Jacob, M., Payeras, M. (2014). Knowledge, tourism. In: Jafari, J., Xiao, H. (eds) Encyclopedia of Tourism. Springer, Cham. https://doi.org/10.1007/978-3-319-01669-6_118-1

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• Thinking on Tourism

Tourism’s Landscape of Knowledge

by Jafar Jafari | Dec 25, 2002

Tourism research and scholarship is a fairly new interdisciplinary field, and I hope to offer an abbreviated pastiche of this expanding field of knowledge, culled from my own experience. I’m using my own entrance to and journey through tourism scholarship as the basis for streamlined comments and observations on the subject. Although not my style, I’m writing this article in the first person. The format and overall scope were suggested by the editor of  ReVista , to which I agreed, especially upon learning that it would be published in the issue devoted to tourism studies. I always welcome opportunities that allow discussion of advancements in this field with outside audiences, such as those typically reached by  ReVista .

Tourism as an industry has a long and illustrious history to its own credit. Among other things, it traces its evolution from early days when a privileged few traveled once in a life time, to eras when this practice became relatively more popular due to improved economic conditions and increased knowledge of other peoples and places, to times when technology (particularly transportation) took its many small and giant leaps, and to the present when mass tourism is experienced in practically all countries, either as generating markets, receiving destinations, or both. In 2000, according to published sources, some 698 million international tourists spent $476 billion to see the world. Significantly this volume excludes domestic tourism practiced within national boundaries, which actually constitutes the bulk of what this industry represents globally.

This continuous growth and expansion over many centuries eventually led to an initially modest vista which revealed tourism as a field of investigation, a phenomenon to be studied and understood. Its emergence, as a thrust or a by-product, became more evident after World War II, when many countries (re)discovered the industry as a tool for rebuilding and re-energizing tired and exhausted economies. During the post-war years, particularly in the 60s, studies championed tourism chiefly for its economic properties, such as its contribution to growth and development, its ability to generate jobs, and its “natural” disposition to earn foreign exchange, badly needed to import goods and services for economic diversification. Elsewhere I have labeled this monodisciplinary treatment and somewhat orchestrated voice as the Advocacy Platform for the industry, which broadcast (and is still doing so) all that is considered good about it and hence advocating its worldwide development and expansion.

This one-sided economic position led to the Cautionary Platform, representing studies and views which argue that tourism is not all benefits and, significantly, comes with many sociocultural and even economic costs. Researchers mostly from other social science fields such as anthropology occupied this position. Their resulting publications, especially characteristic of the 70s, mainly focused on the “dark side” of the industry and cautioned host countries against its perceived and documented costs and unwanted consequences.

After the advocacy and cautionary voices were heard, many researchers began to examine different forms of tourism development, arguing that all are not equal and indeed some are more desirable than others. This voice was heard from the Adaptancy Platform, favoring one alternative over another, with its loudest pitch during the 80s. The resulting writings favored such forms as agritourism, cultural tourism, ecotourism, rural tourism, small-scale tourism, sustainable tourism, among others, without forgetting to name mass tourism of today—dominant even during earlier decades—as a form or alternative in its own right.

These three voices, at times being heard simultaneously—both then and today—led to the formation of the Knowledge-based Platform in the 90s. This development marks the beginning of an informed visionary mission of utilizing scientific research processes for a scientification journey into the landscape of knowledge that was unorchestratedly and fragmentedly formed during years preceding it. By this time, the advocacy, cautionary, and adaptancy positions had been articulated and their combined terrains formed the basis of the fourth platform which favored a holistic/multidisciplinary treatment and understanding of tourism: to reveal its structures and functions, to formulate concepts or theories that explain it, to apply research tools and methods which best suggest its nature and substance, and more. This journey of expedition for making pathways into the landscape, marking and mapping its fields, and naming and celebrating its achievements has been marshaled by a growing army of mainly academic researchers. Many are heading every which way, but all intend to expand the knowledge boundaries and to fortify the scientific constitution of the field.

Today’s researchers did not all start their tourism work at the same times and actually each entered the landscape through different “back doors” for diverse stated and unstated reasons. To take my case as an example, its distance vista opened to me with my first job as a tour guide, an activity that by its very nature sees various sectors of the industry interactively. This experience in itself suggested the big picture and the prospects of entering it by studying tourism at university level. In the mid-60s, as no US universities offered degrees in this field, I found my way to Cornell University, where I pursued a BS degree in Hotel Management. Soon it became evident that the day-to-day operational aspects of the hotel sector did not appeal to me. By the time I was a senior, I had decided that graduate school was my game, but not knowing how I could find entrance to fields broader than hotel management, I sought a social sciences approach which would open multidisciplinary perspectives on tourism to me.

Facing the realities of the time, and the unseated position of tourism on U.S. university campuses, I decided to pursue an MS in Hotel Administration at the same institution, but with the intent of reaching out beyond the academic confines of the program, something that my academic advisor enthusiastically accommodated. I selected a minor in international relations and informally worked with a cultural anthropologist on the campus. Probably this amounted to the extent of my outreach without raising unwanted questions from the traditional graduate program in which I was registered. These calculated outreaches afforded me the basic scope and substance for writing a 1973 thesis on the role of tourism in developing countries.

At this juncture, I decided to contribute to the industry by entering the tourism education and training field. Thus, I joined University of Wisconsin-Stout whose Hotel Management program was five years old at the time. I was attracted to this campus because of its willingness to feature tourism in its curriculum. The earlier years of graduate studies had already frustrated me with the single-minded advocacy voices and positions, leading me to strongly feel that a new medium was needed to foster development of other perspectives on tourism, especially the non-economic, whether positive or negative. The missing treatment became the focus and thrust of  Annals of Tourism Research , which I started in late 1973, one semester after my entering the teaching field.

As expected, especially the advocacy/industry-oriented players or voices of the time did not receive the journal sympathetically. But then the cautionary platform had gained strength and  Annals  started receiving increasing attention, almost totally among members of the academic community. After some five years, the strategies of the journal led to the adoption of “A Social Sciences Journal” as its subtitle, to further encourage importation of theories and methods to tourism from these and other related fields. With an obvious tendency to favor research for the sake of research, with or without immediate applications in the industry,  Annals  parted way from the mainstreams of the time; and with a definite commitment to the formation of knowledge as its raison d’etre, the journal was on its own. The then favored quantitative research methods, used to articulate/substantiate the economic contributions of tourism as an industry, started to make room in  Annals  for qualitative applications to the sociocultural dimensions of tourism as a phenomenon. Since this quarterly journal did not want to be an advocacy voice, it started with the cautionary and quickly found its way to the knowledge-based platform (almost bypassing the adaptancy calls). During the formative years of  Annals , I completed my doctoral studies in cultural anthropology, a discipline which regularly brought nourishment to and inspiration for the journal’s making and shaping.

Now in its 29th year of publication,  Annals  has some 100 editors from over 30 countries, representing diverse multidisciplinary fields. Its 25th Silver Anniversary Supplement (which appeared in 1998) features its 1973-1998 subject index, as well as a complete list of over 2,000 authors and referees who, together with the editors, represent a dedicated army of “explorers” and “excavators” in this field. In the meantime, many new tourism journals have appeared, with each pushing the frontiers in a different direction, resulting in a fast-growing knowledge-based landscape. Presently some 40 journals are engaged in the scientification journey, as well as a growing population of books. For example, in the early 70s, there were only two or three tourism textbooks. Today, practically every week a few new books appear, produced by some very prestigious publishing houses worldwide. The number is much larger if one accounts for books (and journals) published in other languages.

In addition, other forces have been present and pushing the frontiers outward. For instance, initially tourism associations were doing their part in contributing to applied research. But there was need for a group exclusively committed to the advancement of knowledge in this field, without being necessarily concerned with immediate applications or feeling obligated to please business-oriented audiences. Thus, in the early 80s this need led me to think about the formation of an independent academy. After discussion and work with a circle of recognized tourism scholars for a few years, the International Academy for the Study of Tourism was formed in 1988. Admission to this Academy is judged on the basis of one’s scholarly contribution to the advancement of tourism knowledge, requiring the entire membership to vote on each candidate for admission. With 75 positions as its maximum capacity, presently the Academy has about 70 members from some 25 countries. Its biennial meetings, open to the membership and their invited guests only, have already resulted in several scholarly books.

The production of diverse tourism reference books is another example of the maturation of tourism studies. One primary need was for an academic encyclopedia on the subject. After discussing this idea with a couple of publishers in mid-90s, I committed myself to act as its Chief Editor. Through the efforts of some 25 Associate Editors and over 350 authors worldwide to contribute to the making and shaping of its contents, the  Encyclopedia of Tourism  finally appeared in 2000. Its 1,200 plus entries (of various length) cover the building blocks of knowledge which structure and explain the study of tourism, more as a field of research than practice. With its publication another goal on this expedition was reached.

To retrace the earlier phases of the journey in order to acknowledge a land-shaping force in the field, during the advocacy era of the 60s only a handful of colleges and universities in the United States and elsewhere offered predominantly hotel management programs. Then suddenly came a shift in favor of combined hotel/tourism curricula and later freestanding tourism programs. These now offer BS, MS, and PhD programs and research opportunities, each acting as an academic fountain flowing into rivers of knowledge, together irrigating multidisciplinary fields for rewarding harvests. The pattern is international and this development is especially striking when compared with the popularity and growth of other fields.

Where is tourism heading from the present vantage point or conquered grounds? As already noted, its rapid growth and development as an industry has received plenty of attention. Its occasional slow-downs in some parts of the world, even as exceptional as the recent incident of the 2001 attack on the World Trade Center towers in New York City, will prove to be short-term pain for long-term gain, especially as governments, policymakers, and citizens of the world are now recognizing its multidimensional global importance. Hearing U.S. policymakers speak on behalf of tourism, and even seeing President Bush in television ads promoting travel and tourism, all suggests how strong the economic poles and fortresses of the industry have become and heading to. But, again, a discussion of tourism as an industry (its present shape and future prospects) belongs to another paper, and so does its full institutionalization in the everyday social fabric of peoples everywhere. What marks the boundaries of this commentary is its focus on tourism as a field of study and scholarship. So what does lie ahead within the already established and outlying academic parameters?

To me, this forward movement will continue zealously, now more than before with a better sense of direction and informed vision. I see more scholarly journals taking their debuts in immediate years ahead, each wanting to carve out and contribute to a niche territory for itself, each trying to compete for a (the) lead position—a necessary academic exercise that should expedite the scientification course of tourism. The number of universities committing to the study will continue to grow, with many accommodating research rather than application of it as their thrusts. Various disciplines, especially social sciences, will more openly adopt tourism as a research area, both on campuses and in various disciplinary membership associations (a process which is already on its way). Other fields or disciplines will (re)discover tourism in new ways, as for example the deep-seated but unexplored relationship of medicine/health care/healthy lifestyle and tourism will be fully explored and exploited. In a different vein, tourism—as a regular importer of knowledge from other fields in order to form its own building blocks—will more forcefully export knowledge to the very fields from which has been generously borrowing, with more heavy flows ahead.

Further, it will become more evident to governments that tourism is not just a trade or an industry, but a phenomenon, a sociocultural right and privilege, a must for healthy life and economy, which must be studied and understood, and its uses and applications should not and cannot be limited to the economic fortune that it reportedly generates. With this recognition, government tourism offices (whether called Ministry, Secretary, or Board of Tourism) will employ people who have studied tourism and understand it both as an industry and a phenomenon, a development that would be a drastic departure from the present profile of their personnel. The industry itself will finally be meeting its academic partner—which it has hardly noticed so far—and will begin to offer energizing support for its maintenance and the fueling of its forward mission, including financing graduate students in this field, funding more specialized endowed chairs, and confidently anchoring upon the multidisciplinary foundation that tourism has amassed during the past few decades.

To conclude, tourism—both as an industry and a sociocultural phenomenon/field of study, with strong national and international economic position and with firm footholds on major university campuses worldwide—is here to stay, with its journey continuing toward its well-deserved summits. The past achievements will soon seem meager as it nears its destined horizons, with many histories to be written to record and celebrate its multidisciplinary scientification, detailing challenges faced, and peaks conquered. This coming of age (with the above undercurrents as examples) promises deserving occasions to celebrate the heightening of scholarship in this academic field.

Jafar Jafari  is Editor-in-Chief of Annals of Tourism Research and Founding President of International Academy for the Study of Tourism. He would like to observe that the substance of this brief paper is in keeping with the invitation extended to him by the editor of  ReVista : “Had the same invitation been extended to someone else—to present an outline of the landmarks in his/her academic journey in the field of tourism—a different paper with different examples would have been produced. Although clear, this disclaimer seems especially in order in this burgeoning field of study.”

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Stimulating Tourist Inspiration by Tourist Experience: The Moderating Role of Destination Familiarity

Jianping xue.

1 College of Management, Shenzhen University, Shenzhen, China

2 School of Economics and Management, Yibin University, Yibin, China

Zhimin Zhou

Salman majeed.

3 International Center for Hospitality Research & Development, Dedman College of Hospitality, Florida State University, Tallahassee, FL, United States

Ruixia Chen

4 School of Tourism Management, Henan Finance University, Zhengzhou, China

Associated Data

All datasets generated for this study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding author.

The tourist experience is a core indicator of destination management for the comprehensive evaluation of destination value. Tourist experience and tourist inspiration are important concepts in the stream of research on destination marketing and management. However, these relationships remained under-explored in the extant literature. This study examined the impact of tourist experience on tourist inspiration under the moderating impact of destination familiarity. To achieve the objective of this study, data were collected online from 622 Chinese tourists. We employed partial least squares structural equation modeling (PLS-SEM) to statistically analyze the gathered data. Findings show that four types of tourist experiences, namely education, esthetics, entertainment, and escapism, significantly and positively influenced the inspired-by state of tourist inspiration, which further influenced the inspired-to-state of tourist inspiration. Destination familiarity exerted a significantly negative moderating impact on the relationship between education experience and inspired-by state of tourist inspiration. Sensitivity analysis presents that education experience was the strongest predictor of the inspired-by state followed by aesthetics, escapism, and entertainment facets of the tourist experience. Findings contribute to the theory and practice of tourism management with a robust interpretation of tourist experience, tourist inspiration, and destination familiarity to solidify the effective management of tourist destinations. Limitations and future research directions are noted.

Introduction

Shopping and consumption at a tourist destination is an important tourist behavior, which fuels destination revenue and revitalizes local economies, especially in the context of declining tourist inflow during destination crises, such as the COVID-19 pandemic ( Rasoolimanesh et al., 2021 ). Tourist behavior, such as purchase and consumption of destination products and services, is often sudden, temporary, unplanned, and is inspired by destination situation and tourist experience during tourist visit to a destination ( Woodside and King, 2001 ). For example, at the Lantern Festival in China, tourists in Zigong, a city in Sichuan Province of China, get inspired by Zigong’s special cultural lanterns, and make unplanned and sudden purchase decisions about Zigong’s specialty lanterns. Inspiration is a motivational state that promotes the transition from consumption ideas to consumption behavior ( Böttger et al., 2017 ). The inspiration theory advocates that an individual may get inspired by new things to generate novel ideas, and the transcendence of these ideas may promote an individual’s intrinsic motivation to realize new ideas ( Thrash and Elliot, 2003 ).

Tourist inspiration is defined as a motivational state that drives tourists to realize consumption-related new ideas ( Böttger et al., 2017 ; Dai et al., 2022 ). Inspiration includes three core characteristics, i.e., evocation, transcendence, and approach motivation, and two states, i.e., an inspired-by state and an inspired-to state ( Thrash and Elliot, 2004 ). Evocation means that external stimuli provoke inspiration, which is a spontaneous process rather than self-awakening ( Böttger et al., 2017 ; Dai et al., 2022 ). Transcendence means that an individual discovers new and better possibilities, which have never been discovered in the past ( Winterich et al., 2019 ), with a feeling of positivity, clarity, and self-enhancement ( Böttger et al., 2017 ). Finally, approach motivation refers to an individual’s inner drive to turn new ideas into actions ( Dai et al., 2022 ). The inspired-by state of tourist inspiration is an epistemic activation component ( Böttger et al., 2017 ) that demonstrates how external stimuli, such as destination environment, activities, and marketing efforts, induce consumption-related ideas into tourist cognitive filters and generate tourist awareness about new and better consumption possibilities ( Winterich et al., 2019 ). The inspired-to state is an intention component ( Böttger et al., 2017 ) that demonstrates how a tourist derives an intrinsic motivation to actualize consumption-related ideas. Tourist inspiration drives consumption-related ideas into tourist consumption behavior, which may provide a potential shortcut to characterize tourist purchase decisions ( Dai et al., 2022 ). Scholars document that the inspired-by-state significantly and positively affects the inspired-to state ( Böttger et al., 2017 ; Izogo et al., 2020 ). Tourist inspiration occurs when the inspired-by state and the inspired-to-state exist in a causal and sequential manner ( Thrash et al., 2014 ). Previous studies on the tourist decision-making process mainly focused on pre-travel tourist destination choice decisions and ignored tourist consumption and purchase decisions during a tourist visit to the destination ( Dai et al., 2022 ). Research on tourist inspiration and associated consumption-related decision-making process during tourist visit to a destination remained mixed and fragmented in the extant literature, which demands research attention for conclusive evidence.

Tourists are consumers of destination products and services; however, tourist purchase decision might be different from ordinary consumer purchase decision. As a classic theory of the consumer decision process, the Engel-Kollat-Blackwell (EKB) model assumes that consumer decision-making is a completely rational process ( McCabe et al., 2016 ) that passes through five stages, i.e., need recognition, information search, evaluation of alternatives, purchase choice, and post-purchase ( Darley et al., 2010 ). Given the facts of information overload or information insufficiency, cognitive limitations, and personal energy/time/cost constraints, tourists are not fully rational to find and evaluate available potential alternatives ( Wattanacharoensil and La-ornual, 2019 ). Tourist consumption behavior reflects the pursuit of pleasure rather than utility maximization ( Dai et al., 2022 ). The five stages of the EKB model sometimes do not fully correspond to tourist purchase decision-making process. It is because the EKB model’s decision-making stages may be simplified or even omitted by tourists during the information search and evaluation of alternatives during the consumption-related decision-making process. Thus, the EKB model may fail sometimes in explaining tourist consumption-related decision-making processes during tourist visit to destinations. Dual-system theories propose that there are two distinct and complementary decision-making systems. System 1 relies on emotions to make decisions, which is an intuitive response, with rapid, heuristic, and affect-driven characteristics. System 2 relies on cognition to make decisions, which is a process of deliberate considerations, with slow, rational, analytic, and reflective characteristics ( Kahneman, 2011 ). Ordinary consumers who make purchase decisions following the decision-making steps of the EKB model are more likely to rely on System 2 of the dual-system theories, while tourists who make purchase decisions following tourist inspiration are more likely to rely on System 1 of the dual-system theories. Tourists get inspired by discoveries or new experiences obtained from the destination environment, activities, and marketing efforts, which prompt tourists to get new consumption-related ideas ( Böttger et al., 2017 ; Dai et al., 2022 ). A unique and novel travel-related experience gleaned from tourist interaction with a destination stimulates tourist imagination and fuels tourist inspiration. Since tourist inspiration promotes the transition of new consumption-related ideas to consumption behavior ( Böttger et al., 2017 ), it is important to explore the factors that trigger tourist inspiration, which remained under-explored in the previous studies ( Khoi et al., 2019 ; He et al., 2021 ). A profound understanding of tourist inspiration may bridge the gap where the EKB theory may not fully explain tourist’s consumption-related decision-making processes during visits to tourist destination.

The tourist experience is defined as an interaction between a tourist and a destination ( Stamboulis and Skayannis, 2003 ). An individual’s experience of destination events may be unique and completely different from that of others ( Pine and Gilmore, 1998 ; Stamboulis and Skayannis, 2003 ). Scholars document the notion of the tourist experience in terms of education, esthetics, entertainment, and escapism realms of the tourist experience ( Oh et al., 2007 ). The experience economy creates memorable events for individuals ( Pine and Gilmore, 1999 ). From the perspective of the experience economy, the notion of tourist experience has been examined by scholars across different fields ( Larsen, 2007 ; Ritchie and Hudson, 2009 ; Volo, 2009 ). Existing research in the stream of tourism attempted to explore the outcomes of tourist experience, such as tourist wellbeing ( Hwang and Lee, 2019 ), pleasant arousal ( Loureiro, 2014 ), and tourist inspiration ( He et al., 2021 ). A study on wellness tourism experience explored the relationship between tourist experience and tourist inspiration and found that education, esthetics, and escapism facets of tourist experience significantly impact tourist inspiration except for entertainment experience ( He et al., 2021 ). Different tourism-related studies emphasize the dimensions of tourist experience differently and report mixed findings in a specific context that limit the generalizability of the findings of the studies. For example, Luo et al. (2018) focused on escaping and education dimensions of the tourist experience in the context of wellness tourism and Choi and Choi (2018) examined the entertainment and escaping dimensions of the tourist experience in the context of mass tourism. He et al. (2021) focused on tourist experience and measured tourist inspiration in the context of wellness tourism. Nevertheless, there is a need to investigate the impact of tourist experience on tourist consumption-related inspiration in the broader context of tourism, such as conventional tourism. This study examines the relationship between tourist experience and tourist consumption-related inspiration in a conventional context of tourism, which is broad, to expand the generalizability of the conceptual understanding of the tourist experience and tourist inspiration. Moreover, this study explores how education, entertainment, esthetics, and escapism dimensions of the tourist experience affect tourist inspiration, i.e., the inspired-by-state that ultimately affects the inspired-to-state of tourist inspiration.

Destination familiarity means tourists’ subjective assessment of their existing knowledge and information alongside learning new knowledge and skills during visits to tourist destinations ( Hernández Maestro et al., 2007 ). Some tourists prefer to choose unfamiliar destinations to obtain a novel travel experience ( Chark et al., 2020 ), which increases the probability of tourist inspiration, while some tourists get inspired by familiar destinations to obtain a stable travel experience with intentions to reduce travel-related uncertainties, which reduces the probability of tourist inspiration ( Kim et al., 2019 ). From this, it is discerned that destination familiarity exerts its impact on the relationship between tourist experience and tourist inspiration. Existing studies show that tourists who are familiar with a destination exhibit positive attitude and behavioral intentions, such as intention to visit tourist destination ( Chaulagain et al., 2019 ; Shi et al., 2022 ), satisfaction ( Sanz-Blas et al., 2019 ), and destination evaluation ( Chen et al., 2017 ; Kim et al., 2019 ). Scholars believe that destination familiarity may increase tourist confidence in choosing a destination in parallel to triggering tourist decision-making process to choose familiar destinations ( Milman and Pizam, 1995 ). Tourists’ prior knowledge or destination familiarity may increase tourists’ sense of safety and reduce tourists’ perceptions of perceived risk during visits to destinations ( Karl, 2016 ).

An individual’s familiarity affects his/her information search behavior ( Gursoy, 2019 ). While taking decisions to visit a tourist destination and consume destination products and services, tourists who are familiar with destinations reduce their search for external information regarding tourist destination because such familiar tourists hold sufficient destination information ( Gursoy and McCleary, 2004a ). On the other hand, unfamiliar tourists lack sufficient destination-related information and, thus, increase their search for external information regarding tourist destinations to reduce the levels of uncertainty and perceived risk during travel to tourist destinations ( Carneiro and Crompton, 2009 ; Karl, 2016 ). The inspiration theory maintains that inspiration is triggered by external stimuli rather than internal self-awakening ( Böttger et al., 2017 ; Dai et al., 2022 ). External stimuli may likely trigger more tourist inspiration in low-familiar tourists as compared to high-familiar tourists ( Böttger et al., 2017 ; Winterich et al., 2019 ). From the perspective of tourist consumption-related decision-making, tourists who are familiar with a destination are more likely to make decisions based on the system 2 approach of the dual-system theories, which is similar to the theoretical premises of the EKB model. It is because high-familiar tourists might have sufficient destination information for a rational decision to visit a tourist destination ( McCabe et al., 2016 ). However, low-familiar tourists are more likely to make decisions based on the system 1 approach of the dual-system theories, which is similar to tourist consumption-related inspiration. It is because tourists might lack sufficient destination information and rely on their intuition and cognitive reactions to external stimuli for consumption-related destination decision-making ( McCabe et al., 2016 ). However, studies that demonstrate the role of tourist destination familiarity in tourist decision-making to visit tourist destinations remained succinct. Drawing on the above and to bridge the identified research gap, this study also examines how destination familiarity exerts its moderating impact on the relationship between tourist experience and tourist inspiration.

This study aims to examine the following: (1) How does tourist inspired-by state impact tourist inspired-to state? (2) How does tourist experience impact tourist inspiration, i.e., tourist inspired-by state? (3) How does tourist destination familiarity exert its moderating impact on the relationship between tourist experience and tourist inspiration, i.e., tourist inspired-by state? Findings unravel the psychological mechanism of tourist purchase motivation from the perspective of tourist inspiration. This study fills theoretical gaps with a proposed conceptual framework and offers guidelines to destination marketing organizations (DMOs) in solidifying destination management and promotion efforts to skyrocket sales revenue of tourist destination. This study provides roadmaps for scholars and practitioners to conduct future research on destination marketing and management.

Literature Review

Tourist inspiration: inspired-by state and inspired-to state.

Customer inspiration is defined as a state of temporary motivation evoked by corporate marketing efforts, promoting the generation of new ideas related to consumption, and driving consumers to take action on new ideas ( Böttger et al., 2017 ). As an important concept of the inspiration theory in marketing, customer inspiration includes inspired-by and inspired-to states in its breadth and depth and focuses on the generation of new ideas inspired by corporate marketing efforts and customer consumption behavior ( Böttger et al., 2017 ). Tourist inspiration and its cognitive importance in tourist decision-making have gained the widespread attention of scholars and practitioners from different fields ( Khoi et al., 2019 ; Khoi et al., 2021 ; Dai et al., 2022 ). Dai et al. (2022) note the importance of travel inspiration at the tourist dreaming stage and refer travel inspiration as a motivational state that may influence tourist behavior, such as tourist destination choice. Gollwitzer (1990) proposed the mindset theory of action phases and divided the consumer decision-making process into two phases i.e., a pre-decision phase of deliberation and a post-decision phase of implementation, embodying a sequential relationship. Böttger et al. (2017) argue that the inspired-by state belongs to the deliberation phase, while the inspired-to-state reflects the transition to the implementation phase. In the stream of tourist inspiration, there is a causal and sequential relationship between the inspired-by state and the inspired-to state where the inspired-by-state exists before the inspired-to state ( Böttger et al., 2017 ; Cao et al., 2021 ; Dai et al., 2022 ).

External stimuli, such as destination environment, destination events, and discovery of new possibilities in a tourist destination, may trigger tourist inspired-by-state in tandem with generating new ideas regarding tourist consumption with self-transcendence ( Khoi et al., 2019 ). According to the theory of self-determination, the attractiveness of new ideas regarding tourist consumption drives tourist self-realization and fuels tourist unplanned purchases ( Ryan and Deci, 2000 ), which is sketched as the inspired-to state of tourist inspiration on the canvas of this study. For example, when a tourist is inspired by a product with destination characteristics, the idea of purchasing such a product and giving the same to a friend as a gift may emerge naturally ( Böttger et al., 2017 ). The appropriateness of the product as a gift becomes an internal driving force that generates tourist purchase intention, which is an inspired-to state of tourist inspiration ( Thrash and Elliot, 2004 ). Some scholars argue that inspired-by state may also be a precursor to inspired-to state ( Hinsch et al., 2020 ; Izogo et al., 2020 ; Izogo and Mpinganjira, 2020 ). For example, in a cross-cultural study, Izogo et al. (2020) found that inspired-by state significantly and positively affects the inspired-to state. Similar findings were found in research on augmented reality ( Hinsch et al., 2020 ) and social media content ( Izogo and Mpinganjira, 2020 ). However, most studies advocate the causal and sequential impact of inspired-by state on inspired-to state ( Böttger et al., 2017 ; Dai et al., 2022 ). Thus, there is a need to testify the impact of inspired-by state on inspired-to state for conclusive evidence. Drawing on most studies reflecting the impact of inspired-by state on inspired-to state, we propose the following hypothesis.

• Hypothesis H1 : Tourist inspired-by state exerts a significantly positive impact on the inspired-to state of tourist inspiration.

Tourist Experience

The tourist experience is the application of the experience economy in a tourism context. The concept of the experience economy is widely accepted by tourism scholars and practitioners. According to the two dimensions of customer connections, namely absorption and immersion, and the level of customer participation, namely passive and active participation, four experience realms of tourist experience are identified in the extant literature for business promotion, i.e., education, esthetics, entertainment, and escapism ( Pine and Gilmore, 1999 ). A unique tourist experience stems from an interaction between destination event and tourist cognitive reaction ( Pine and Gilmore, 1998 ) that may stimulate tourist psychological arousal ( Hosany and Witham, 2010 ) alongside provoking tourist inspiration ( Khoi et al., 2019 ). Tourist experience influences tourist psychological arousal, which is the first step toward tourist inspiration ( Loureiro, 2014 ).

Education Experience

Education experience may impact tourist inspiration ( Whiting and Hannam, 2014 ). Tourists attempt to find new ways to gain new knowledge about tourist destinations to improve consumption-related decision-making ( Oh et al., 2007 ). Education experience has two characteristics, i.e., active participation and absorption ( Pine and Gilmore, 1998 ). From the perspective of tourism, education experience allows tourists to acquire new knowledge and skills to identify new and better possibilities, stimulates tourist imagination, and generates new ideas relevant to tourist consumption of destination products and services ( Winterich et al., 2019 ). Since tourist inspired-by state is an epistemic activation process, which reflects evocation and transcendence of tourist inspiration ( Böttger et al., 2017 ), tourists learn new knowledge and skills as a part of educational experience during visits to a tourist destination that may inspire tourists, trigger tourist novel consumption-related ideas, and grab tourist attention, which reflects the evocation characteristics of tourist inspiration ( Pine and Gilmore, 1999 ; Dai et al., 2022 ). The discovery of new and better possibilities during visits to a tourist destination allows tourists to realize the quality of new ideas and gain a sense of self-transcendence, which reflects the transcendence characteristics of tourist inspiration ( Thrash and Elliot, 2003 ). Therefore, we propose the following hypothesis.

• Hypothesis H2 : Education experience exerts a significantly positive impact on the inspired-by state of tourist inspiration.

Entertainment Experience

Personal experience linked to entertainment is the most emphasized dimension of the tourist experience in destination marketing ( Pine and Gilmore, 1999 ). Destination performances and activities attract tourist attention and make tourists feel happy and excited about destination performances and activities ( Oh et al., 2007 ). During this process, tourists do not directly participate in destination activities, which presents that entertainment experience encapsulates the characteristics of passive participation and absorption in its breadth and depth. It is noted that entertainment experience provokes tourist positive emotions when tourists watch a destination performance ( Hwang and Lee, 2019 ). The broaden-and-build theory in the field of positive psychology argues that positive emotions broaden individuals’ cognitive scope alongside building individuals’ physical, intellectual, social, and psychological resources ( Fredrickson, 2001 ). Existing shreds of evidence demonstrate that the broaden-and-build theory has been applied to research on tourist wellbeing ( Sirgy, 2019 ), value co-creation ( Lin et al., 2017 ), and social media sharing behavior ( Chen et al., 2021 ). Tourists with positive emotions are more open-minded, flexible to adopt changes, and able to generate more creative ideas, which can promote tourist self-efficacy to overcome destination challenges ( Chen et al., 2021 ). According to the broaden-and-build theory, positive emotions instantly expand an individual’s creative thinking ( Fredrickson, 2001 ). Watching destination performances may stimulate tourists’ happy feelings, promote broader and more imaginative tourist thinking, and generate new ideas regarding tourist consumption. Destination performances and activities may activate tourists’ positive emotions to gain new consumption-related ideas, which reflect the evocation characteristic of tourist inspired-by state. New ideas and creative solutions induce a feeling of self-transcendence, which reflects the transcendence characteristic of the inspired-by state of tourist inspiration ( Thrash and Elliot, 2003 ). Thus, we also propose the following hypothesis.

• Hypothesis H3 : Entertainment experience exerts a significantly positive impact on the inspired-by state of tourist inspiration.

Esthetics Experience

The esthetics experience is a process in which tourists feel and appreciate objective matters and the environment ( Pine and Gilmore, 1999 ). Tourists feel completely immersed in the objective environment and start perceiving and explaining esthetic meanings of destination environment from their unique perspectives, which may trigger tourist inspiration ( Khoi et al., 2019 ). Hosany and Witham (2010) document that an individual’s interpretation of the physical environment fuels an individual’s esthetic experience. Tourists are immersed in the destination environment, passively appreciate, and feel destination beauty, and do not intend to bring changes to destination environment ( Oh et al., 2007 ). This process requires an individual’s full concentration on the environment ( Pine and Gilmore, 1999 ). Therefore, esthetic experience mirrors the characteristics of both passive participation and immersion ( Pine and Gilmore, 1998 ). Esthetic appreciation has a strong cognitive component that requires tourists to invest energy and cognitive resources. When tourists are inspired by the beauty of objective matters or the environment of a destination, tourists discover new and better possibilities in generating consumption-related new ideas ( Khoi et al., 2019 ). Drawing on the above, we propose the following hypothesis.

• Hypothesis H4 : Esthetics experience exerts a significantly positive impact on the inspired-by state of tourist inspiration.

Escapism Experience

Escaping reality is an important motivation for tourists ( Kozak, 2002 ). Tourists temporarily escape the unsatisfactory aspects of daily life and seek places to tour and participate in activities arranged at tourist destinations ( Oh et al., 2007 ). Therefore, escapism has the characteristics of both active participation and immersion ( Pine and Gilmore, 1998 ). To escape reality, tourists expect to travel to specific tourist destinations and participate in destination activities to distance themselves from daily life matters for rest, relaxation, and a feeling of stress alleviation. Traveling to tourist destinations allows tourists to feel that they are in a different time and space and this feeling helps tourists to enjoy a new lifestyle with new and better possibilities of life activities in tourist destinations alongside inspiring tourists with new consumption-related ideas ( Pine and Gilmore, 1999 ). Based on the above, we propose the following hypothesis.

• Hypothesis H5 : The escapism experience exerts a significantly positive impact on the inspired-by state of tourist inspiration.

The Moderating Role of Destination Familiarity

As an important construct in the field of marketing, familiarity with a product or brand refers to consumer experience and knowledge about a product or brand that may influence consumer decision-making regarding a product or brand ( Alba and Hutchinson, 1987 ). Previous studies present that consumer positive decision-making and resultant favorable behavior are linked to consumer familiarity with brand products or services, such as first-time and repeat purchases ( Tam, 2008 ; Paasovaara et al., 2012 ), as compared to consumer unfamiliarity with brand products or services. Destination familiarity is defined as an individual’s subjective assessment of destination information and knowledge ( Hernández Maestro et al., 2007 ). Tourists’ behavioral intentions are influenced by tourists’ subjective familiarity assessment of destination attributes ( Rao and Sieben, 1992 ; Park et al., 1994 ). When tourists feel that they are familiar with a tourist destination, they are more confident in their decision-making to visit tourist destinations ( Milman and Pizam, 1995 ).

Existing studies show that destination familiarity has an important impact on tourist information search behavior ( Gursoy, 2019 ). Tourists first conduct an internal search to obtain desired information from their memory and experience ( Coupey et al., 1998 ). Tourists who extract desired information from their memory attempt to make informed decisions and do not engage in additional information search from external sources ( Brucks, 1985 ). Tourists who do not find the desired information from their memory and experience search for information from external sources for rational travel-related decision-making ( Gursoy and McCleary, 2004b ). Evocation as a salient feature of tourist inspiration means that tourist inspiration is spontaneously evoked by an external stimulus ( Böttger et al., 2017 ; Dai et al., 2022 ). Tourist inspiration is more likely to be triggered in low-familiar tourists as compared to in high-familiar tourists, because information obtained from outside may help tourists learn new knowledge, make discoveries, and gain new insights, which stimulate tourist imagination ( Winterich et al., 2019 ). High-familiar tourists extract information from their memory and experience for decision-making, which may not fully trigger tourist inspiration due to the lack of external new things ( Böttger et al., 2017 ). Tourists who are familiar with destinations show the favorable evaluation of destination attributes and develop positive behavioral intentions as compared to unfamiliar destinations ( Chaulagain et al., 2019 ; Sanz-Blas et al., 2019 ; Shi et al., 2022 ). Previous studies note that destination familiarity moderates the relationship between brand equity and tourist revisit intention ( Shi et al., 2022 ), the relationship between logotype and tourist attitude toward a destination ( Roy and Attri, 2022 ), and the relationship between perceived quality and tourist visit intention ( Chi et al., 2020 ). As tourist familiarity with a destination will increase, novel experiences and discoveries from external stimulation will decrease, which will reduce tourist inspiration. Therefore, we also propose the following hypotheses.

• Hypothesis H6 : Destination familiarity exerts a significant moderating impact on the relationship between education experience and the inspired-by state of tourist inspiration such that the relationship is weak when destination familiarity is high.
• Hypothesis H7 : Destination familiarity exerts a significant moderating impact on the relationship between entertainment experience and the inspired-by state of tourist inspiration such that the relationship is weak when destination familiarity is high.
• Hypothesis H8 : Destination familiarity exerts a significant moderating impact on the relationship between esthetics experience and the inspired-by state of tourist inspiration such that the relationship is weak when destination familiarity is high.
• Hypothesis H9 : Destination familiarity exerts a significant moderating impact on the relationship between escapism experience and the inspired-by state of tourist inspiration such that the relationship is weak when destination familiarity is high.

The proposed theoretical associations among the constructs of this study are presented in Figure 1 .

Conceptual model.

Methodology

Questionnaire design.

A survey questionnaire was designed to gather data from Chinese respondents having tourist experience. Screening questions were made a part of the survey questionnaire: (1) What type of destination was your last trip? (2) What is the name of your recently visited tourist destination? (3) How recent is your tourist experience? To measure the proposed constructs in this study, scale items were adapted from the previous studies. Scale items for education, esthetics, entertainment, and escapism dimensions of tourist experience were adapted from Oh et al. (2007) , scale items for tourist inspiration (including the inspired-by state and the inspired-to state) were adapted from Böttger et al. (2017) , and scale items for destination familiarity were adapted from Gursoy and McCleary (2004a) . All scale items were measured using a seven-point Likert scale, which ranged from 1 (strongly disagree) to 7 (strongly agree) (see Appendix 1). Scholars document that the seven-point Likert scale is well-suited to conduct online surveys ( Chaulagain et al., 2019 ). The survey questionnaire was originally developed in English. Three native Chinese doctoral students, who were proficient in English and had academic and industry experience in tourism marketing, were invited to translate the English version of the questionnaire into Chinese. By following the work of Majeed et al. (2020a) , we used the blind-translation back-translation method to translate the English version of the questionnaire into the Chinese language. Two bilingual professors, who were unfamiliar with the field were invited to convert the translated Chinese version of the survey questionnaire into English. The quality of the English and Chinese versions of the survey questionnaires were compared for clarity and similar intended meanings of the questions and minor adjustments were made to the content and composition of the survey questionnaire before the full launch of the survey ( Chen et al., 2020 ).

Data Collection

This study conducted an online survey at Wenjuan Xing 1 , a professional online academic survey platform in China, between November 5, 2019 and November 10, 2019, to gather data from Chinese tourists who were at least 18 years old to ensure the consent requirement of the study respondents ( Majeed et al., 2020b ; Xue et al., 2020 ). Wenjuan Xing undertakes a random sampling method to administer surveys and records responses from its more than three million registered users, who demonstrate diverse backgrounds and belong to different cities in China ( Cao et al., 2021 ). Wenjuan Xing adopts a multichannel approach to distribute questionnaires to randomly invited users to reflect a greater representation of the relevant study population for the survey ( Cao et al., 2021 ). The participants in the online survey were Chinese adult tourists who had traveled to tourist destinations. A total of 626 responses were received during the data collection process. After removing responses carrying missing values and respondent age as less than 18 years, a total of 622 were retained for the final analysis.

Study Respondents’ Demographic Details

The number of male and female respondents in this study was relatively balanced, accounting for 45.7 and 54.3%, respectively (see Table 1 ). Most respondents were under the age of 40 years (80.38%), corporate staff (66.1%), and were married (67.2%). Table 1 shows that approximately 67.4% of the study respondents mentioned their education level as undergraduate. Approximately 63.5% of the study respondents mentioned 2–3 trips per year, 62.8% of respondents traveled for the first time, 50.6% of respondents liked to travel with family, and 31.5% respondents liked to travel with friends. Approximately 94.1% of respondents traveled to domestic tourist destinations. Destinations related to natural and heritage landscapes were favored by most of the study respondents, i.e., 47.7 and 42.1%, respectively. Approximately 74.8% of the study respondents visited tourist destinations within the previous 3 months from the date of the survey.

Demographic and destination characteristics.

Data Analysis Strategy

The four realms of tourist experience and the two states of tourist inspiration are lower-order latent variables in this study. Partial least square structural equation modeling (PLS-SEM) was employed to test the proposed relationships among tourist experience, tourist inspiration, and destination familiarity. PLS-SEM is preferred to the co-variance-based approach because PLS-SEM is one of the most used methods in analyzing the structural relationships of latent variables ( Chin and Newsted, 1999 ) and moderating roles ( Wong, 2016 ; Nitzl and Chin, 2017 ). Smart PLS 3.2.7 was used for data analysis in this study.

Measurement Model Results

Table 2 presents the items and reliability evaluation results of the constructs of the study. Except for three items in the range from 0.667 to 0.697, which is above the minimum acceptable value of 0.50 recommended for factor loadings ( Hair et al., 2010 ), all factor loadings were above 0.70 and were considered acceptable ( Chin, 1998 ). The Cronbach’s alpha and composite reliability values of all constructs were above the recommended threshold of 0.70 ( Nunnally and Bernstein, 1994 ), indicating good internal reliability of the study constructs.

Measurement model results.

AVE, average variance extracted; CR, composite reliability; α, Cronbach’s alpha.

a Reverse coded.

The convergent validity and discriminant validity of each construct were evaluated. The average variance extracted (AVE) of all constructs ranged from 0.582 to 0.772 (see Table 2 ), which is above the recommended threshold of 0.50, indicating that all constructs of the model have good convergent validity ( Fornell and Larcker, 1981 ). The Fornell-Larcker criterion and the heterotrait-monotrait (HTMT) ratio were calculated to evaluate the discriminant validity of the constructs ( Henseler et al., 2015 ; Hair et al., 2021 ). Table 3 shows that the square root of the AVE of each construct was found greater than the correlation coefficient of other constructs, indicating that all constructs have good discriminant validity and met the Fornell-Larcker criterion. The maximum value of the HTMT ratio ( Table 4 ) was found as 0.857, which is less than the recommended threshold of 0.90 ( Henseler et al., 2015 ; Rasoolimanesh et al., 2021 ), indicating that all constructs had acceptable discriminant validity.

Fornell-Larcker criterion.

Bold diagonal values represent the square root of AVEs.

Heterotrait-monotrait (HTMT) ratio.

Structural Model Results

Before the bootstrapping procedure, destination familiarity was set as a moderator, inspired-by state as a dependent variable, and education, entertainment, esthetics, and escapism dimensions of tourist experience as independent variables to generate four moderating impacts. Since destination familiarity is a reflective-reflective construct in this study, a product indicator calculation method was selected while generating the moderating impact on the relationship between dimensions of tourist experience and the inspired-by state of tourist inspiration. To exclude the influence of other factors, demographic and destination variables mentioned in Table 1 were operationalized in the model as control variables. Complete bootstrapping with 5,000 sub-samples was performed to examine the hypothesized relationships presented in the conceptual model. Findings ( Table 5 ) show that R 2 values of the dependent variables are over 0.1 and Q 2 values are over 0, presenting the predictive ability and predictive relevance of the structural model ( Falk and Miller, 1992 ). To solidify the investigation of the goodness of fit and the significance of hypothesized relationships in the model, path coefficients were examined. Findings ( Table 5 ) show that inspired-by state has significantly positive impact on inspired-to state (β = 0.431, t = 10.456, p < 0.001). Thus, hypothesis H1 is supported. Findings for education experience (β = 0.373, t = 9.606, p < 0.001), entertainment experience (β = 0.184, t = 4.685, p < 0.001), esthetics experience (β = 0.218, t = 5.612, p < 0.001), and escapism experience (β = 0.231, t = 7.122, p < 0.001) show that education, entertainment, esthetics, and escapism dimensions of tourist experience exert significantly positive impact on the inspired-by state of tourist inspiration. Therefore, hypotheses H2, H3, H4, and H5 are supported. Findings show that destination familiarity has a significantly negative impact on the relationship between education experience and inspired-by state of tourist inspiration (β = −0.109, t = 3.095, p < 0.05), indicating that when tourist destination familiarity is high, the relationship between education experience and the inspired-by state of tourist inspiration is weak. This supports hypothesis H6. However, findings show that destination familiarity has no moderating impact on the relationship between entertainment experience and inspired-by state (β = 0.002, t = 0.051, p > 0.05), between esthetics experience and inspired-by state (β = 0.049, t = 1.523, p > 0.05), and between escapism experience and inspired-by state (β = 0.042, t = 1.38, p > 0.05). Thus, hypotheses H7, H8, and H9 are not supported. The structural model of the study is presented in Figure 2 .

Path analysis.

*Destination familiarity = the moderating role of destination familiarity; *p < 0.05, ***p < 0.001.

Path co-efficient model. * P < 0.05, ** P < 0.01, *** P < 0.001, n.s P > 0.05.

Sensitivity Analysis

The objective of sensitivity analysis is to determine how much of the change in the dependent variable is caused by the change in the relevant independent variable ( Han et al., 2021 ) and to obtain a ranking of the importance of the independent variable’s influence on the dependent variable ( Ahani et al., 2017 ; Leong et al., 2020 ). Artificial neural network (ANN) modeling is the most used method for sensitivity analysis because of its obvious advantages over traditional statistical methods ( Sharma et al., 2021 ), such as regression analysis. ANN does not require the data to follow a normal distribution and is also suitable for the analysis of non-linear relationship variables ( Tan et al., 2014 ; Leong et al., 2020 ). An ANN model usually consists of three layers, namely the input layer, the hidden layer, and the output layer, and each layer is connected by an activation function ( Sharma et al., 2021 ). In terms of activation function, the sigmoid function is generally considered by researchers due to its advantages of squeezing the original data ( Chiang et al., 2006 ). The IBM’s SPSS 21 neural network module and its multilayer perceptron were employed to perform ANN analysis and a feed-forward-backward-propagation (FFBP) algorithm for training and testing data in this study ( Taneja and Arora, 2019 ). In line with Leong et al. (2020) , 90% of data was used for training, while the remaining 10% of data was used for testing where sigmoid is the activation function for the hidden and output layers ( Sharma and Sharma, 2019 ). Referring to the method of Sharma et al. (2021) , a 10-fold cross-validating procedure was used to avoid the overfitting problem in ANN analysis. The root mean square error (RMSE) is widely used by scholars to validate the results of the ANN analysis ( Chong, 2013 ; Liébana-Cabanillas et al., 2017 ), and, hence, followed for ANN analysis in this study.

To analyze the importance of education, entertainment, esthetics, and escapism dimensions of tourist experience and their associated impact on the inspired-by state of tourist inspiration, we constructed one ANN model. In the ANN model, the four dimensions of tourist experience, i.e., education, entertainment, esthetics, and escapism, are in the input layer, the inspired-by state of tourist inspiration is in the output layer, and there are three hidden nodes in the hidden layer (see Figure 3 ). Table 6 shows that the average RMSE values for both training and testing processes were relatively small at 0.074, indicating an excellent model fit ( Leong et al., 2019 ; Leong et al., 2020 ). To rank the predictive power of the input neurons, a sensitivity analysis was performed. Table 7 shows the importance and normalized importance of each input neuron, i.e., education, esthetics, entertainment, and escapism dimensions of the tourist experience. The value of normalized importance refers to the importance of each input neuron divided by the maximum importance and expressed as a percentage ( Leong et al., 2020 ). The results of the sensitivity analysis showed that education experience had the greatest normalized importance at 98.1%, suggesting that education experience was the most powerful predictor of the inspired-by state followed by esthetics (59.3%), escapism (46%), and entertainment (37.7%) dimensions of the tourist experience.

Artificial neural network architecture.

Root mean square error (RMSE) for artificial neural network model.

SSE, sum square of errors; N, sample size; ANN, Artificial neural network model.

Sensitivity analysis.

EDU, education; EST, esthetics; ENT, entertainment; ESC, escapism; ANN, Artificial neural network model.

Discussion and Conclusion

The findings of this study show that tourist inspired-by state significantly and positively influenced tourist inspired-to state which is in line with the previous studies demonstrating a significant and positive correlation between the inspired by state and the inspired-to state of customer inspiration ( Böttger et al., 2017 ; Hinsch et al., 2020 ; Izogo et al., 2020 ). For example, Böttger et al. (2017) found that inspirational content affects the inspired-to state through the inspired-by state in the high idea shopping condition. Hinsch et al. (2020) and Izogo et al. (2020) also confirmed the significant and positive relationship between tourist inspired-by state and tourist inspired-to state in the context of research on cross-culture and augmented reality topics that support the findings of this study. Mediation analysis (see Appendix 2) shows the significant mediating role of inspired-by state between the relationships of education, entertainment, esthetics, and escapism dimensions of the tourist experience and inspired-to state of tourist inspiration. Since the direct impact of inspired-by state on inspired-to state is significantly positive, the significant mediating role of tourist inspired-by state between the dimensions of the tourist experience and inspired-to state of tourist inspiration reflects partial mediation and solidifies the existance of a causal relationship between inspired-by and inspired-to states of tourist inspiration. As stated in the theory of self-determination, the transition of tourist inspiration from the inspired-by state to the inspired-to state is driven by the self-transcendence and attraction of a new consumption idea ( Ryan and Deci, 2000 ), and the intrinsic motivation for autonomy and competence may be an internal driving force to implement new ideas regarding consumption ( Böttger et al., 2017 ). Tourist inspiration is an extension of general inspiration in the field of tourism, and, thus, our findings showing the relationship between the inspired-by and inspired-to states are consistent with the extant literature on inspiration ( Böttger et al., 2017 ).

The findings of this study show that the education experience positively and significantly influenced the inspired-by state of tourist inspiration. A strong beta (β) value for the relationship between education experience and inspired-by state of tourist inspiration reflects a strong impact of education experience on the inspired-by state as compared to the impacts of entertainment, esthetic, and escapism dimensions of the tourist experience. These findings are consistent with the work of He et al. (2021) where the scholars validated the relationship between education experience and tourist inspiration in the context of wellness tourism. The education experience improves tourist knowledge and skills through active learning during tourist visit to tourist destination ( Oh et al., 2007 ). The acquisition of new knowledge and skills can enhance tourist cognition, broaden tourist horizons, and stimulate tourist imagination ( Rudd et al., 2018 ) to help tourists discover new possibilities and ideas regarding consumption ( Winterich et al., 2019 ). It is estimated that approximately 50% of the total inventions are inspired by new scientific knowledge ( Callaert et al., 2014 ), and creativity is closely related to the application of new knowledge ( Gurteen, 1998 ). Our findings support the works of Gurteen (1998) and Callaert et al. (2014) .

The findings of this study also show that the entertainment experience significantly and positively influenced the inspired-by state of tourist inspiration. Compared with the other three dimensions of tourist experience, entertainment experience has a weak relationship with the inspired-by state of tourist experience due to the smallest path coefficient. The impact of the entertainment experience on tourist inspiration is investigated in this study which remained under-explored in the previous studies. Destination performances and activities inspire tourists by provoking tourists’ positive emotions and feelings of happiness, which are the prominent features of the entertainment experience ( Oh et al., 2007 ). From the perspective of the broaden-and-build theory, positive emotions and feelings of happiness motivate tourist imagination, enhance tourist creativity, and promote tourist divergent thinking to help tourists discover new ideas regarding consumption ( Fredrickson, 2001 ).

This study demonstrates that esthetics experience significantly and positively influenced the inspired-by state of tourist inspiration. Compared with education experience and escape experience, the path coefficient of the influence of esthetics experience on the inspired-by state is weak. These findings are consistent with the work of He et al. (2021) . The esthetics experience reflects an individual’s cognitive response to the environment or events, which might be unique and different from others ( Pine and Gilmore, 1998 ). Tourists’ appreciation of the environmental beauty and other objective matters of tourist destination reflects tourists’ inspiration and imagination ( Böttger et al., 2017 ). The findings of this study provide robust support to the previous studies that demonstrated a strong relationship between imagination, i.e., the inspired-by state in this study, and esthetic experience ( Brady, 1998 ; Joy and Sherry, 2003 ).

This study revealed that the escapism experience significantly and positively influenced the inspired-by state of tourist inspiration, which is also consistent with the work of He et al. (2021) . However, compared with the other three dimensions of tourist experience, He et al. (2021) reported a strong path coefficient for the relationship between escapism experience and tourist inspiration, which differs from the findings of this study. The escapism experience refers to tourists’ escaping experiences from daily life and traveling to destinations to participate in specific activities ( Oh et al., 2007 ). The previous literature has confirmed that escape experiences can be very memorable, pleasurable, and inspiring for tourists ( Tom Dieck et al., 2018 ; Hwang and Lee, 2019 ). Different environments and lifestyles allow tourists to discover new possibilities and develop new ideas related to consumption with self-transcendence.

The findings of this study revealed a negative, however, weak, moderating impact of destination familiarity on the relationship between education experience and the inspired-by state of tourist inspiration. Nevertheless, the impact of entertainment, esthetics, and escapism dimensions of tourist experience on the inspired-by state of tourist inspiration was not negatively moderated by destination familiarity and the moderating impact remained comparatively weak due to co-efficient values near zero. Destination familiarity is described as tourist cognition and tourist knowledge and experience regarding tourist destination ( Tan and Wu, 2016 ; Liu et al., 2018 ). As tourists become more familiar with destinations, fewer new possibilities are discovered, which reduces the probability of obtaining new ideas and exerts a little impact on tourist inspiration. Extant literature presents that familiarity negatively impacts imagination expansion ( Sharman et al., 2005 ), which is consistent with the findings of this study. Entertainment, esthetics, and escapism dimensions of tourist experience are more related to tourist emotions and feelings and are less affected by cognition-based destination familiarity. Thus, destination familiarity exerts no moderating impact on the relationships among entertainment, esthetics, and escapism dimensions of tourist experience and tourist inspiration.

Theoretical Contribution

This study makes several important theoretical contributions to the extant literature. First, from the general perspective of tourism, this study puts forth empirical evidence to demonstrate the impact of tourist experience, i.e., education, esthetics, entertainment, and escapism, on tourist inspiration, i.e., the inspired-by state, that provides a broader lens to DMOs to understand tourist cognitive responses for destination promotion, which previously remained context-specific and limited, such as wellness tourism ( He et al., 2021 ) and international travel ( Khoi et al., 2019 ). This study expands the critical understanding of the relationship between tourist experience and tourist inspiration by clarifying the influence of entertainment experience on tourist inspiration which remained inconsistent and mixed in the previous studies on conventional tourism and wellness tourism ( He et al., 2021 ). Tourist inspiration reveals the psychological mechanism of tourist experience that promotes tourist purchase behavior. Tourist shopping or consumption behavior at a host destination is likely to be driven by tourist inspirations. Second, based on the transmission model of inspiration, which was proposed by Thrash et al. (2010) and Böttger et al. (2017) found that inspired-by state mediates the influence of marketing stimulus on inspired-to state. In the field of marketing, previous studies verified the significant impact of inspired-by state on the inspired-to state ( Hinsch et al., 2020 ; Izogo et al., 2020 ). In the field of tourism, some empirical studies explored the antecedents and consequences of tourist inspiration ( He et al., 2021 ; Khoi et al., 2021 ). However, the relationship between the inspired-by state and the inspired-to state, as the two components of tourist inspiration, remained deeply under-explored. This study explored tourist consumption inspiration and found that the inspired-by state of tourist inspiration can significantly and positively affect the inspired-to state in the context of tourism, thus, consolidating the theory of customer inspiration and extending the applicable boundaries of the general inspiration theory in the field of tourism. Third, He et al. (2021) found that education experience significantly affects tourist inspiration in the context of wellness tourism, and this relationship is positively moderated by openness to experience. Our findings show that the education experience can significantly and positively impact the inspired-by state of tourist inspiration and destination familiarity negatively moderates the relationship between education experience and the inspired-by state, which extends knowledge and understanding regarding the impact of tourist education experience on tourist inspiration for additional theoretical insights.

Managerial Implications

Destination marketing organizations can design and arrange destination performances and events to enhance tourist experience, which may motivate tourist inspiration and increase destination sales revenue. Although the discussed four dimensions of tourist experiences significantly and positively affect tourist inspiration, DMOs need to combine their advantages to strategically position tourist experience of destinations. Based on such a positioning strategy, DMOs can plan related marketing activities to highlight specific tourist experiences in tourist destination to strengthen destination brand image. For example, the southern Sichuan Bamboo Sea is in Yibin City, Sichuan Province, China, and is a 4A-level natural scenic spot in China. To highlight the educational experience and aesthetic experience, the scenic spot has built the largest bamboo professional museum in China by combining the advantages of rich bamboo resources to show tourists the long history of Chinese bamboo culture and various bamboo crafts. Visiting the museum may inspire tourists to purchase bamboo craft products to increase scenic spot sales revenue. To highlight the escape and entertainment experiences, the scenic spot plans bamboo raft water experience activities. This inspires tourists to consume bamboo raft experience projects and, ultimately, to increase scenic spot sales revenue. Thus, tourist inspiration uncovered under the empirical lens of this study provides new strategic directions for DMOs.

For destinations characterized by education experience, DMOs need to consider the differences in tourist destination familiarity between revisiting and first-time tourists and adopt different marketing strategies for different types of tourists. For revisiting tourists, DMOs can use two marketing strategies to stop declining purchase motivation caused by the negative moderating effect of destination familiarity to maintain destination sales revenue. The first strategy is that using sales promotions and designing creative marketing campaigns may improve tourist purchase motivation and tourist inspiration, respectively. The second strategy is to increase tourist novelty experience during tourist visits to destinations to trigger tourist inspiration, which weakens the negative moderating effect of destination familiarity, with the help of continuous innovation in destination performances and events.

COVID-19 pandemic may negatively impact tourist willingness to visit familiar and unfamiliar tourist destinations, resulting in a huge impact on the global tourism industry due to the sharp drop in the number of tourists ( Rasoolimanesh et al., 2021 ). The COVID-19 pandemic will likely impact tourist consumption patterns worldwide, such as the growing popularity of free and independent travel, luxury trips, and health and wellness tourism ( Majeed and Ramkisson, 2020 ). The ongoing COVID-19 pandemic may have influenced people to reconsider their travel decisions for familiar and unfamiliar tourist destinations to avoid the risk of catching the COVID-19 virus during travel. From the perspective of wellness tourism experience, He et al. (2021) examined the influence of tourist experience on tourist inspiration during the COVID-19 pandemic, and the conclusions drawn by He et al. (2021) are consistent with the findings of this study, providing support to the applicability of the findings of this study during the ongoing context of the COVID-19 pandemic. Since our study was conducted before the COVID-19 pandemic, a comparison between the findings of our study and of He et al. (2021) open doors for DMOs for interesting takeouts of this study during and post the COVID-19 pandemic. However, tourist destinations need to reconsider their service designs and distribution channels to match tourists’ changing cognitive reactions and behavioral intention during and post the COVID-19 pandemic. Destinations can strengthen prevention and control measures at tourist attractions, such as controlling the density of tourists, increasing the requirement of negative nucleic acid tests, and frequent disinfection of the tourist attractions in densely populated areas, to reduce the perceived risk of catching the COVID-19 virus during tourist visit to tourist attractions. Improved prevention and control measures to combat the risk of catching the COVID-19 virus will increase tourist sense of security during visits to destination alongside enhancing tourist experience to trigger positive tourist inspiration.

Limitations and Future Research Directions

This study explores the relationship between the dimensions of tourist experience and tourist inspiration. However, there are some limitations of this study that open doors for future research on the topic under investigation. There are many antecedents to tourist inspiration ( Khoi et al., 2019 ; Winterich et al., 2019 ). However, the current study only explored four dimensions of tourist experience as antecedents to tourist inspiration. Future research can explore other factors that may influence tourist inspiration based on the traits of tourists and the characteristics of destinations for a profound understanding of tourist inspiration. Our study examined the moderating impact of destination familiarity on the relationship between tourist experience and tourist inspiration and found that destination familiarity has no moderating impact on the relationship between the proposed facets of tourist experience and tourist inspiration except for the relationship between education experience and inspired-by state of tourist inspiration. Future research can extend the scope of our work to investigate the impact of other moderators, such as national culture, on the relationship between tourist experience and tourist inspiration for additional insights.

Since this study explored the inspired-to state of tourist inspiration with a focus on purchase motivation, the proposed theoretical framework of the study can be extended to reflect how tourist inspiration affects tourist revisit intention, tourist wellbeing, and tourist intention to recommend a destination ( Filep and Laing, 2019 ). Future research may also focus on other perspectives to examine tourist inspiration at different stages of travel. For example, how can tourist inspiration influence tourist intention to visit/revisit specific tourist destinations during the pre-travel planning phase? Since a growing number of tourists collect destination information online when making travel plans ( Majeed and Ramkissoon, 2022 ), it will be worth exploring how DMOs can inspire tourists through online information and fuel tourist travel intention for a specific tourist destination.

Data Availability Statement

Ethics statement.

This study was carried out in accordance with the recommendations of the Local Ethics Committee of Shenzhen. All the study participants provided written informed consent in accordance with the Declaration of Helsinki. The study protocol was approved by the Local Ethics Committee of Shenzhen University.

Author Contributions

JX: conceptualization, conduct of the survey, data gathering, data analysis, revisions, development, and proofreading of the manuscript. ZZ: conceptualization and survey design. SM: revisions, development, and proofreading of the manuscript. RC: data analysis. NZ: survey design. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

Thanks to Yufan Jian for her constructive comments to improve the quality of this study.

1 https://www.wjx.cn

This work was supported by the National Natural Science Foundation of China (Grant Nos. 72172093 and 71832015) and the Science and Technology Research Project of Henan Province, China (Grant No. 222102320001).

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2022.895136/full#supplementary-material

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Take advantage of the search to browse through the World Heritage Centre information.

Understanding tourism at your destination

• Toolkit About the Sustainable Tourism Toolkit How to use this guide? Our Objective Resource Library
• Guides Strategic foundations Guide 1: Understanding Guide 2: Strategy Guide 3: Governance Guide 4: Engagement Core Delivery Guide 5: Communication Guide 6: Infrastructure Guide 7: Value Guide 8: Behaviour Guide 9: Investment Guide 10: Monitoring
• Case Studies Guide 1: Historic Town of Vigan Guide 2: Angkor Guide 2: Ichkeul National Park Guide 3: Melaka and George Town Guide 4: Avebury Guide 4: Old and New Towns of Edinburgh Guide 4: Great Barrier Reef Guide 4: Røros mining town and the circumference Guide 5: Røros Mining Town and the Circumference Guide 6: Cornwall and West Devon Mining Landscape (United Kingdom) Guide 7: Røros Mining Town and the Circumference Guide 8: Wadi Al-Hitan Guide 9: Land of Frankincense

What this guide 1 will tell you

This guide 1 will help you understand why tourism matters, some key questions you may need to ask and answer, and some ways to fill evidence gaps, such as utilising other partner's resources. Continue reading below to follow our steps to success.

Steps to success

Why this matters.

Every business school in the world teaches, 'If you can't measure it, you can't manage it'. You cannot manage tourism or help shape it in progressive ways without having a basic understanding of what it is, how it affects people and places, and what it can potentially become with some inspired and progressive interventions. To ensure the scarce resources available for tourism development and heritage protection are utilized to their full effect, it is crucial a unified understanding exists across each destination regarding what is successful, what does not work, and what sustainable opportunities exist for growth or development. Not all tourism is good tourism; some forms of tourism are much more sustainable, while others may have a negative effect on the surrounding environment if not managed properly.

Almost all potential sites can benefit from better evidence and data – this is not just a heritage management issue, but a tourism destination issue. It is necessary you work to gather this information . Other places similar to your sites have successfully addressed these questions, and often with limited resources. You may find the examples most relevant to your situation in our Resources page .

Start with the basics define your terms of reference

Be clear on where and what your 'destination' is . A destination is the physical space in which a tourist spends their holiday or vacation. It includes a full range of services, products and experiences :

• The attractions people visit
• The accommodation in which they stay
• The transport arrival hubs
• The food and drink establishments utilised
• The retail outlets in which they shop
• The museums and galleries they visit
• Even the city, town, village, or homes where the local community resides.

A World Heritage site (WHS) can be a destination in itself. However, more often it is located in, or part of, a wider venue, forming the key , or one of the key, attractions of the place concerned. The UNESCO World Heritage and Sustainable Tourism Programme is based on the need to manage tourism at a destination scale – managing the issues simply within the boundaries of the World Heritage sites would be ineffective.

Defining your broader destination is extremely important in building foundations for sustainable tourism, and it can be particularly helpful to look at how other places have done this already. For example , Angkor Wat WHS is the attraction, but Siem Reap is the destination, or Uluru Kata Tjuta WHS (formerly known as Ayers Rock) is the attraction, while Alice Springs is the destination.

We offer guidance below that addresses tourism challenges at a destination scale. Therefore, it will be important to know and understand the geography of your location  - where it begins and also where it ends.

How much do you know about the destination?

Here are some basic questions you will need to answer about your destination. It may be useful to list your answers in a separate document to refer back to later.

Can you answer all of the following?

• How many tourists do you receive per year?
• How long do they stay in your destination?
• Who are your tourists? Where do they come from?
• Are you attracting the most advantageous segments of the tourism market? How do you perform relative to other comparable destinations?
• How do tourists arrive and move around your destination? Where do they go to afterwards?
• What are their motivations for coming? What do they know about your site?
• What do they care about? Do they understand your outstanding universal value (OUV)?
• What are the positive and negative social, economic, cultural, and ecological impacts caused by visitors? How do they affect the heritage management of the site?
• Where, and by whom or what, are these impacts experienced?
• How many people can your site/destination sustainably cope with and manage?
• Do you understand the scale, quality, capacity, and location of your tourism infrastructure (hotels, restaurants, travel providers, food and drink, leisure, retail)?
• How do your visitors spend their money? Who benefits from this spending? Who does not benefit?
• Who picks up the costs of the heritage?
• Who or what entity must be part of a partnership that would bring about positive changes to your destination?

If you cannot answer these questions , or similar questions specific to your site, you must dedicate some time to trying to find these answers before attempting to change anything. These answers will help you gather the necessary information to begin managing tourism in your location at a destination scale.

The four crucial issues you need to measure and understand, and why

Understanding tourism is the first step to managing your site more effectively. Surprisingly, few World Heritage sites collect accurate data on key tourism indicators. Good data is the key to both being able to monitor threats to the site or the host community, and ensuring interventions are effectively targeted. The following four topics are crucial to fully understanding tourism possibilities at your destination.

1) Supply side

To manage tourism effectively, destinations need to understand the supply side of the process – which involves undertaking an inventory of tourism assets and infrastructure, while assessing the scope for growth and the changes over time. The effectiveness of a destination relies on securing revenue and is heavily dependent upon the location, scale, capacity, and quality of the accommodation, transport system, food and drink, retail, leisure experiences, and visitor attractions. Every destination should have a simple and up to date inventory of its tourism assets and visitor attractions.

2) Demand side

Sites must also understand the demand side of the tourism sector :

• How many people want to visit? Is the demand growing or declining?
• Who are the visitors, and when do they visit?
• Why do they come, and how long do they stay?
• How much do they spend and what do they purchase?
• Where do they come from?
• What do they want to experience, and how do they learn about the site, its values, and the host community?
• Are visitors satisfied with the experience?
• How is all of this changing over time, and does the destination attract the most advantageous visitor segments?

This information is crucial because you may need to use it later for new investment possibilities and new or updated infrastructure . All destinations should at the very least measure visitor satisfaction levels.

3) Community voice – community impacts

It is critical that destinations think carefully about the potential positive and negative impacts that tourism may have on the host community and their intangible cultural heritage. Communicate with the host community to understand their needs, concerns, and aspirations. It is a basic tenet of sustainable tourism that host communities have a voice in shaping the tourism processes that affect them. There is tendency to think about the community's wishes after everything has already been decided – this is a grave mistake and one likely to breed mistrust and apathy on the part of local residents.

4) Heritage, cultural, social, and ecological impacts

Perhaps the most important issue when talking about World Heritage sites is understanding the heritage – what can and cannot happen in its proximity. We would hope that every site has a Heritage Management Plan that is clear about the impacts and opportunities that result from tourism, as well as the areas of concern and issues to be addressed. It is critical for effective heritage management that destination personnel understand and monitor the past, present, and potential future ecological, cultural, and social impacts of tourism. In many sites there will be ways to sustainably manage tourism and tourism growth, but site managers need to understand the point at which impacts are destructive and require intervention. The degree to which tourism businesses provide local career opportunities (with fair wages), equal opportunities, and occupational safety are important and worthy of analysis. Think carefully about 'liveability' as well as the visitor experience. It is also important to monitor risks and negative impacts over time so that areas of concern can be managed in the appropriate way at the appropriate times.

These four areas of action are critical to effective destination management . Every World Heritage site destination should evaluate their knowledge and understanding on these issues. This is not simply some form of onerous conservation regulation. It is as much about developing and managing the destination for the benefit of its businesses and host community, as it is about raising awareness concerning what can and cannot happen at sites recognised as the world's most important and valued historic places or natural landscapes.

Bring together the key data and evidence on your destination in one place

Create a simple inventory of the available evidence on tourism issues in the destination. This will save a lot of time for stakeholders and is a useful exercise for a conservation or management body, as well as for a commercial business.

Knowledge and understanding is powerful so spread it across the destination. Most tourism macro data is not market sensitive. It can usually be shared and analysed publically with no ill effects for the destination (though it may reveal certain weaknesses or difficulties if the destination is doing things less well than it should be). Surprisingly few World Heritage destinations can answer any or all of these questions with any supporting evidence. We would, therefore, recommend that you bring together any available evidence on the destination and make it accessible, as it will empower businesses and others to think strategically about the performance of the tourism sector.

Assess objectively whether enough is known about tourism in your destination

What are the gaps in your knowledge and evidence?

It will become apparent relatively quickly which key questions you cannot answer with the evidence currently available. Make a simple list of the topics you know and understand. Continue with a list of those you do not know, but think would be useful to know. This list is rather important for the stages that follow because you will be able to engage other partners in helping you fill the information gaps you find.

Who can fill the data/evidence gaps?

Identify, link, and connect different stakeholders who have an interest in better tourism. There are many ways to collect data without spending a large sum of money. Many World Heritage sites will be able to establish relationships with local or international universities, colleges, and schools, as well as private businesses willing to devote time, effort, and money to understanding tourism and its associated issues with supporting evidence. If all else fails, engaging interns and volunteers to use simple but robust survey techniques can shed light on the tourism market for the destination as a whole.

The point is that often there are other organisations willing to use the destination as a research location, creating a mutually beneficial relationship for all parties involved. Some destinations already have established Evidence and Impact Forums for interested specialist parties and academics; if asked, a surprisingly wide range of stakeholders could be interested in helping you undertake this research.

Some ways to get started

Do not be daunted by the number of things you do not know… begin your evidence gathering and analysis . You may even start to answer some of the key questions by simply buying a clipboard, standing on the street, and asking visitors some polite questions. If you can ask a couple hundred visitors the right questions , then you will begin formulating insights into tourism at your destination. Likewise, if you contact around 20 tourism businesses via face-to-face interviews or through an online survey , you will begin to create a picture of what is happening at your destination, what is working, and what is not. Simple observations can reveal a great deal – get a map and mark observations concerning crowding, litter, deterioration of the historic environment, or poor visitor experiences. Your efforts may not meet the highest standards of social science, but this is not important.

Some destinations will, of course, be well resourced to hire professional teams of experts to undertake robust analysis of these issues – and that is to be encouraged where possible – but most destinations have to do their best with a range of practical, DIY, and partner solutions. We are not demanding perfect analysis. Rather, we are arguing that some form is essential . If you are lacking an available human workforce, you may encourage visitors to fill out a short survey when booking with hotels or agencies, or leave one in their hotel rooms. If incentivised , perhaps with the possibility of winning tickets to a local show or a free dinner, it has been shown that people are far more likely to complete such surveys. The luckiest, or best-managed locations may already have a destination management organisation happy to lead a data gathering project on tourism, and their work may simply need to be influenced by heritage professionals to widen its scope.

As you gather new evidence make it public . However small your samples or tentative your conclusions, you should make these public so others can respond , help you widen the survey base, or simply disagree with your findings and replace the information with something better. Knowledge is never perfect or finished; it is the process of learning and finding the information that matters.

Assess sustainability meaningfully- can tourism ever be sustainable at your site?

Now that you are collecting and analyzing data, consider whether there are ways other than tourism to share your site and give your community a good quality of life. The global environment faces profound challenges due to our addiction to travel and the consumption of resources at unsustainable levels . Planes, trains, cars, and other forms of transport are a significant contributor to climate change through the burning of fossil fuels, and many communities face significant challenges in terms of water usage and the disposal of waste water and other solid wastes. The world is experiencing unprecedented levels of species extinction through habitat loss for food production, pollution, and over fishing, so now more than ever you need to assess whether you can justify tourism. If you are, in fact, able to do so, assess what kind of tourism can be accommodated that does not contribute negatively to the situation, either directly on a local basis or through externalities (e.g. CO2 emissions) on a global basis.

We need a new kind of tourism that does not contribute to environmental damage, climate change, pollution, and loss of ecosystems. Some sites are already making the tough decision not to open complete access to visitors. Instead they have chosen to share their stories and values through a greater online presence, or offering remote access to the site with accompanying narrative guides– for instance, St Kilda in Scotland is one example. When gathering data to understand tourism in your destination do not duck the toughest question of all – face it and think about it. If the need for tourism is so great and is effectively unavoidable for your community, then think about how you can manage or prevent its direct effects on a local basis. In parallel, find ways to offset or mitigate its externalities on a global basis, such as a scheme for carbon offsetting.

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Wānaka man’s tourism knowledge helps improve local environment and educate visitors

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Tim Barke has put his tourism knowledge to good use, helping tell the stories of Wānaka locals to visitors and working on improving the environment.

Losing his tourism job to the Covid-19 pandemic inspired Wānaka man Tim Barke to use his knowledge of the industry to help improve the environment, tell locals’ stories and educate visitors on what makes the town tick, Alison Smith writes.

When Tim Barke bought his Wānaka property just before the Covid-19 pandemic hit in 2020, he planned to enjoy the rural lifestyle and commute to Queenstown for his corporate job.

Heading up Totally Tourism, the umbrella company for 12 aviation, adventure tourism and cruise boat enterprises, the pandemic meant Barke soon found himself out of that job and working shoulder to shoulder with the Jobs For Nature workforce.

“We clambered around the mountains and cut pine trees down,” he said.

“It was amazing - brutally cold - our coldest days were minus 8 degrees.”

Barke said he got to work with his son, who as a mountain bike track builder, was also out of a job.

“It was an experience I would never have got to have, spending four months around the mountain with my son.

“Everybody on the team was from different backgrounds – ex-CEOs, people who washed dishes – all earning the same. It was an amazing experience.”

The experience led Barke to the environmental protection organisation, Wai Wānaka, which aims to improve waterway health in the catchment rurally.

Wai Wānaka achieves this by engaging with 84 per cent of the Upper Clutha’s larger farms and involving more than 60 properties larger than 20ha, such as Barke’s.

Once borders were reopened a role came up with Lake Wānaka Tourism.

Barke saw this as a once-in-a-lifetime opportunity to transform the local industry, collaborating with Wai Wānaka to put his tourism knowledge into environmental action.

“One of the reasons we bought our property is that we’re really interested in soil regeneration and regenerative farming practices, and trying stuff out to see what makes a difference,” he said.

“We’re small enough to be able to try stuff without it costing too much, but big enough to try it in different sections.”

The Wai Wānaka team helped with soil analysis and guidance on tools, such as visual soil assessments, and rabbit and wilding pine control.

Wai Wānaka also connected Barke to his neighbours in the sub-catchment of Poplar Beach.

The organisation has helped establish six of the seven catchment groups and four small landholder groups operating in the Central Lakes District.

These groups determine their priorities for each catchment, receiving a pool of funding to help with group facilitation. They also gain access to experts, tools and resources.

The science behind how the groups operate is based on a three-year research project involving more than 75 farm businesses around New Zealand, funded by Our Land and Water.

Wai Wānaka’s actions are based on the Community Catchment Plan.

Barke believed Wai Wānaka made it easier for locals to meet and work with their neighbours and provided invaluable outcomes with a science-based plan.

“As communities, we’re a lot more mobile than we used to be, so people move house, towns and regions more than in the old days, so those networks are harder to build up and keep,” he said.

“For me personally, this has been a really beneficial opportunity to get to know my neighbours. We were new to Wānaka, and it shortcuts the process.

“By having those experts, it gives you a lot more confidence than just catching up with neighbours and spitballing ideas.

“You can fast-track things easier when you have scientific data behind the decisions you are making.”

He said getting people together, and understanding what worked and what didn’t, had been an interesting process.

“Overall, we’re all trying to achieve the same thing - to be custodians of the land and help the health of the land and the ecosystems within the land.

“Some of those in our catchment group’s sole income is produced from the land but they can only do that if the land is healthy.”

Barke said there were “huge benefits” to the groups if they could achieve cost-effective processes that helped regenerate the soil and ecosystems.

Barke’s lifetime career is in tourism, beginning in the late 1980s.

Right from the start he could see the opportunities that tourism presented - but also the potential impacts on the natural resources that it relied on - something that travellers were also starting to realise.

Barke said it was partly about the destination planning and how a region operated.

“Our job used to be to sell as much tourism product overseas as we could - it was literally bums on seats.

“Through the brand repositioning and destination management process that we spent two years doing, we found out that the community was rapidly feeling pressured by tourism and feeling like they were being pushed out, with tourism taking precedence over locals.”

Barke and his team rebuilt www.wanaka.co.nz to tell stories about who Wānaka’s locals are, what they do as part of their ideal lifestyle and how the locals look after their place.

“Then we offer an invitation to the people that resonates with.”

He said that by doing this, visitors had a better idea of how to fit into the community.

“We’re trying to create opportunities for visitors to get involved with and get a better understanding of how we look after the place and their role in that.

“It’s attracting the people who are going to be the best fit.

“It’s [also] encouraging tourism products that have a regenerative focus, like having people going four-wheel driving on high country stations to check pests, and learning why that’s being done, or approaching the selling as a storytelling process rather than marketing.”

The outcome is twofold.

“The people wanting to come here have a much better understanding of where they’re coming to and who they’re coming to.

“Therefore, they’ve got a better understanding of what they can expect but also what’s expected of them when they come.”

Collaborating with Wai Wānaka’s team, the tourism offering is a genuine outcome for the good of the catchment.

Back on his land, Barke was keen to progress, alongside his neighbours, the reforestation of a barren hill face that had only weeds and rabbits on it.

“If we can get a native ecosystem going, we can connect Wānaka with Luggate through a natural corridor and potentially give people access to explore it.

“That in itself would have an impact on the weather – having a decent-sized forest can affect how much precipitation it gets.”

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• What is tourism and hospitality?

Tourism and hospitality are thriving industries encompassing many sectors, including hotels, restaurants, travel, events, and entertainment.

It’s an exciting and dynamic area, constantly evolving and adapting to changing customer demands and trends.

The tourism and hospitality industry offers a diverse range of career opportunities that cater to various interests, skills, and qualifications, with positions available from entry-level to executive management.

The booming tourism  and hospitality industry also offers job security and career growth potential in many hospitality-related occupations.

What is tourism?

Tourism is traveling for leisure, pleasure, or business purposes and visiting various destinations, such as cities, countries, natural attractions, historical sites, and cultural events, to experience new cultures, activities, and environments.

Tourism can take many forms, including domestic, or traveling within your country, and international tourism, or visiting foreign countries.

It can also involve sightseeing, adventure tourism , eco-tourism, cultural tourism, and business tourism, and it’s a huge contributor to the global economy, generating jobs and income in many countries.

It involves many businesses, including airlines, hotels, restaurants, travel agencies, tour operators, and transportation companies.

What is hospitality?

Hospitality includes a range of businesses, such as hotels, restaurants, bars, resorts, cruise ships, theme parks, and other service-oriented businesses that provide accommodations, food, and beverages.

Hospitality is all about creating a welcoming and comfortable environment for guests and meeting their needs.

Quality hospitality means providing excellent customer service, anticipating guests’ needs, and ensuring comfort and satisfaction. The hospitality industry is essential to tourism as both industries often work closely together.

What is the difference between tourism and hospitality?

Hospitality and tourism are both related and separate industries. For instance, airline travel is considered as part of both the tourism and hospitality industries.

Hospitality is a component of the tourism industry, as it provides services and amenities to tourists. However, tourism is a broader industry encompassing various sectors, including transportation, accommodation, and attractions.

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Is tourism and hospitality a good career choice?

So, why work in hospitality and tourism? The tourism and hospitality industry is one of the fastest-growing industries in the world, providing a colossal number of job opportunities.

Between 2021 and 2031, employment in the hospitality and tourism industry is projected to expand faster than any other job sector, creating about 1.3 million new positions .

A tourism and hospitality career  can be a highly rewarding choice for anyone who enjoys working with people, has a strong service-oriented mindset, and is looking for a dynamic and exciting career with growth potential.

Growth and job opportunities in tourism and hospitality

Tourism and hospitality offers significant growth and job opportunities worldwide. The industry’s increasing demand for personnel contributes to economic and employment growth, particularly in developing countries.

The industry employs millions globally, from entry-level to high-level management positions, including hotel managers, chefs, tour operators, travel agents, and executives.

It provides diverse opportunities with great career progression and skill development potential.

Career paths in tourism and hospitality

There are many career opportunities in tourism management and hospitality. With a degree in hospitality management, as well as relevant experience, you can pursue satisfying and fulfilling hospitality and tourism careers in these fields.

Hotel manager

Hotel managers oversee hotel operations. They manage staff, supervise customer service, and ensure the facility runs smoothly.

Tour manager

Tour managers organize and lead group tours. They work for tour companies, travel agencies, or independently. Tour managers coordinate a group’s transportation, accommodations, and activities, ensuring the trip runs to schedule.

Restaurant manager

Restaurant managers supervise the daily operations of a restaurant. They manage staff, ensure the kitchen runs smoothly, and monitor customer service.

Resort manager

Resort managers supervise and manage the operations of a resort. From managing staff to overseeing customer service, they ensure the entire operation delivers excellence.

Entertainment manager

Entertainment managers organize and oversee entertainment at venues like hotels or resorts. They book performers, oversee sound and lighting, and ensure guests have a great experience.

Event planner

Event planners organize and coordinate events, such as weddings, conferences, and trade shows. They work for event planning companies, hotels, or independently.

vent planners coordinate all aspects of the event, from the venue to catering and decor.

Travel consultant

Travel consultants help customers plan and book travel arrangements, such as flights, hotels, and rental cars. They work for travel agencies or independently. Travel consultants must know travel destinations and provide superb customer service.

What skills and qualifications are needed for a career in tourism and hospitality?

Tourism and hospitality are rewarding industries with growing job opportunities. Necessary qualifications include excellent skills in communication, customer service, leadership, problem-solving, and organization along with relevant education and training.

Essential skills for success in tourism and hospitality

A career in the tourism and hospitality industry requires a combination of soft and technical skills and relevant qualifications. Here are some of the essential key skills needed for a successful career.

• Communication skills : Effective communication is necessary for the tourism and hospitality industry in dealing with all kinds of people.
• Customer service : Providing excellent customer service is critical to the success of any tourism or hospitality business . This requires patience, empathy, and the ability to meet customers’ needs.
• Flexibility and adaptability : The industry is constantly changing, and employees must be able to adapt to new situations, be flexible with their work schedules, and handle unexpected events.
• Time management : Time management is crucial to ensure guest satisfaction and smooth operations.
• Cultural awareness : Understanding and respecting cultural differences is essential in the tourism and hospitality industry, as you’ll interact with people from different cultures.
• Teamwork : Working collaboratively with colleagues is essential, as employees must work together to ensure guests have a positive experience.
• Problem-solving : Inevitably, problems will arise, and employees must be able to identify, analyze, and resolve them efficiently.
• Technical skills : With the increasing use of technology, employees must possess the necessary technical skills to operate systems, such as booking software, point-of-sale systems, and social media platforms.

Revenue management : Revenue management skills are crucial in effectively managing pricing, inventory, and data analysis to maximize revenue and profitability

Master fundamental hospitality and tourism secrets for a high-flying career at a world-leading hospitality brand

With this Master’s degree, you’ll discover the skills to manage a world-class hospitality and tourism business.

Education and training opportunities in tourism and hospitality

Education and training are vital for a hospitality and tourism career. You can ensure you are prepared for a career in the industry with a Bachelor’s in hospitality management   and Master’s in hospitality   programs from Glion.

These programs provide a comprehensive understanding of the guest experience, including service delivery and business operations, while developing essential skills such as leadership, communication, and problem-solving. You’ll gain the knowledge and qualifications you need for a successful, dynamic, and rewarding hospitality and tourism career.

Preparing for a career in tourism and hospitality

To prepare for a career in tourism and hospitality management, you should focus on researching the industry and gaining relevant education and training, such as a hospitality degree . For instance, Glion’s programs emphasize guest experience and hospitality management, providing students with an outstanding education that launches them into leading industry roles.

It would help if you also worked on building your communication, customer service, and problem-solving skills while gaining practical experience through internships or part-time jobs in the industry. Meanwhile, attending industry events, job fairs, and conferences, staying up-to-date on industry trends, and networking to establish professional connections will also be extremely valuable.

Finding jobs in tourism and hospitality

To find jobs in tourism and hospitality, candidates can search online job boards, and company career pages, attend career fairs, network with industry professionals, and utilize the services of recruitment agencies. Hospitality and tourism graduates can also leverage valuable alumni networks and industry connections made during internships or industry projects.

Networking and building connections in the industry

Networking and building connections in the hospitality and tourism industry provide opportunities to learn about job openings, meet potential employers, and gain industry insights. It can also help you expand your knowledge and skills, build your personal brand, and establish yourself as a valuable industry professional.

You can start networking by attending industry events, joining professional organizations, connecting with professionals on social media, and through career services at Glion.

Tips for success in tourism and hospitality

Here are tips for career success in the tourism and hospitality industry.

• Gain relevant education and training : Pursue a hospitality or tourism management degree from Glion to gain fundamental knowledge and practical skills.
• Build your network : Attend industry events, connect with colleagues and professionals on LinkedIn, and join relevant associations to build your network and increase your exposure to potential job opportunities.
• Gain practical experience : Look for internships, part-time jobs, or volunteering opportunities to gain practical experience and develop relevant skills.
• Develop your soft skills : Work on essential interpersonal skills like communication, empathy, and problem-solving.
• Stay up-to-date with industry trends : Follow industry news and trends and proactively learn new skills and technologies relevant to tourism and hospitality.
• Be flexible and adaptable : The tourism and hospitality industry constantly evolves, so be open to change and to adapting to new situations and challenges.
• Strive for excellent guest service : Focus on delivering exceptional guest experiences as guest satisfaction is critical for success.

Tourism and hospitality offer many fantastic opportunities to create memorable guest experiences , work in diverse and multicultural environments, and develop transferable skills.

If you’re ready to embark on your career in tourism and hospitality, Glion has world-leading bachelor’s and master’s programs to set you up for success.

Photo credits Main image: Maskot/Maskot via Getty Images

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What is a tourist? Tourist definition

Disclaimer: Some posts on Tourism Teacher may contain affiliate links. If you appreciate this content, you can show your support by making a purchase through these links or by buying me a coffee . Thank you for your support!

What is a tourist? How you define the term tourist? Is there a widely accepted tourist definition?

When we are and are not tourists is not always clear. Am I a tourist when I travel one hour on the train to London for the afternoon? Am I a tourist when I stay with my Grandma in Scotland for a week? The problem is, that there is no clear answer to these questions.

In this article I will attempt to answer the question ‘what is a tourist’ by providing you with some definitions of the term tourism, alongside some thought-provoking connotations.

What is tourism?

What is a tourist, am i a tourist or a traveller, tourist definition, what is a tourist to conclude.

If we want to understand what a tourist is, first we need to fully comprehend the concept of tourism.

As I explain in my article discussing the definitions of tourism , tourism is a term that has no universally accepted definition. Tourism is the generic term used to cover both demand and supply that has been adopted in a variety of forms and used throughout the world. 

Tourism essentially refers to the activities undertaken by visitors, also known as the visitor economy. The tourism industry encompasses all activity that takes place within the visitor economy. 

This includes activities that are directly related to the tourist, such as staying in a hotel, ordering a meal or visiting a tourist attraction. It also includes indirect activities, such as the transport company which delivers the food to the restaurant in which the tourist eats or the laundry company that has a contract with the hotel for cleaning bed sheets. 

It is largely due to the indirect contributions to tourism, that defining and measuring the tourism industry is so difficult!

Tourism comes in many different shapes and sizes and there are many different types of tourism . There is mass tourism , niche tourism and special interest tourism. There is domestic tourism and international tourism . There is inbound tourism and outbound tourism .

A tourist is a product of tourism. Tourists are the people who take part in tourist activities. Tourists are important stakeholders of tourism .

There are many factors that the average person associates with a tourist. I have listed a few of these below:

• lying on a beach
• drinking cocktails/beer/alcohol
• visiting major tourist attractions
• staying in a hotel
• visiting a place with a different climate
• packing a suitcase
• flying on an aeroplane
• getting a suntan

The United Nations prescribes that tourists need to stay away from their home environment for more than one night but less than one year in order to qualify as a tourist. This is the criteria that is often used and cited within the academic literature. But in reality, this is not a universal criterion at all.

In fact, it is actually somewhat problematic that there is no universal criteria for what constitutes a tourist. Lets look at an example. In 2020 tourism was all but decimated around the world due to the COVID pandemic. During the height of the pandemic in Europe and much of the rest of the world, China began to make claims that their domestic tourism industry was once again booming.

OK great. But the important question here is- what is a tourist? How did/do China, and other countries around the world, measure tourist numbers?

Is the person who lives in Shanghai a tourist when they go to The Bund for the afternoon? Are they a tourist when they take a day trip to Hangzhou? Are they a tourist when they go to stay with their aunty in Sanya ?

This is not by any means a Chinese issue. This is a global issue. How can we compare tourism numbers between two or more countries unless we have hard and fast rules about what is or isn’t a tourist? It makes no sense to me at all…

The issue is that there is no clear rule about who is a tourist and who is not a tourist. Yes, there are academic debates discussing tourist typologies (e.g. Leiper , Cohen, Urry, Uriely, Wickens), but these don’t answer the basic underlying question of who is a tourist.

Whilst he also doesn’t provide any definitive answers to this problem, McCabe’s paper offers a critical review of what is a tourist, underpinned by sociological debates and concepts. I want to keep it simple in this article, but if you want to take a more in-depth look, I recommend his paper. You can read the paper here .

In recent years there seems to be an absurd trend that has grown, where tourists have developed a bad reputation. Tourists are portrayed as second-class citizens. Tourists are lazy. Tourists are dumb.

And this isn’t limited to the general public, it exists within the academic community too. In the tourism literature, tourists are represented in an overwhelmingly negative light, and often in critical or sociological studies in deference to more ‘superior’ forms of travel- such as backpacking.

The tourist is bad and the traveller is good- that’s what you will read if you Google the question ‘am I a traveller or a tourist’.

Most claims to differentiate between the two state that travellers are good- kinder to the environment, think more, travel slowly (i.e. backpackers), engage in cultural tourism . Whereas tourists are associated negative connotations, such as enclave tourism , economic leakage in tourism , lazing around on the beach, being drunk, taking too many photographs.

In reality, this is all a load of absolute rubbish. Are these ‘travellers’ staying away from home for a period of time? Yes. Are they visiting areas for leisure or business? Yes. Are they visiting tourist attractions? Yes.

So the reality is that these self-acclaimed ‘travellers’ are in reality- tourists.

What I suggest has happened here is that people have attempted to differentiate between different types of tourists , by coining the terms ‘traveller and tourist. But little do they know- the work has already been done, several times….

Within the academic community there have been many differentiations made between types of tourists. From Plog’s allocentric and psychocentric tourist typology to Cohen’s mass tourists, explorers and drifters, alongside many other studies examining tourist behaviours and motivations, clear differentiations between types of tourists have been made.

However, these typologies are not mainstream knowledge and outside of academia, most people will never have heard of this research. As such, the tourists themselves have taken it upon themselves to develop their own basic typology. The problem, however, is that they haven’t got it quite right- because in reality both classifications are indeed tourists.

In response to the evident desire to differentiate between tourist types, I would like to propose that we re-name these classifications. Instead of the term traveller, we could use explorer and instead of the term tourist, we use holidaymaker. This way, we can acknowledge that both types of people are tourists, but they are not tourists in the same way.

It is evident that the definition of a tourist is unclear. This makes comparability and accurate measurement of the scale of the tourism industry difficult. Whilst there is an urgent call for a universal definition to be developed and utilised, I doubt this will happen any time soon, at least not on a global scale.

Until there is a universally accepted definition of a tourist, I will propose my own tourist definition as follows:

‘A tourist is a person who travels away from where they live to partake in leisure or business [tourism] activities for a specified period of time. Types of tourists vary and tourists can sit anywhere along the spectrum between allocentric explorers and mass organised holidaymakers.’

We are all tourists at some time or another. Whether we take a trip to the seaside in our own country or whether we travel to the other side of the world to be volunteer tourists , there are many different types of tourism and many different types of tourists.

Do you have anything to add on the tourist definition debate? Please leave your remarks below!

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Engineering students gain real-world knowledge for future success during Italy trip

Lucas Johnson

Apr 15, 2024, 6:35 AM

by Lucas Johnson

More than 20 Vanderbilt engineering students recently visited Italy during their spring break to not only see some iconic structures, but also learn the engineering behind the Pantheon and Venice’s sophisticated floodgates so they could apply that knowledge to future engineering projects of their own.

The trip was part of an inaugural class taught this semester in the Civil and Environmental Engineering Department and sought to give the 22 students a deeper understanding of the engineering behind some of Italy’s structures, such as the ancient Pantheon and MOSE project designed to protect the city of Venice from flooding. The MOSE project is an integrated system consisting of rows of mobile gates that uses air pressure to keep water levels in check.

As part of their class assignments, the students worked in groups to design floodgates as well as build and test concrete dome prototypes based on their studies of how the Pantheon was constructed. The class was originally scheduled for 15 students, but instructors increased the number because of interest.

“We wanted to help students understand the history and the beauty of structural engineering with the hope that they will be able to better work with architects to achieve beautiful and structurally sound buildings in their careers,” said Lori Troxel, professor of the practice of civil and environmental engineering and a class instructor.

While in Italy, the students traveled to Rome, Venice, and Milan. In Milan, they spent time with architects who had worked with the renowned architect Zaha Hadid, and met with a group of students from Polytechnic University of Milan who were taking a class on structural health monitoring. In Venice, they talked to engineers involved with the city’s unique flood gates. And in Rome, the students visited ancient sites like the Pantheon, the Coliseum, and the Roman Forum.

Winnie Huang, a junior majoring in civil engineering, marveled at the construction of the Pantheon.

“Seeing the Pantheon in person made clear why its design has allowed for it to last thousands of years,” said Huang. “Despite the cracking as a result of the hoop stresses of the dome, the Pantheon has notably stayed structurally sound due to its construction with Roman concrete, which contains self-healing properties. Although we didn’t personally have the opportunity to work with Roman concrete for our project, we took inspiration from the Pantheon in designing our own miniature concrete dome.”

For Santino Clemente, whose grandparents are Italian immigrants, the trip was his third time in Italy and one he had looked forward to because after each visit he found himself wanting to go back. Before the latest trip, he watched a documentary about the MOSE project.

“Being there in person and getting to ask all our questions to the engineers was an awesome experience,” said Clemente, a junior majoring in mechanical engineering.

After returning from Italy, the students tested floodgates they had constructed in a creek at a park near the university. In constructing the floodgates, they had a budget of $50 and could use whatever scrap materials they found.

Philmon Gashaw, also a junior mechanical engineering major, said his group used a magnet, wood, and acrylic to design their floodgate. “We put it in the creek and saw how well we could stop the water,” said Gashaw. “It worked surprisingly better than I thought.”

Many of the students applied what they learned about the MOSE project to the construction of their floodgates. For Clemente and his team, he said it was the angle for the wall of their floodgate.

“We learned that the MOSE gates are lifted up to a 42-degree angle to prevent a straight-on impact from the tide, which would result in a much higher force,” he said. “Therefore, even though the top of our gate was fully vertical, we added a ramp at the bottom that guided the water upward. This prevented the water from pushing our floodgate on first impact.”

Ghina Absi, assistant professor of the practice of civil and environmental engineering and a class instructor, said she enjoyed seeing the students’ engagement and excitement as they worked on the projects, and hopes what they learned will benefit them down the road.

“Even when they’re trying to solve a tiny problem of stopping a flow in a tiny channel next to campus, they will be able to take all the lessons they’ve learned and apply them to the big project I know they are capable of doing in the future,” said Absi.

Last year during spring break, Troxel led a group of engineering professors and students to Israel as part of a different program to learn about the country’s water recycling programs and bring those lessons back to share with Sterling Ranch, a 21st century sustainable city south of Denver, Colorado, that has doubled as a training site and test bed for Vanderbilt students and professors since 2015.

Trips to destinations like Italy and Israel also highlight experiential learning opportunities through an academic degree requirement called Immersion Vanderbilt , which provided funds to reduce student costs for the trip to Italy.

“There’s no better way for students to learn than to provide them with real-world experience,” said Cynthia Paschal, senior associate dean for undergraduate education. “Study abroad initiatives like these are examples of the ways Vanderbilt is assuring our students are prepared to compete on a global stage.”

For the Italy trip, the CEE Department provided a staffer to help with organization and on-site logistics, and the School of Engineering provided support so that students on financial aid could participate. Additionally, philanthropic support from the company Finfrock helped offset travel costs.

Contact: Lucas Johnson,  [email protected]

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How abu dhabi is bringing the world’s first esports island into its future.

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Aerial view of Abu Dhabi, United Arab Emirates, high-rise buildings and some of the emirate's ... [+] 200-plus islands.

In Abu Dhabi, two modern high-rises bookend a cluster of multi-story, low-lying buildings. At the moment, the structures appear in renderings for what would be the world’s first esports island. But while investments in esports have been cooling off in many places around the globe, plans for the industry-defining megaproject are heating up in the capital city of the United Arab Emirates.

News of the esports island emerged as True Gamers, an operator of a global network of gaming lounges and clubs, announced intentions for a $280 million investment in what is projected to be a $1 billion development. The island would include a digital technology and innovation workspace in one tower, a resort hotel in another tower, a complex of training and meeting spaces, and an arena designed for hosting multi-format events and exhibitions. Even in concept, the project advances Abu Dhabi among regional destinations that are rapidly growing as global centers for sports and sports-led development.

The location being eyed for the esports island is in the centrally-located Al Raha district of residential, retail, commercial, and recreational properties nearby the city’s Zayed International Airport. It sits across a waterway from the sports- and leisure-focused Yas Island .

Yas is renowned for hosting prestigious sports events like the Formula 1 season finale, UFC mixed martial arts cards, NBA exhibition games, and DP World Tour golf tournaments. It welcomes hundreds of thousands of visitors to its Ferrari World, Waterworld, Warner Bros. World, and SeaWorld theme parks. Luxury hotels, shopping malls, golf courses, restaurants, and nightlife venues lend to an entertaining year-round atmosphere. For most of the time since opening in 2009, Yas has also presented a range of health and fitness sessions for the public, including making the entire F1 track available twice weekly for walking, running, or bicycling by people of all ages, abilities, and interests.

While Yas may stand out as a prominent destination for sports-related amenities among Abu Dhabi's array of 200 islands, it is not alone. Another is Huydayriat Island , a 3000-hectare (approximately 7500-acre) fitness- and nature-focused island that includes a surf park, cycling tracks, a velodrome, football pitches, basketball and tennis courts, running and walking trails, skate parks, an obstacle course, watersports, and sixteen kilometers (about ten miles) of beaches. Saadiyat Island has cultural, heritage, educational, residential, recreational, hospitality, and tourism offerings, including kayaking routes that wind around and into the Louvre Abu Dhabi museum.

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Department of Culture and Tourism Abu Dhabi chairman Mohamed Khalifa Al Mubarak recently shared that the emirate’s tourism strategy considers more than $10 billion in state-sponsored and public-private partnership infrastructure investments between now and the end of the decade . The results of those projects figure to add $24.5 billion to the nation's annual gross domestic product. An island that caters to esports and gaming would fit in among those plans and the range of nature preserves, cultural sites, leisure spots, tourist attractions, and commercial centers across the emirate’s existing islands.

But an esports investment wouldn’t come into being for purposes of economic opportunism or public relations gains. It would be because it aligns with the objectives and goals of Abu Dhabi Vision 2030 , the roadmap set forth by the government in 2006 to ensure a sustainable economy.

During the past two decades, governments of cities and nations across the Gulf region have been making massive investments into transforming their economies from a reliance on oil-based operations to an interest in knowledge-based organizations. The strategy aims to enable self-sustaining industries in anticipation of the day in the middle of this century when the bulk of oil reserves are figured to run dry.

The model that the UAE is following to achieve that is “unique and novel,” says Robert Salomon, dean of the NYU Stern School of Business at NYU Abu Dhabi and a professor of management at NYU Stern. “The traditional model in the developing world has been export-led growth. For Abu Dhabi, it’s ‘let's just jump from an oil-based, developing economy and go straight toward services and a knowledge-based economy.’”

The trillions of dollars of investment being committed to these changes are not being driven primarily by economic development, though. They are being powered more so by social impact.

The Abu Dhabi economy is fashioned around a society designed for living, working, and connecting. In terms of approach, it bucks the classical model that puts economics over society. In terms of culture and worldview, it places a premium on improving social pursuits as a means to stirring economic opportunities. Sports and sports-led development are part of that ambition.

“One of the features that defines a developed country is leisure time. And one of the things that people do when they have leisure time is they dedicate more time to sport,” Salomon says. “Sport is one of the markers of a society that has developed.”

From Salomon’s perspective, Abu Dhabi’s local and global investments in sports, the arts, entertainment, film, and creative services are indicators that the emirate has arrived at an inflection point in its evolution. That opens its leadership and people into a new round of thinking-through the questions about what developed countries do and what developed countries can do. “A project like the esports island is consistent with that happening,” he says.

As the esports island emerges on the horizon, Abu Dhabi has a well-established track record of hosting esports events. For example, it recently welcomed back the Blast Premier World Final, an international tournament with a $1 million prize pool, for the second time. Events like that highlight the region’s growing presence in the esports industry.

Esports-related revenue in the region had an annual increase of nearly eight percent to almost $2 billion last year and is on pace to continue rising through the end of the decade, according to a report by Niko Partners . Saudi Arabia generated more than half of the revenue, followed by the UAE with almost one-third of it. This surge in esports, alongside Abu Dhabi's increasing focus on gaming and digital entertainment, is evident decisions such as the integration of Abu Dhabi Gaming—a government-led initiative that aggregates the local gaming ecosystem around talent development, game development, digital education, and esports—into the portfolio of the Department of Culture and Tourism Abu Dhabi late last year.

From ancient times through the middle of the past century, the Abu Dhabi economy was fueled by fishing and pearl diving. Then came oil and trade. Now and in the foreseeable future, it is knowledge and culture. With plans for projects like the world’s first esports island on the rise, Abu Dhabi is primed to further its status as a global sports hub.

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Computer Science > Computation and Language

Title: multi-hop question answering under temporal knowledge editing.

Abstract: Multi-hop question answering (MQA) under knowledge editing (KE) has garnered significant attention in the era of large language models. However, existing models for MQA under KE exhibit poor performance when dealing with questions containing explicit temporal contexts. To address this limitation, we propose a novel framework, namely TEMPoral knowLEdge augmented Multi-hop Question Answering (TEMPLE-MQA). Unlike previous methods, TEMPLE-MQA first constructs a time-aware graph (TAG) to store edit knowledge in a structured manner. Then, through our proposed inference path, structural retrieval, and joint reasoning stages, TEMPLE-MQA effectively discerns temporal contexts within the question query. Experiments on benchmark datasets demonstrate that TEMPLE-MQA significantly outperforms baseline models. Additionally, we contribute a new dataset, namely TKEMQA, which serves as the inaugural benchmark tailored specifically for MQA with temporal scopes.

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