Journal of Tourism Futures

collaborative AI applications (designed to operate cooperatively rather than substitute humans) can improve human efficiency and simplify processes (Maddikunta et al., 2021). In this way, the collaboration between users and AI allows for the creation of value-added services and improvement in decision-making and offers a personalised experience to cultural tourist users. This HAIC can be considered a characteristic of Industry 5.0 (Demir et al., 2019): robots and humans working together whenever and wherever possible. 2.2 Dimensions of user–AI interactions in cultural institutions Studies on interactions between users and AI have greatly increased in past years (Markovic et al., 2021). Nevertheless, there is still a need for theoretical and methodological frameworks to advance knowledge in this area (Bartneck et al., 2007; Ivanov et al., 2019). Researchers have attempted to conceptualise and implement the different dimensions of interactions between users and AI applications to explain user satisfaction and experience (Tussyadiah and Park, 2018; Primawati, 2018). Based on previous theories (Venkatesh et al., 2003; Wirtz et al., 2018), researchers have attempted to conceptualise and operationalise the different dimensions of user–AI interactions. Other authors explain the user interactions with AI applications (Tussyadiah and Park, 2018; Primawati, 2018). Considering these previous studies, the dimensions of AI applications can be classified into three groups: functional, contact and co-experience dimension. 1. The functional dimension refers to the ease of use of technology and its usefulness and the adoption of social norms. Schepers and Wetzels (2007) say that there is a significant influence of subjective norm on the perceived usefulness and the behavioural intention to use. When cultural institutions consider AI-supported solutions in operational contexts, the value proposition continues to be unclear for many due to upfront resource investments and subsequent opportunity costs (French and Villaespesa, 2019). Nevertheless, understanding the drivers behind user attendance to cultural venues like museums and how to increase these numbers is important to museum and other cultural institutions’ managers (Yap et al., 2020). 2. The contact dimension is based on the proposal from Van Doorn et al. (2017), about the “automated social presence” in services which refers to the extent to which machines (e.g. robots) make users feel that they are in the company of another social entity. Social presence has been shown to affect trust-building since individuals are more likely to develop trust in another person when they meet personally. It can be assumed that social presence or the feeling that“someone is taking care” affects acceptance and consequently has an influence on customer behaviour (Wirtz et al., 2018). 3. The co-experience dimension describes experiences regarding how individuals develop their personal experience based on their social interaction with others. The experience of visiting museums and cultural institutions can be enhanced with the application of AI to collaborate on their own experience by interacting with these tools. The USUS model (Weiss et al., 2009) introduces the co-experience indicator within the context of user experience. For some services, the acceptance of AI applications will depend on the extent to which technologies can fulfil consumers’ need for rapport (Wirtz et al., 2018), co-creation (Tung and Au, 2018) or conversation (Bickmore et al., 2013) that increases engagement and thus results in greater user satisfaction (Kim et al., 2015). From these bases, this paper proposes a conceptual framework that considers the three main identified dimensions (Figure 1). This framework will be used in the empirical study that is presented in the method section. From Figure 1, it can be observed that the co-experience dimension plays a central role in the interactions between AI applications and users because it constitutes the main source for the experience. The conceptual framework also considers the double perspective of production and experience domains along the three dimensions identified. Because all the dimensions are closely linked, collective management is the only way to create an innovationbased sustained competitive advantage. PAGE 4 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

3. Method 3.1 Design of the research and approach The study adopts a deductive approach (Bingham and Witkowsky, 2021), starting from the literature review and previously presented conceptual framework (Figure 1). This approach is based on qualitative methods allowing to examine two roundtable discussions (Zheng et al., 2020; Orea-Giner et al., 2021b; Damian et al., 2021). The objective is to identify the potential and the challenges to the usage of AI applications in cultural institutions from the perspective of cultural institution experts and cultural tourists. 3.2 Roundtable discussions’ guide and organisation The roundtable guide considered previous studies, and it was divided into three blocks: (1) the functionality of AI (Pinillos et al., 2016; Wu and Cheng, 2018; Wirtz et al., 2018; Ivanov et al., 2018; Tussyadiah and Park, 2018; Ivanov et al., 2019; Li et al., 2021), (2) the contact of AI with users (Primawati, 2018; Tussyadiah and Park, 2018; Gaia et al., 2019; Fuentes-Moraleda et al., 2021) and (3) the co-experience dimension of AI (Heerink et al., 2010; Van Doorn et al., 2017; Stock and Merkle, 2018). The roundtable discussions were held on 11 November 2021, with an average length of each session of 105 min. Each roundtable discussion was conducted by a moderator. Due to health restrictions, the roundtable discussions were conducted in a mix format, combining the physical presence of participants and the online participation of some of them. Both roundtable discussions were done in Spanish, and Microsoft Teams was used for recording and connecting with online participants. Previously, this approach was regarded as a reliable and viable way for doing qualitative research (Cachia and Millward, 2011; Fuentes-Moraleda et al., 2021). The roundtable discussions were videotaped with the participants’ permission. 3.3 Participants The two roundtables’ participants were (1) professionals from cultural institutions (2) and participants who engage in cultural tourism activities and visit cultural institutions during their holidays and daily life. For the first roundtable discussion, the participants were chosen through purposeful sampling based on their expertise (Patton, 1990) linked to cultural institutions’ management or technology enterprises focused on the cultural institutions’ solutions. Figure 1 Dimensions system: interactions between user–AI applications in service experiences of cultural institutions from the Industry 5.0 approach VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 5

According to previous research, each study has its own set of traits and criteria, making it impossible to establish a standard sample size for this approach (Hennik et al., 2019). Based on the data and orientations supplied (Hennik et al., 2019), our study comprised 6 different participants in each roundtable discussion. These participants were chosen so that there was an equal number of each gender and that their profiles were similar. The first roundtable discussion includes professionals from cultural institutions with previous AI experiences. The researchers made a list of professionals working in or for cultural institutions and connected with technology aspects (marketing, communication, cultural management, AI development, etc.). This list contained 18 names from different institutions. These professionals were contacted, and, finally, 6 participants participated (Table 1). The second roundtable discussion was focused on the cultural institutions’ users selected on the basis of their background in visiting cultural institutions and museums, as well as their interest in cultural activities during their travels. All participants must have previous experiences with AI. In this way, it is possible to get a broader view on their contact with technology and the needs of the cultural tourist as a user of cultural institutions and not only as a visitor (Table 2). This group can be divided into the following categories: Generation Z, Millennials, users with children and users with disabilities. The researchers used snowball sampling (Noy, 2008) to find individuals from different profiles and contacted them. Initially, 22 people were contacted, and, finally, 6 individuals having previous experiences with AI accepted to participate in the roundtable discussion. Table 1 Cultural institutions experts participating in discussion 1 of the roundtable Gender Expertise Position Previous interaction with AI Code Female Marketing Director of marketing and strategic business development at a museum Yes RTD1P1 Male Marketing Head of the commercial and educational area at a cultural institution Yes RTD1P2 Male AI developer CEO of a technological company Yes RTD1P3 Female Communication Deputy director for scientific communication and culture Yes RTD1P4 Male Communication Dissemination department Yes RTD1P5 Female Expert in management of cultural institutions Academic Yes RTD1P6 Table 2 Cultural tourists and users participating in roundtable discussion 2 Type Gender Profession Previous interaction with AI Code Generation Z Female Student Yes RTD2P7 Generation Z Male Student Yes RTD2P8 Generation Z Female Graphic designer Yes RTD2P9 Millennial Female PhD candidate and worker in a tourist information office Yes RTD2P10 Millennial Female Curator candidate Yes RTD2P11 Person with children Female Community manager Yes RTD2P12 Person with children Male Aerospace engineer Yes RTD2P13 Person with disabilities Female Artist Yes RTD2P14 PAGE 6 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

3.4 Data processing and analysis The initial step was transcribing all the roundtable discussions. The transcription was done in Spanish (primary language utilised) using the Amberscript tool. Transcriptions were reviewed manually to ensure their accuracy. The second phase involved manually coding and analysing the data using NVivo. A thematic analysis was done. This method allowed for the identification, dissection and announcement of subjects in the data (Braun and Clarke, 2006). A search for and an identification of recurring themes in the qualitative data gathered from the roundtable discussions was done. The analysis was performed by one researcher and checked later by another one, having a 96% of coincidence. After solving the detected disagreements, the findings were organised into categories based on the framework (Figure 1). 4. Results and discussion The complementarity between the two roundtables necessitates us to present the main results in an integrative manner according to the structure of dimensions that shape the framework employed: (1) functional dimension, (2) contact dimension, (3) co-experience dimension. Participants’ comments from the roundtable composed of experts and cultural tourists and users are codified using “RTD1Pi” and “RTD2Pj”, respectively. 4.1 Functional dimension The functional dimension is fundamental in offering an integrated experience with respect to the rest of the existing tools and resources in cultural institutions. AI is used to attempt to automate communication, observation, knowledge, decision-making and response and reasoning by replicating users’ thinking and learning processes. All these skills are as interrelated as are the corresponding subfields of AI, which are distinguished by their techniques and applications (Mich, 2022). In AI, users must be maintained in the loop of automation processes using a semi-automatic approach any time technologies are unable to totally replace users’ intelligence (Mich, 2022). The following quotes are from the roundtable discussion data: In some museums that have installed smart speakers [...] Then the user would arrive, the voice assistant would speak and there would be a dialogue about the work with the speaker [ ...]. You were talking to a speaker, and it was giving you information that you were specifying in a conversation [ ...]. (RTD1P2) This type of technology is not applied in all cultural centres, but the participants considered that it would be interesting to be able to consult the information about the works exhibited in museums, about access to the rooms and about other aspects related to obtaining information quickly. Another AI function mentioned during the discussion is the use of beacons to connect with a user’s smartphone and thus to be able to offer information. Beacons are seen by cultural institutions as being simpler to use and to implement in terms of costs than other systems, such as robots. Because of this, many cultural institutions now incorporate AI, but just a handful deploy a robot system in their rooms or spaces (Fuentes-Moraleda et al., 2021). The most notable and intriguing characteristic of a museum service robot is its capacity to present as much information as feasible about the culture that a museum represents. The robot knows where every piece is – not just the museum’s showpieces – and can encourage users to go see less well-known items, thus giving users the opportunity to expand their artistic knowledge while providing the museum with a means of developing the artistic potential of often-overlooked pieces. Another need for the use of social robots in museums arises due to their capacity to communicate and display moods and emotion (Kirby et al., 2010). However, the application of robotics in museums is seen as problematic, as can be seen in the following statement by one of the participants: Talking about robotics, [...] when you want to introduce an element into, for example, a workshop, the prices are very high, or you must go for simpler robots that allow you to do fewer things in order to have a reasonable cost. [...] Another handicap that I think has already been mentioned with robotics is what VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 7

happens when we have very large flows of visitors, which is one of the hallmarks of our identity. (RTD1P5) Therefore, the different functionalities that robotics can provide are affected by a series of difficulties to their implementation in the space of cultural institutions both because of their high cost and their difficulty to operate in certain spaces. Under this category, the quote below was frequently discussed: The robot is an object that is part of the museum, in addition to the visit you are making. So, I mean that the secret is to integrate it well. The user’s experience is a fluid experience, where that element links directly. It is not something forced that you want to put in, but something that forms part of that experience. (RTD1P3) Participants consider that to implement robots in cultural centres, this challenge related to the problems they can generate and that could affect their experience must first be addressed. However, there are other AI functionalities that can be applied in cultural institutions. One of the functionalities is the ability to generate a more complete experience for cultural tourists and users during the pre-experience, experience and post-experience so that it is possible to select the elements to see and make a personalised experience, as can be seen in the following quote: I would like a lot as a user the possibility [...] of making a selection of the work I want to visit so I can get information about it and get a more personalised tour and be able to take advantage of the time I want to invest. (RTD2P7) In addition, this personalised visit function through AI could be used to generate accessible itineraries with functional diversity for people. The potential of implementing these technologies in the future is linked to the creation of collaborative experiences. It is a field yet to be explored despite the advantages of their application for all audiences and especially for users with disabilities during pre-experience and experience. The following quote highlights the possibility of using this functionality to offer an accessible itinerary: Once you get to the museum, it’s true that I don’t know of any museum that has an accessible itinerary to be able to move from the entrance of the museum, to know where you enter and maybe get to a specific floor [ ...]. I understand that not all the resources are going to be accessible. (RTD2P14) Another aspect of the application of AI is the technological difficulties in its application due to a lack of funding from cultural institutions. This affordability problem can be overcome by using cheaper systems that are easier to implement, such as web pages with integrated chatbots. Consumers are beginning to embrace chatbots despite their limitations, such as a lack of support of the client’s mother tongue in chatbot conversations and the mismatch that sometimes happens between a chatbot’s pace and that of the customer. More personalisation and customisation are required (Pillai and Sivathanu, 2020). Some museums in different countries are developing chatbots to assist their users and provide a different and enhanced user experience (Varitimiadis et al., 2021). Participants consider that the website is the first contact with the cultural institution, being in the future an opportunity to create personalised visits, by implementing, for example, chatbots. The following are the frequently mentioned quotes in this category: I work in digital marketing, and I also miss a lot on the websites of the museums themselves. It would be interesting if there were chatbots through which I could make quick and immediate enquiries. (RTD2P12) A key aspect is the desire by cultural institutions for apps to plan, organise and receive information. These types of apps are considered inefficient, and it has been stressed that it is possible to create a web app which is more accessible and interactive than an app that is used during a preexperience, experience and post-experience. The following sentence summarised this: You don’t really need to download an application nowadays either. Web applications work in the good old-fashioned way that you go to a website and are fully interactive and have all the possibilities that you really need in an app nowadays. (RTD2P13) PAGE 8 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

Finally, functions must be monitored and reviewed on an ongoing basis so that information is reliable – especially if the functions are used to provide information regarding the visit of persons with vulnerabilities due to their special needs. Guo et al. (2020) examine how AI may harm specific handicap groups if it is not designed, developed and tested with care. Furthermore, Smith and Smith (2021) report that AI systems do not yet work properly for disabled people or, worse, may actively discriminate against them. Future technology implementation should evaluate the accessibility, not only regarding the physical aspects of cultural institutions but also the technology itself. The following quote sums up the dangers posed by AI to people with disabilities: I wouldn’t trust technology one hundred percent especially depending on the information it gives. And regarding what is in a museum, maybe if it’s about the life of an artist, of course, I’m going to trust what they tell me. (RTD2P14) 4.2 Contact dimension AI makes it easy to reach different audiences and personalise a visit, so it is essential in reaching out to digital natives. For example, Gen Z’s tastes differ from those of previous generations. In general, Gen Z is a generation that employs time-saving smart gadgets, seeks a one-of-a-kind experience and authenticity and plans its own budget and journey (Ozdemir-Guzel and Bas, 2021). According to Vitezic and Peri c (2021) , hedonic motivation (rather than anthropomorphism, effort expectation, performance expectations and social influence) had the greatest impact on Gen Z’s emotions and, as a result, their willingness to use AI devices. They also observed that the frequency with which people used their smartphones had a moderating influence on the association between perceived effort of utilising AI and emotions. The following are some of the most referenced quotes in this category: It fascinates me when you see those videos on YouTube ... of a child, the one-and-a-half-year-old girl who still can’t read [...] How is she going to face a painting when she’s 18? (RTD1P3) The type of contact with AI is crucial. In the case of user–robot interaction, robots can be classified as utilitarian, cartoonish, human-like or mixed based on their appearance (Tung and Au, 2018). The type of user, the form, voice and other factors related to the design of the AI device that is in contact with a user can cause either rejection or acceptance by the user. During the roundtable discussions, this fact was commented on: I think a humanoid robot would be very off-putting to me and I think it also takes the attention away from the museum. I think it’s not something that people are used to seeing, so I think in a museum that would be the focus of attention, and I think it’s not appropriate because the focus should be the museum itself. [...]. (RTD2P13) Chuah and Yu (2021) point out that the development of emotional intelligence in robots also brings about a huge paradigm change in how people interact with them. This statement is linked to the search for a more emotional and sensory AI, which, through contact with a user, allows for the development of an inclusive, immersive and interactive experience when considered in a holistic way, including the pre-experience, experience and post-experience. At present, these aspects are not implemented in cultural institutions. This aspect is discussed using an example of a visit made by one of the participants: It is quite a sensory visit. It plays a lot with the theme of temperature and even smells, and you are given a little bracelet at the entrance to the museum. As you enter the different rooms, you pass it through a reader, and it welcomes you to the room in a personalised way. It can even give you complementary information in some areas. You can even take a photo and it automatically arrives in your mailbox. I understand that for them it is also a very big source of information [...] I felt very included in the museum because they are welcoming you and I felt connected to that world. (RTD2P10) This search for an interactive and immersive experience is notable among members of Generation Z, who are looking to AI for a transmission of information that is not only purely theoretical about the content of cultural institutions but that also allows them to transmit and awaken emotions and VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 9

feelings before, during and after a visit. To this end, they emphasise that the form of contact is fundamental. This aspect can be seen in the following quote: [...] I would like to know or feel what people perceive when they are looking at that painting, what sensations you can get [ ...]. For example, you could have a tablet with which you could personalise the visit, for example, with a QR code acquired when you buy the ticket, and you can navigate through the museum with this code while asking yourself, ‘What do you feel when you see this, and what do you like about it?’ Thus, ensuring that not only is the user seeing the exhibition but that you are also giving feedback while you are seeing it while receiving a result. (RTD2P9) This contact with AI does not replace the contact with the staff of cultural institutions but is interpreted as another resource of the cultural institution for generating a satisfactory overall experience for the user (tom Dieck et al., 2018). 4.3 Co-experience dimension The co-experience dimension is linked to the concepts of co-creation and co-production (Minkiewicz et al., 2016). To co-create as an inherent aspect of service, the interplay between consumers, workers, cultural institutions and technology must be considered (Sarmah et al., 2018). AI can be used as a tool for creating a community around the cultural institution from a holistic perspective, specifically in the post-visit phase. The following statement sums it up: It could also help us to be more involved in the life of the museum, like trying to co-create a little bit with it. [ ...]. Everything as a process, [...] as a tool that can be used as a tool to help us to create community. (RTD2P11) AI can be used to create continuous collaboration during all phases of the user experience (preexperience, experience and post-experience) between users, employees and the cultural institution to generate immersive, integrated and collaborative experiences. By using AI, it is possible to collect user data to create a personalised visit as well as to generate continuous feedback to the cultural institution. This can be seen in the following statements: There is a lot of technology which, based on all the extraction of this data, personalises your visit and offers one content or another based on your behaviour and your interests. If you are registered, [...] it knows absolutely everything about you. [...] what we need is to make that information actionable so that that digital experience is good, satisfactory and memorable. (RTD1P4) Roundtable participants highlighted that this technology would be very useful in the future to be able to personalise their visit to cultural centres. However, at present, they have not been able to make use of it because it is not yet implemented. This collection of user data enables the application of machine learning techniques. Previous studies have demonstrated the possibility of predicting consumer behaviour by applying machine learning based on previously collected data (Arefieva et al., 2021). It is possible to use artificial intelligence and machine learning to guide the visit and also if you share your visit with other people who can interact together and change a little bit as well. (RTD2P12) The use of AI to generate co-experiences also creates an emotional link with a user, which goes beyond the visit because it can allow contact before, during and after the visit, creating a personalised experience for the user and guaranteeing access to information for the managers of cultural institutions to improve decision-making in the future. This connection, which is currently non-existent, would be based on obtaining recommendations on cultural institutions and would create a flow of connections and relationships with the cultural institution, as the following commentary shows: I think it can connect, just as we do with Netflix, when it gives us recommendations. [...] Maybe the works you’ve visited the most, and the time you’ve invested in each one of them. If you have viewed more information about a particular type of work, that exhibition will send you an itinerary – even more additional information – afterwards. [ ...]. (RTD2P12) PAGE 10 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

However, the main problem detected with the co-experience dimension is the possibility of collecting data on users to personalise the experience based on their profile, interests and behaviour. Data sharing is key to promoting this collaboration and generating experiences, but reluctance to share data can be an impediment to the implementation of this AI function. Previous studies confirm that principles and guidelines for ethical AI must be applied in these types of contexts (Jobin et al., 2019). This use of data to personalise the visit to cultural institutions is not currently applied, but it is an aspect that would enhance the visitor experience, as the following sentence shows: I am personally very reluctant to give my personal data to anyone because in the end it is shared with third parties. You are never really in control of your information. (RTD2P8) Therefore, in the application of AI in cultural institutions, ethical and security principles must be considered when collecting data, which can be achieved through the creation of a community based on the co-experience dimension. 5. Conclusions Cultural institutions are a type of tourist resource that can enhance the brand image of cultural destinations (Lindsay, 2018) as well as to promote the arrival of tourists (Gravari-Barbas, 2020). Cultural institutions are in continuous change given that their basic aim of protecting culture is going to be maintained, as the results show. However, the approach of interacting with users must be adapted to the transition to Industry 5.0 tools to create collaborative experiences and customise the experience in the future. These technology applications enhance access to collections rather than minimising the relevance of the content (Koukoulis and Koukopoulos, 2016). Cultural tourists and users of cultural institutions are experimenting a change on their profile linked to technology development. The elite position of culture will be eroded as high culture is replaced by “the local” in many places (Russo and Richards, 2016). Considering different local and tourist segments, digital natives, such as Gen Z (Ozdemir-Guzel and Bas, 2021), seek a different approach to cultural institutions than digital immigrants, as the analysis confirms. These audiences do not have the same concept of cultural institutions and visit them in completely different ways. As the results shows, this fact makes the advanced development and application of AI unfeasible because of the requirement of a large investment and the long process of checking and testing the functionality of this technology. This means that cultural institutions end up using simple AI systems that do not work well and can generate problems for users. They also neither personalise the experience nor make use of Industry 5.0 approach. In conclusion, cultural institutions must use AI in an integrated way to create a community in the context of the Industry 5.0 approach while considering all the key actors. AI is not just another tool and does not replace staff, but rather helps to connect with cultural tourists and users. It allows staff to get to know the users better besides generating an immersive experience. Moreover, AI is essential in creating a community and building it day by day. Therefore, AI is not seen as just a tool but as a part of the whole. Users want to be part of the community and to participate by co-creating personalised experiences focused on attracting tourists and local users in the future. 5.1 Theoretical implications The main theoretical implication is the definition of a model (Figure 2) including a holistic perspective of user experience of AI applications in services experiences of cultural institutions, considering the three dimensions. This model arises from the analysis of qualitative data from the point of view of users and experts participating in this study. This model sets out the fundamental aspects to be developed through AI tools in a user’s journey map from both managerial and users’ perspectives. The visit (virtual and face-to-face) is considered an experience. These tools could be implemented at the pre-experience, experience and post-experience phases around the three dimensions considered. In the model (Figure 2), VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 11

the HAIC is the centre that emerges from the functional and contact dimensions. During the preexperience phase, communication strategies of cultural institutions could reinforce the planning of the visit through the implementation of AI. These strategies include pre-visualisation of the spaces, schedules and reservation of experiences. During all the experience phases, AI applications can be implemented in an inclusive, immersive and interactive way. In addition, there are other aspects such as community building, collaboration and emotional links where users and managers are involved. For instance, machine learning methods can be applied to collect data from the visitors’ physical experience and from all the different digital touchpoints of that journey, like the website, social media, ticketing and mobile apps (French and Villaespesa, 2019). From another perspective, in museums and cultural institutions, recommender systems can prevent information overload for visitors by presenting interesting items based on the visitor’s interest in the already seen items. 5.2 Practical implications Regarding the practical implications, the application of AI from an Industry 5.0 perspective allows cultural institutions to interact with users during the pre-experience, experience and postexperience; learn more about their profile and interests to personalise their experience; and introduce elements of brand value such as co-creation of experiences and community-building. Some AI applications that can improve the visitors’ experience are chatbots helping visitors organise their visit and offering a personalised experience. Virtual reality can offer broader access, particularly to remote visitors, providing “virtual tour” experiences. Moreover, social robots’ implementation in museums and cultural institutions can improve the visitors’ experience due to the possibility of offering services in different languages, creating inclusive experiences for disabled people and being available 24/7. In addition, managers of cultural institutions focused on user care can obtain crucial data and information to develop visits by creating inclusive, immersive and interactive experiences. 5.3 Limitations and suggestions for further study There are some limitations to this study. First, because of the health crisis, the three roundtable conversations were held in a hybrid format (online and face-to-face), and the selected roundtable Figure 2 User experience and AI application in services experiences of museums and cultural institutions from an Industry 5.0 approach PAGE 12 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

discussion format may have influenced the participants’ responses owing to its public event status. Second, in terms of the flexibility of the thematic analysis, which might have led to inconsistency and lack of coherence (Terry et al., 2017), each member of the research team validated the analysis. Future research should consider the actual and specific application of AI tools in cultural institutions, as well as considering different characteristics (e.g. size, type, place of cultural institutions) to obtain conclusions about the different dimensions identified in this study. Future research will be conducted considering the case vignette method, previously used in qualitative studies (Fritzsche and Bohnert, 2021). References Akundi, A., Euresti, D., Luna, S., Ankobiah, W., Lopes, A. and Edinbarough, I. (2022), “State of industry 5.0 analysis and identification of current research trends”, Applied System Innovation, Vol. 5 No. 1, p. 27. Arefieva, V., Egger, R. and Yu, J. (2021), “A machine learning approach to cluster destination image on Instagram”, Tourism Management, Vol. 85, p. 104318. Armbrecht, J. (2014), “Use value of cultural experiences: a comparison of contingent valuation and travel cost”, Tourism Management, Vol. 42, pp. 141-148. Bartneck, C., Suzuki, T., Kanda, T. and Nomura, T. (2007), “The influence of people’s culture and prior experiences with Aibo on their attitude towards robots”, Ai and Society, Vol. 21 No. 1, pp. 217-230. Belanche, D., Casalo, L.V. and Flavi an, C. (2019), “Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers”, Industrial Management and Data Systems, Vol. 119 No. 7, pp. 1411-1430, doi: 10.1108/IMDS-08-2018-0368. Bickmore, T.W., Vardoulakis, L.M.P. and Schulman, D. (2013), “Tinker: a relational agent museum guide”, Autonomous Agents and Multi-Agent Systems, Vol. 27 No. 2, pp. 254-276. Bingham, A.J. and Witkowsky, P. (2021), “Deductive and inductive approaches to qualitative data analysis”, Analyzing and Interpreting Qualitative Data: After the Interview, pp. 133-146. Bonacini, E. and Giaccone, S.C. (2021), “Gamification and cultural institutions in cultural heritage promotion: a successful example from Italy”, Cultural Trends, pp. 1-20. Braun, V. and Clarke, V. (2006), “Using thematic analysis in psychology”, Qualitative Research in Psychology, Vol. 3 No. 2, pp. 77-101. Cachia, M. and Millward, L. (2011), “The telephone medium and semi-structured interviews: a complementary fit”, Qualitative Research in Organizations and Management: An International Journal, Vol. 6 No. 3, pp. 265-277. Calero-Sanz, J., Orea-Giner, A., Villace-Molinero, T., Mu noz-Maz ~ on, A. and Fuentes-Moraleda, L. (2022), “Predicting A new hotel rating system by analysing UGC content from tripadvisor: machine learning application to analyse service robots influence”, Procedia Computer Science, Vol. 200, pp. 1078-1083, available at: https://www.sciencedirect.com/science/article/pii/S1877050922003167 Camarero, C., Garrido, M.J. and Vicente, E. (2015), “Achieving effective visitor orientation in European museums. Innovation versus custodial”, Journal of Cultural Heritage, Vol. 16 No. 2, pp. 228-235. Capriotti, P. (2010), “Museums’ communication in small-and medium-sized cities”, Corporate Communications: An International Journal, Vol. 15 No. 3, pp. 281-298. Carayannis, E.G. and Morawska-Jancelewicz, J. (2022), “The futures of Europe: society 5.0 and industry 5.0 as driving forces of future universities”, Journal of the Knowledge Economy, doi: 10.1007/s13132-021-00854-2. Chuah, S.H. and Yu, J. (2021), “The future of service: the power of emotion in human-robot interaction”, Journal of Retailing and Consumer Services, Vol. 61, p. 102551. Clarizia, F., Colace, F., Lombardi, M., Pascale, F. and Santaniello, D. (2018), “Chatbot: an education support system for student”, in Castiglione, A., Pop, F., Ficco, M. and Palmieri, F. (Eds), Cyberspace Safety and Security, Springer International Publishing, Cham, p. 291. Cristobal-Fransi, E., Ramon-Cardona, J., Daries, N. and Serra-Cantallops, A. (2021), “Museums in the digital age: an analysis of online communication and the use of e-commerce”, Journal on Computing and Cultural Heritage (JOCCH), Vol. 14 No. 4, pp. 1-21. VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 13

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Van Doorn, J., Mende, M., Noble, S.M., Hulland, J., Ostrom, A.L., Grewal, D. and Petersen, J.A. (2017), “Domo arigato Mr. Roboto: emergence of automated social presence in organizational frontlines and customers’ service experiences”, Journal of Service Research, Vol. 20 No. 1, pp. 43-58. Varitimiadis, S., Kotis, K., Pittou, D. and Konstantakis, G. (2021), “Graph-based conversational AI: towards a distributed and collaborative multi-chatbot approach for museums”, Applied Sciences, Vol. 11 No. 19, p. 9160. Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D. (2003), “User acceptance of information technology: toward a unified view”, MIS Quarterly, pp. 425-478. Vitezic, V. and Peri c, M. (2021), “Artificial intelligence acceptance in services: connecting with Generation Z”, The Service Industries Journal, Vol. 41 Nos 13-14, pp. 926-946. Webster, C. and Ivanov, S. (2022), “Public perceptions of the appropriateness of robots in museums and galleries”, Smart Tourism Research Center, Kyung Hee University, Vol. 2 No. 1, pp. 33-39, doi: 10.1007/ s10055-020-00444-8. Weiss, A., Bernhaupt, R., Lankes, M. and Tscheligi, M. (2009), “The USUS evaluation framework for humanrobot interaction”, AISB2009: Proceedings of the Symposium on New Frontiers in Human-Robot Interaction, Citeseer, p. 11. Wirtz, J., Patterson, P.G., Kunz, W.H., Gruber, T., Lu, V.N., Paluch, S. and Martins, A. (2018), “Brave new world: service robots in the frontline”, Journal of Service Management. Wu, H. and Cheng, C. (2018), “What drives experiential loyalty toward smart restaurants? The case study of KFC in Beijing”, Journal of Hospitality Marketing and Management, Vol. 27 No. 2, pp. 151-177. Yap, N., Gong, M., Naha, R.K. and Mahanti, A. (2020), “Machine learning-based modelling for museum visitations prediction", "Machine learning-based modelling for museum visitations prediction”, 2020 International Symposium on Networks, Computers and Communications (ISNCC), IEEE, p. 1. Zheng, D., Liang, Z. and Ritchie, B.W. (2020), “Residents’ social dilemma in sustainable heritage tourism: the role of social emotion, efficacy beliefs and temporal concerns”, Journal of Sustainable Tourism, Vol. 28 No. 11, pp. 1782-1804. About the authors Alicia Orea-Giner is associate professor (tenure-track) in tourism management at the Department of Business Economics (Universidad Rey Juan Carlos). She is a member of the Openinnova research group and collaborates with Centro Universitario de Estudios Turısticos (CETUR). She is an associated researcher at the Equipe Interdisciplinaire de Recherches sur le Tourisme and supervisor of master’s theses at Universite Paris 1 Panth eon-Sorbonne. Considering research, she is social technologist for Sustainable Tourism ((ST)2 ). She is associate editor for Tourism Management Perspectives (JCR Q1). She actively participates in international conferences and is a reviewer of JCR-indexed journals. Alicia Orea-Giner is the corresponding author and can be contacted at: [email protected] Ana Munoz-Maz ~ on, PhD in social science, is a professor at the Rey Juan Carlos University in Madrid. Her extensive research and teaching background focuses on the fields of sustainability, planning, governance and development in tourism. She has collaborated with numerous national and international universities and works as advisor and researcher in several tourism projects with the UNWTO, The Women’s Institute in Spain and other institutions such as the Inter-American Development Bank, the European Union and the Spanish Agency for International Development Cooperation. Additionally, she participated in many projects with public tourism administrations and private companies in Europe, Latin America and Asia. Teresa Villace-Molinero, PhD in advanced marketing and master ’s in strategic marketing from the Universidad Autonoma de Madrid, is associate professor of tourism marketing and information technology applied to tourism management at the Universidad Rey Juan Carlos, for both undergraduate and graduate students. She has taught in other institutions such as Les Roches and the Chamber of Commerce. Villace-Molinero has also been a visiting professor at the Satakunta University of Applied Sciences (Finland). In the field of academic management, she has worked as coordinator of the degree in tourism at the Universidad Rey Juan Carlos for 5 years. Her professional activity has been linked to the field of tourism management from a marketing point of view. She has worked as marketing director in a company specialised in strategic consulting and VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 17

management of sports centres and spas in hotel chains (Meli a Hotels International, Barcelo Hotel Group). Her main areas of work have been focused on the tourism sector, specifically on issues related to consumer behaviour (customer loyalty), the use of technology (robots) and gender. As a result of the research projects in which she has participated, she has presented papers at both national and international conferences, and has publications in journals of international impact (JCR and Scopus). She is an editor and reviewer in several international journals. Laura Fuentes-Moraleda has a PhD in social sciences from UNWTO and Nebrija University, and she is lecturer of tourism market analysis and tourism planning at Rey Juan Carlos University, both for undergraduate and postgraduate levels. In the past fifteen years, her professional activity has been linked to the field of tourism destination management, and she has contributed to activities related to development and sustainable projects in tourist destinations in European and Latin American countries, while working with domestic agencies, public and private. She is deputy director at Tourism Studies Centre in Rey Juan Carlos University. For instructions on how to order reprints of this article, please visit our website: www.emeraldgrouppublishing.com/licensing/reprints.htm Or contact us for further details: [email protected] PAGE 18 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

Documenting the knowledge of pro-environmental travel behaviour research: a visual analysis using CiteSpace Jiale Zhang and Farzana Quoquab Abstract Purpose – The purpose of this study is to present a comprehensive knowledge mapping and an in-depth analysis of pro-environmental travel behaviour research to better understand the global trend in this field that have emerged between 2000 and 2021. Design/methodology/approach – In this study, a visual analysis of 187 scholarly articles between the year 2000 and 2021 related to pro-environmental travel behaviour (PETB) is presented. Using the knowledge mapping based on CiteSpace it presents the current research status, which contains the analysis of collaboration network, co-citation network, and emerging trends. Findings – The results revealed that the PETB is an emerging topic, which has an increased number of publications in recent years. Though the collaboration network between scholars is dispersed, some countries exert stronger collaboration network. Researchers from England, USA and China have worked more on this topic comparatively. “Pro-environmental norm” is found to be the major concern in regard to PETB, and the theory of planned behaviour (TPB) is the most common theory used by the scholars around the world. Ten articles with the highest citations are found to be the most valuable articles. COVID-19, value orientation, negative spillover, carbon footprints, biospheric and adolescent are some of the latest keywords based on the past two years’ literature review, all of which have huge research potential in the future. Originality/value – This study is among the pioneers to shed some light on the current research progress of PETB by using a bibliometric analysis to provide research directions for scholars. Moreover, this study utilized latest data from 2000 to 2021. The studies which are published before and during the pandemic are also incorporated. Keywords Tourists’ environmental responsibility, Pro-environmental travel behaviour, Tourism industry, Knowledge mapping, Visual analysis, CiteSpace Paper type Research paper Introduction Pro-environmental behaviour refers to the behaviour that can minimize the negative impact of individuals’ activity on the environment as well as can benefit the environment (Steg and Vlek, 2009; Wu et al., 2021). Likewise, the pro-environmental travel behaviour (PETB) indicates tourists’ likelihood to choose the frequency of travel, the destination, the mode of transportation, the tourism products and the activities during the travel for the purpose of environmental protection (O’Connor and Assaker, 2021). Indeed, it exerts a positive effect on the environment of tourism destinations and improves economic performance (Dartey-Baah and Amoako, 2021). Tourism destinations that are more involved in undertaking social and environmental responsibility tend to attract more tourists and improve their profits (Su et al., 2020). Although the tourism industry contributes to the growth and welfare of the society, it also generates environmental pollution and degradation (Azam et al., 2018; Sadom et al., 2022a, b). In recent Jiale Zhang and Farzana Quoquab are both based at the Azman Hashim International Business School, Universiti Teknologi Malaysia, Johor Bahru, Malaysia. Received 24 March 2022 Revised 13 July 2022 28 September 2022 Accepted 14 October 2022 © Jiale Zhang and Farzana Quoquab. Published in Journal of Tourism Futures. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http:// creativecommons.org/licences/ by/4.0/legalcode DOI 10.1108/JTF-03-2022-0101 VOL. ▪▪▪ NO. ▪▪▪ , pp. 1-22, Emerald Publishing Limited, ISSN 2055-5911 j JOURNAL OF TOURISM FUTURES j PAGE 1

years, with the increased focus on environment and the rapidly growing number of tourists, many researchers started to investigate the notion of tourists’ PETB from different country and cultural contexts. Some scholars focused on specific pro-environmental practices, such as low carbon travel, binning behaviour and zero litter initiative (Esfandiar et al., 2020; Hu et al., 2019; Liu et al., 2017). Some other researchers investigated the drivers of pro-environmental behaviours, such as personalized travel planning (Ahmed et al., 2020), use of the Internet (Wu et al., 2019), moral obligation (Wu et al., 2021) and environmental background (Wang et al., 2019). Since the outburst of COVID-19, the global tourism industry has suffered significantly. With the increased infectious cases and death toll, in order to defeat the COVID-19 pandemic, many countries have implemented strict policies and imposed lockdowns. Such lockdowns and social distancing measures affected the tourism industry seriously because governments closed all travel activities to control the spread of the pandemic. To understand whether there is any change of the travel behaviour of tourists, more scholars have started to explore the effects of COVID-19 on tourism behaviours (Matiza, 2022; Wachyuni and Kusumaningrum, 2020; Yang et al., 2021) and PETB (O’Connor and Assaker, 2021; Urban and Braun Kohlova, 2022
). In this study, we have included papers that were published before and during the pandemic, which is unique in nature. Even after 20 years of research, PETB remains a research topic that is worthy to be further investigated. Indeed, the carbon emission and environmental pollution have always been a difficult problem for the mankind to solve. In this regard, the COVID-19 is regarded as the revenge of nature on humans (Chakraborty and Maity, 2020). Considering this, the present study attempts to understand the issue to its depth and breadth using the knowledge mapping via CiteSpace. This study provides significant research insights for the practitioners to understand the PETB of tourists before and after the pandemic. For example, it is found that, during the pandemic, the tourists became more concerned about their health, and the hotels with the good sanitary facilities became more popular among the travellers (Heydari et al., 2021). Besides, travellers became more environmentally concerned than before (O’Connor and Assaker, 2021). Apart from showcasing the research status of the existing relevant literature, this study also enables scholars to have a general understanding of the future research trend on this topic. Knowledge mapping has been widely used in many disciplines to provide a systemic and objective overview of a specific research topic (Fang et al., 2018). CiteSpace is one of the commonly used software in bibliometric analysis, which is developed by Chen (2004). In the tourism industry, Fang et al. (2018) used CiteSpace to analyse climate change and tourism, whereas Li et al. (2017) analysed hospitality research using CiteSpace. However, to the best of our knowledge, there is a dearth of review papers on PETB. Though the outbreak of COVID-19 has a huge impact on PETB, there is a dearth of research that focused on PETB during pandemic. This study used the latest data that include COVID-19. In doing so, we provided a systemic and objective overview of research on PETB. Moreover, we aim to showcase bibliometric characteristics and visualize relationships of articles on this topic published in the scholarly reputed journals that are indexed in Web of Science (WoS) between 2000 and 2021. This paper is organized as follows. First, a review of PETB is provided, and the used materials and methodology are explained. Next, the results of the collaboration network, co-citation network and emerging trends of PETB are presented. Lastly, the discussions, implications, future research directions and limitations are explained. Pro-environmental travel behaviour (PETB) Different authors defined PETB in different ways, which are shown in Table 1. Overall, it is regarded as a behaviour embraced by the travellers to protect the environment and to boost economic performance. Not only definitions, different scholars have also studied the notion of PETB based on different theories. For instance, O’Connor and Assaker (2021) considered the norm activation model (NAM) and economic sacrifices theory to study the effect of COVID-19 on PETB. Wang et al. (2019) considered the theory of planned behaviour (TPB) and the broken window theory to PAGE 2 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

examine the moderating effect of environmental background on the relationship between traveller’s environmentally responsible behaviour and intention. On the other hand, Kiatkawsin and Han (2017) used value–belief–norm (VBN) theory and expectancy theory to study young travellers’ intention to behave pro-environmentally. Whereas Onwezen et al. (2013) used NAM and the TPB to explore the function of anticipated pride and guilt on pro-environmental behaviour. Past studies also examined the drivers of PETB and found that psychological factors (Nilsson and Kuller, 2000 € ) and situational factors (Heydari et al., 2021; O’Connor and Assaker, 2021) are likely to influence pro-environmental behaviour. Again, Han et al. (2018) studied the role of user-generated content on travellers’ pro-environmental behaviour in the Chinese context. Their study revealed that the content about pro-environmental knowledge and awareness both significantly encourage pro-environmental behaviour. Wang et al. (2019) used the broken window theory to explain the importance of environmental background to travellers’ environmentally significant behaviour. Whereas Wu et al. (2019) investigated the role of information technology on young adults’ mobility Table 1 The definitions of pro-environmental travel behaviour in past studies Variable Definitions Sources Pro-environmental travel behaviour (PETB) “PETB refers to pro-environmental behavior with respect to traveling less, traveling closer to home, traveling less by plane, choosing a destination, selecting transportation, choosing accommodations, making attractions and activity choices, and making more sustainable choices of tourism products in general.” (P. 8) O’Connor and Assaker (2021) Pro-environmental travel behaviour refers to the behaviours for “ achieving broader environmental and health objectives such as air pollution reduction, physical activity improvement and climate change mitigation.” (P. 2) Ahmed et al. (2020) PETB “means voluntarily choosing low-carbon travel, including public transport, non-motorised traffic and walking, based on an attitude of caring about the environment and a willingness to sacrifice some degree of convenience, comfort and time.” (P. 467) Chen et al. (2019) “Activity-travel behavior of an individual can be found by tracking the travel choices one makes to perform any activity and the environmental impact of personal travel is assessed in terms of the number of out-of-home trips, distance traveled, and the mode choice, such as walking, cycling, car and public transport usage. A more pro-environmental activity travel behavior is for example traveling shorter distances to perform a particular activity by using public transport, cycling/walking instead of taking the car.” (P. 110) Adnan et al. (2019) “Pro-environmental behavior is perceptive conduct executed by human beings in order to mitigate the damaging impact of human activities on the natural environment.” (P. 1873) Chuang et al. (2018) The PETB is the efforts that “people make, both before and during their vacation, can play an important part in creating a more sustainable tourism sector. For example, choosing accommodation and transportation with low carbon dioxide (CO2) emissions, can place pressure on the tourism industry to supply products and services that help to satisfy these demands.” (P. 196) Doran et al. (2017) Peoples’ behavioural consideration towards the environmental impact caused by travelling when make the choice of transport means and frequency of journeys for different destinations Nilsson and Kuller € (2000) VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 3

behaviour. The result shows that the changes in the usage of the Internet can positively influence pro-environmental intention. Based on these discussions, it is evident that there are more empirical studies to examine the drivers of PETB, and less emphasis is given to have a bibliometric analysis on the phenomenon, which this paper attempts to address. Undoubtedly, the outbreak of COVID-19 has taken a toll on the overall tourism industry’s growth and financial performance worldwide. Since the outbreak of COVID-19, it became a global concern whether the pandemic has affected tourists’ PETB too. Urban and Braun Kohlova (2022)
conducted a panel study before and during the COVID-19 lockdown, and they found that COVID19 did not change tourists’ pro-environmental behaviour. However, O’Connor and Assaker (2021) found that tourists’ risk perception of COVID-19 has a positive effect on PETB. COVID-19 has brought a serious threat to the health, environment and socio-economic aspects, and the news about COVID-19 can be seen everywhere. Nevertheless, the studies focusing on the effect of emergencies and crises on PETB are scant (Lucarelli et al., 2020). For instance, the role of risk communication, risk perception of COVID-19 and PETB are still not explored fully. The COVID-19 is still ongoing, but people started to cope with the situation. In this review, we have incorporated studies before and during the pandemic to provide a wider understanding of the matter. Materials and methodology Data sources For bibliometric analysis, it is necessary to obtain high-quality literature as the data source; thus, a reputable database should be selected (Fang et al., 2018). WoS includes the Science Citation Index Expanded, the Social Sciences Citation Index and the Arts and Humanities Citation Index database, which is regarded as an ideal data source for bibliometric analysis (van Leeuwen, 2006; Fang et al., 2018), which contains 12,000 leading journals worldwide. It has been widely used in the bibliometric analysis by many scholars from different disciplines (Fang et al., 2018; Li et al., 2017). As such, we collected data from the WoS Core Collection. In this study, we focused predominantly on environmental aspect and thus used “pro-environmental travel behaviour” as the keyword to search relevant articles. All literature studies that contained the word “pro-environment” either in the abstracts or keywords were included for analysis. To the best of our knowledge, the first article about PETB was published in 2000. Thus, in this study, we considered sources that were published between 2000 and 2021. In order to get high-quality research papers, review articles, book chapters and editorial materials were excluded, which yielded 187 articles to proceed for further analysis. Knowledge mapping Knowledge mapping is a kind of bibliometric analysis, which is regarded as “the quantitative analysis of publications in a given field” (Cui et al., 2018, p. 842). It helps scholars to better understand the current research status by providing a systematic and comprehensive knowledge of a specific research field. In bibliometric analysis, the analysis of the keywords enables the researchers to understand the latest hot research topics and the directions of future research. The information of authors, journals, institutions and countries can help scholars to understand the most contributing scholars, most authoritative institution, in order to create academic communication for future collaboration. Co-citation is the most significant analysis in bibliometric analysis because it can show the relations between articles. If an article shows high citation frequency and many links with other articles, it indicates high relevancy and importance of the topic on that particular field (Small, 2003). In this study, we used CiteSpce5.8.R2 software which was developed by Chaomei Chen. Compared with an earlier visualization tool, it can provide clearer and interpretable results (Chen, 2006). This software has been used by many scholars from different disciplines, such as hospitality research, social commerce research, tourism and so on (Cui et al., 2018; Fang et al., 2018; Li et al., PAGE 4 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

2017; Mensah et al., 2021; Wei et al., 2015). In the graph of CiteSpace, analytic objectives are represented by nodes (generally a circle shape). The bigger the node, the more valuable it is. And the coloured links between different nodes present their relationship, where different colours represent different publication years. We analysed the collaboration network, co-citation network and emerging trends using the CiteSpace. The analysis of collaboration network is an image, which can show the frequency of academic collaboration (scholar, country and institution). It is a basic output of bibliometric analysis, which can be conducted by CiteSpace. Co-citation network is another output which represents the most important work in the field because the more important an article is, the higher the number of citations. In the analysis of co-citation, different thicknesses represent different frequencies of cocitation (Chen et al., 2012). Additionally, the emerging trends can be shown by analysis of keywords. Results Research outputs and their categories As depicted in Figure 1, it is a progression of papers published about PETB for 21 years (from 2000– 2021). The first article about PETB was published in 2000, and the growth of publication number was seemed to be slow in the next ten years. However, the number of publications had a steady increase from 2011, and there has been a phenomenal growth of the number of publications on PETB from 2017. The number of publications is projected to increase continuously in the future. The growing number of publications shows that PETB is of increasing interest of scholars. All articles covered 53 subject categories in the WoS. The top ten subject categories are showed in Figure 2, including “hospitality leisure sport tourism” (75 articles; account for 35.4%), “environmental study” (55; 25.9%), “green sustainable science technology” (51; 24.1%), “transportation” (44; 20.8%), “environmental sciences” (37; 17.5%), “transportation science technology” (27; 12.7%), “management” (16; 7.5%), “psychology multidisciplinary” (14; 6.6%), “engineering environmental” (12; 5.7%) and “economics” (11; 5.2%). The top ten subjects’ distribution shows PETB is an interdisciplinary research topic. The hospitality, tourism, green sustainability, transportation and environmental issues are the most prominent topics focused by the scholars in this field. From “psychology and behaviour of tourists’ to “tourism management related to green sustainability” are all belong to such research areas. Figure 1 The number of published papers on pro-environmental travel behaviour between 2000 and 2021 1 0 0 1 0 0 2 1 3 1 2 4 5 11 10 9 12 30 31 42 46 40 0 5 10 15 20 25 30 35 40 45 50 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 snoit acil bupf or eb mu N Year VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 5

The collaboration network of pro-environmental travel behaviour Country collaboration network. The country collaboration network consists of 47 countries and 85 links between 2000 and 2021, which is showed in Figure 3. Based on the close links, different countries have established relatively a more matured collaboration network. The coloured lines indicate that Germany, Norway, Netherlands and Belgium have had a close collaboration in recent years. England, the USA, China, Australia and Canada accounted for half of the publications. The top ten countries based on frequency are shown in Table 2. England has the largest contribution with 40 articles and the highest centrality (0.76), and the USA is the second contributor with 28 articles. It is worth noting that China is the third contributor with 21 articles, which reflects the rapid development in tourism and the sustainable tourism development policy of China (Xu and Sofield, 2016). The tourism industry plays a significant role in mobilizing economic growth in China (Xu and Sofield, 2016). Additionally, Australia and New Zealand are referred as at-risk tourism destinations because of the climate change (Fang et al., 2018), which motivated many researchers to investigate this field. Institution collaboration network. There are 213 nodes and 174 lines in the institution collaboration network between 2000 and 2021, which is shown in Figure 4. It is worth noting that the collaboration between institutions is relatively loose. The research institutions have formed a cooperative network dominated by small groups, but not a large and close cooperative network. Therefore, it can be viewed as the research community is not mature yet. However, based on the colour of the links, the Hasselt University and Katholieke University have a close collaboration network in recent years. Top ten institutions with the highest number of publications are showed in Table 3. The Sejong University of South Korea has the highest number of publications (i.e. nine articles), and the University of Surrey, which is located in England, has the second highest publications (i.e. six articles). The Hasselt University of England and Dong A University which are based in South Korea both have published five articles, respectively. On the other hand, Norwegian University Science and Technology, Tianjin University, Griffith University and Lunds University published four articles, respectively. The University of Queensland and University Exeter published three articles each. Figure 2 Annual article output in the ten subject categories 0 2 4 6 8 10 12 14 16 18 snoit acil bupf or eb mu N Year Hospitality Leisure Sport Tourism Environmental Studies Green Sustainable Science Technology Transportation Environmental Sciences Transportation Science Technology Management Psychology Multidisciplinary Engineering Environmental Economics PAGE 6 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

Author collaboration network. There are 269 authors and 255 collaboration links found for PETB research that are published between 2000 and 2021, which is presented in Figure 5. However, the collaboration network seems fragmented, and only few authors exhibit having a close collaboration. Name of the top ten authors based on the number of publications are showed in Table 4. Heesup Han from Sejong University has the most contribution in this field with eight published articles followed by Alexander Yuriev from Concordia University and Arora Arnadottir from the University of Iceland who has published three articles in this field, respectively. Rest of the Figure 3 Country collaboration network Table 2 Top ten countries based on frequency Country Frequency Centrality England 40 0.76 USA 28 0.18 China 21 0.12 Australia 15 0.25 Canada 14 0.13 Norway 14 0.12 Sweden 13 0.01 South Korea 11 0.21 Germany 10 0.08 Netherlands 8 0.16 Note(s): Centrality: a metric of a node measures how likely an arbitrary shortest path in a network will go through the node, which shows the contribution of a node to make connections with other nodes in a network VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 7

authors in this top ten list published two articles each whereas others published only one article, respectively. Since PETB is an emerging research topic, most scholars are relatively new in this field and many of them are currently doing research on this topic. The co-citation network of pro-environmental travel behaviour Document co-citation network. In regard to the document co-citation network, there are 476 references and 1,431 co-citation links found between 2000 and 2021, which are shown in Figure 6. Indexing terms and log-likelihood ratio (LLR) were used to label the clusters. LLR is one of the algorithms, which is used to extract cluster labels at different locations in the cited literature (Fang et al., 2018), which is widely used and recommended. In the document co-citation network, the silhouette score is all above 0.8, which indicates that the clusters have reliable quality. The top 20 Figure 4 Institution collaboration network Table 3 Top ten institutions based on frequency Institution Country Frequency Sejong University South Korea 9 University of Surrey England 6 Hasselt University Belgium 5 Dong A University South Korea 5 Norwegian University Science and Technology Norway 4 Tianjin University China 4 Griffith University Australia 4 Lunds University Sweden 4 The University of Queensland Australia 3 University Exeter England 3 PAGE 8 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

clusters are shown in Table 5. Pro-environmental norm is the largest cluster with 57 member references, followed by towel reuse, sustainable lifestyles, pro-environmental attitudes, biospheric values and so on. In respect to the mean cite year, most of the clusters are new clusters in recent years, in which #14 pro-environmental behavioural intentions were found to be the latest cluster (mean cite year is 2017), which indicates to be the research hotspot. Liu et al. (2017) studied the low-carbon travel intention of residents of Tianjin and found that the low-carbon travel policy and low-carbon awareness can moderate low-carbon travel intention between TPB variables and VBN variables. Hu et al. (2019) studied tourists’ intention to take part in the activity named “zero litter initiative” in Huangshan National Park, which is located in China to protect its scenic environment. Their study Figure 5 Author collaboration network Table 4 Top ten authors based on frequency of publications Author Frequency Institution Heesup Han 8 Sejong University Alexander Yuriev 3 Concordia University Arora Arnadottir 3 University of Iceland Satoshi Fujll 2 Kyoto University Elhadi M Shakshuki 2 Acadia University Shoufeng Ma 2 Tianjin University Sunghyup Sean Hyun 2 Hanyang University Torbjorn Rundmo 2 Norwegian University of Science and Technology Shiraz Ahmed 2 Hasselt University Jukka Heinonen 2 University of Iceland VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 9

Figure 6 Document co-citation network Table 5 Summary of top 20 clusters Cluster ID Size Silhouette score Label (LLR) Mean (cite year) 0 57 0.829 Pro-environmental norms 2016 1 34 0.979 Interpretation 2012 2 29 0.956 Towel reuse 2012 3 26 0.954 Sustainable lifestyles 2008 4 26 1 Pro-environmental attitudes 1996 5 24 0.937 Biospheric values 2016 6 24 0.989 International travel 2008 7 22 0.971 Norms 2013 8 18 0.994 Hybrid choice models 2010 9 16 0.966 Electric bicycles 2003 10 16 1 Greenhouse gases 2009 11 16 1 Theory of planned behaviour 2004 12 15 1 Demographic characteristics 2001 13 12 1 Psychological 2004 14 11 1 Pro-environmental behavioural intentions 2017 15 11 0.989 Choice architecture 2015 16 10 0.964 Carbon offsetting 2012 17 9 0.958 Downshifting 2006 18 7 1 Environmental concern 2015 19 6 1 Destination images 2012 PAGE 10 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

found that lower ticket prices can increase the willingness of tourists to take part in the initiative. Likewise, Kiatkawsin and Han (2017) studied young travellers’ intention to behave proenvironmentally. They combined VBN theory and the expectancy theory to conceptualize their research framework. The result showed that their model has better predictive power, and the expectancy theory positively influences pro-environmental personal norms. In another study, Wu et al. (2021) divided pro-environmental travel intention into two: low-effort and high-effort. They considered social influence as a moderator variable between moral obligation and proenvironmental behaviour. Based on the output provided in Table 5, #4 pro-environmental attitude is a saturated and comparatively old phenomenon. The most used theory in studying PETB is found to be TPB (#11), which has the highest frequency of use in analysing tourists’ behaviour (Adnan et al., 2019; Bae and Chang, 2021; Esfandiar et al., 2020; Hu et al., 2019; Liu et al., 2017, 2020). The most cited articles are often considered milestone research due to their seminal contributions (Chen, 2006). Top ten most-cited papers are shown in Table 6; all of them are cited more than six times. Han’s (2015) paper has the highest citations (19 times cited). As mentioned before, Han also has the most publications on PETB. In this article, he focused on the green lodging context. He developed a comprehensive framework to investigate tourists’ pro-environmental intentions in the green lodging context using VBN theory and the TPB. The results showed that awareness of consequences and the normative process have an important role in generating intention, and nongreen alternatives’ attractiveness posed a strong moderating effect. Chen and Tung’s (2014) research is second highly cited paper. They confirmed that environmental concern can influence visitors’ perceived moral obligation, attitude, subjective norms and perceived behaviour control, which in turn influences the intention of visiting the green hotels. On the other hand, Klockner € ’s (2013) paper is the third highly cited research, who developed a model to understand individuals’ psychology of environmental behaviour using meta-analysis. Author co-citation network. There are 477 authors and 2,379 collaboration links in the author cocitation network, which is shown in Figure 7. There is a close co-citation relationship between scholars. It should be noted that only the first author in an article is considered in this analysis. Top ten most-cited scholars are shown in Table 7. The scholars who developed theory had a high co-citation frequency. For instance, Ajzen is the most-cited author with 98 citations and also has the most centrality (0.42) that is referred as to the metric of the transformative potential of a scientific contribution. He is a Professor in Psychology at the University of Massachusetts Amherst. His work on the TPB has a huge influence in the PETB field and has obtained impressive number of citations. This result is in accordance with the analysis of document co-citation network that the TPB is the most commonly used theory by the scholars in PETB research. Bamberg, a Professor of Social Psychology from the University of Applied Science Bielefeld, analysed psycho-social determinants of pro-environmental behaviour which is found to be the second highly cited author. Han’s name Table 6 Top ten most-cited papers with co-citation network Citation counts References Cluster 19 Han (2015) 0 9 Chen and Tung (2014) 0 8 Klockner (2013) € 8 8 Alcock et al. (2017) 6 8 Onwezen et al. (2013) 0 8 Kiatkawsin and Han (2017) 0 7 Lind et al. (2015) 0 6 Blok et al. (2015) 5 6 Fornara et al. (2016) 0 6 Truelove et al. (2014) 1 VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 11

and his publications appear in both Table 6 (most cited papers) and Table 4 (top ten authors), which further confirms his contribution to PETB research. Journal co-citation network. Journal co-citation network represents the set of journals that contribute to a specific research area. In regard to the PETB, the most contributing journals over the period of last 21 years are shown in Figure 8. A total of 452 journals were found, and the top ten most-cited journals are shown in Table 8. The co-citation frequencies of the top ten journals are more than 70. The Journal of Environmental Psychology is the most contributing journal with 141 co-citations, followed by Environment and Behaviour with 123 co-citation frequencies. The majority of the journals focus on tourism, environment and psychology. Table 9 shows the most prolific journals in PETB research. Journal of Sustainable Tourism is the leading journal in this field with 26 articles published between 2000 and 2021. The second most Figure 7 Author co-citation network Table 7 Top ten most-cited authors with co-citation frequency Authors Frequency Centrality Icek Ajzen 98 0.42 Sebastian Bamberg 81 0.11 Linda Steg 77 0.10 Paul C. Stern 69 0.09 Shalom H. Schwartz 53 0.04 Christian Klockner 47 0.04 John Thogersen 44 0.07 Heesup Han 38 0.13 Stewart Barr 34 0.16 PAGE 12 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

prolific journal is Sustainability (15), followed by Tourism Management (9), Transportation Research Part D Transport and Environment (8) and Journal of Cleaner Production (7). It should be noted that, Table 8 shows the high frequency of citations of the contributing journals to the PETB filed, Figure 8 Journal co-citation network Table 8 Top ten most-cited journals with co-citation frequency Journal name Frequency Centrality Impact factor Journal of Environmental Psychology 141 0.03 5.192 Environment and Behaviour 123 0.13 6.222 Journal of Social issues 83 0.05 3.424 Organization Behavior and Human Decision Processes 80 0.03 4.941 Journal of Applied Social Psychology 76 0.05 2.122 Journal of sustainable tourism 74 0.01 7.968 Transportation Research Part A-Policy and Practice 71 0.02 5.594 Tourism Management 70 0.05 10.967 Journal of Transport Geography 70 0.06 4.986 Table 9 Top ten most prolific journals Journal Publication number Impact factor Journal of Sustainable Tourism 26 7.968 Sustainability 15 3.251 Tourism Management 9 10.967 Transportation Research Part D Transport and Environment 8 5.495 Journal of Cleaner Production 7 9.297 Frontiers In Psychology 6 2.99 Transportation 6 5.192 Transportation Research Part F Traffic Psychology and Behavior 6 3.261 Transportation Research Part A Policy and Practice 5 5.594 VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 13

whereas Table 9 highlights the journals with high impact factors that published papers related to PETB. It is commonly believed that the journals with high impact factors may have higher citation frequencies (Fang et al., 2018). Emerging trends of pro-environmental travel behaviour References with highest number of citations. When an article receives a rapid citation in a short term, it forms a citation burst, which can partly show the research dynamics in a specific field (Fang et al., 2018). Although PETB is an emerging topic, some articles received very high number of citations as shown in Table 10. Based on the output showed in this table, the first wave of the citation burst started between 2011 and 2012, and the second wave of the citation burst appeared between 2015 and 2018, which is in accordance with the publication curve that is discussed in the previous section. The first citation burst is research about exploring the changing nature of sustainable lifestyles, the relationship between home-based environmental practices and tourismbased environmental practices by Barr et al. (2010). Keywords analysis. The analysis of keywords can reflect the development trends of the topic. It also assists to understand the future research directions by highlighting the research hotspots, i.e. highly prioritized topics in the field. The time zone of PETB is shown in Figure 9, and the top ten keywords are shown in Table 11 based on the frequency. Keywords with the same meaning were merged and those with no meaning were eliminated. It is found that pro-environmental behaviour is the most common keyword with 112 frequencies, which appeared as a keyword in 2006. Although some scholars attempted to study PETB, it was not a keyword used by scholars before 2006. The keyword PETB was followed by attitude (48), planned behaviour (44), climate change (28), intention (27), habit (21) and the like. The keywords related to the behaviour of travellers have high frequencies. The keyword planned behaviour belongs to the TPB, which is the most commonly used theory by scholars in this field, which is in Table 10 Top ten references with the highest number of citations References Strength Begin End 2000-2021 Barr et al. (2010) 2.66 2011 2014 Shove (2010) 2.26 2012 2014 Abrahamse et al. (2009) 2.26 2012 2014 Ramkissoon et al. (2013) 2.05 2015 2017 Miao and Wei (2013) 2.05 2015 2017 3.13 2016 2018 Onwezen et al. (2013) 3.51 2017 2018 Han (2015) 2.84 2017 2021 Chen and Tung (2014) 3.76 2018 2019 Donald et al. (2014) 2.07 2018 2019 Klöckner (2013) PAGE 14 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

accordance with the analysis of the previous section. Since the keywords “attitude” and “intention” are part of the TPB, they also exhibit high frequencies. Not surprisingly, climate change is highly related to PETB. The negative effect of the tourism activities on climate change has been subject to many studies (Ahmed et al., 2020; Fang et al., 2018; Hares et al., 2010). It is suggested that 5% of global carbon dioxide emissions are produced by tourism activities, in which transport sector contributes more than 90% of carbon emission (Gossling, 2002 € ). It clearly indicates that, travellers’ pro-environmental behaviours are greatly related to climate change. The choice of transportation and frequencies of travel can directly influence greenhouse gas emissions. In 2007, climate change was regarded as the most serious threat to the sustainability of tourism in the Second International Conference on Climate Change and Tourism (Fang et al., 2018). Since then, researchers started to put significant efforts in addressing the issue related to PETB. Based on the keywords analysis, car use, air travel and the use of transportation are found as some of the topics in PETB research. Perhaps this is due to the fact that transportation is the major source of air pollution. Klockner and Bl € obaum (2010) € built an action determination model to further study ecological behaviour using the example of travel mode choice. Car choice habit was chosen as the habitual processes in their study, and the results showed that habit mediates the link between social influence and personal norm; it also moderates the relationship between intention Figure 9 Time zone view of keywords Table 11 Top ten keywords based on frequencies Keyword Frequency Centrality Pro-environmental behaviour 112 0.14 Attitude 48 0.28 Planned behaviour 44 0.32 Climate change 28 0.2 Intention 27 0.06 Habit 21 0.15 Travel 19 0.02 Impact 17 0.08 Value 17 0.11 Determinant 17 0.09 VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 15

and behaviour. Geng et al. (2017) studied the types of motivations on urban residents’ travel mode. The results showed that pro-environmental motivation significantly promote the choice of green travel mode choice, such as bicycling, walking and public transportation. Kaida and Kaida (2015) confirmed the existence of the spillover effect of congestion charging on pro-environmental behaviour for people who shifted travel mode from car to more pro-environmental mode. It should be noted that some new keywords can easily be overlooked since those keywords are relatively new and appear less frequently. Therefore, Table 12 shows the new keywords which appeared repeatedly in the past two years, which can further present the research hotspots in PETB research. “COVID-19” is a new keyword that appeared in 2021 because of the outbreak of COVID-19. The “tourism and leisure” industry is one of the most threatened global industries, which is affected by the pandemic (Abbas et al., 2021). COVID-19 did not only affect the economy but also affected tourists’ behaviour and mental health (Abbas et al., 2021; Bauer et al., 2021). With the ongoing pandemic, more scholars started to investigate the effects of COVID-19 on PETB. For instance, O’Connor and Assaker (2021) refined and expanded the COVID-19 risk perception measure, which combined norm activation, economic sacrifices and risk perception theories. The results showed that the risk perception of COVID-19 indirectly influences pro-environmental behaviour through environmental concern, environmental responsibility and environmental moral obligation. Willingness to make economic sacrifices for the environment is found to be a new variable which directly influences PETB. It also acts as a mediator between risk perception of COVID-19 and PETB. However, this study did not investigate the mechanism of how the COVID-19 risk perception can be formed and did not consider the external factors that may influence PETBs. Chi et al. (2021) studied the festival travellers’ intention for practicing sanitation activities and keeping social distance during COVID-19 in the Chinese context. Their study revealed that problem awareness of COVID-19 can positively influence the ascription of responsibility indirectly and eventually evoke the sense of obligation to consider prosocial behaviours. The sense of obligation is likely to influence the intention to practice sanitation activities. Although some scholars have studied the effect of COVID-19 on pro-environmental behaviour, there are many aspects yet to unveil. More variables should be considered, and different underpinning theories should be regarded to understand the issue better. Besides, the value orientation, negative spillover, carbon footprints affect, biospheric and adolescent are all new keywords in recent years. These keywords probably can be regarded as the future research hotspots in PETB field. Discussion and future research directions In this study, the CiteSpace analysis outputs provide the bibliographic records on PETB research. It presents a unique and interesting picture of the PETB knowledge domain. The analysis suggests that PETB is an emerging research topic. Nevertheless, there is an increasing trend among researchers investigating this issue, and the number of publications has increased rapidly in recent years. Different countries have close collaboration in PETB. England has the largest contribution with 40 published articles, and the USA is the second contributor with 28 articles. Likewise, China, Australia, Canada, Norway, Sweden, South Korea and Germany all have contributed to this field. Table 12 Repeated keywords in the past two years Keywords Frequency Year Covid-19 2 2021 Value orientation 2 2020 Negative spillover 2 2020 Carbon footprint affect 2 2020 Biospheric 2 2020 Adolescent 2 2020 PAGE 16 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

Nevertheless, the collaboration network of authors and institutions both have a loose structure, and most notes are not connected, which indicates that only a part of the authors and institutions have a close collaboration. It means that the academic collaboration between scholars and institutions is not matured on this topic. As such, in the future, more academic conferences or international academic exchanges on PETB can be organized to enhance the collaboration among researchers and institutions. The analysis suggests that Heesup Han from Sejong University has the most contribution in this field with eight published articles. Alexander Yuriev from Concordia University and Arora Arnadottir from the University of Iceland published three articles, respectively, in this field. It is worth noticing that Hasselt University and Katholieke University have had a close collaboration network in recent years. In the analysis of the document co-citation network, #0 Pro-environmental norms is found to be the largest cluster with 57 member references, followed by towel reuse, sustainable lifestyles, proenvironmental attitudes, biospheric values and so on. In the analysis of author co-citation, Ajzen who developed the TPB has received the highest number of citations. And the TPB is the most common theory used by scholars in PETB research. Based on the journal co-citation analysis, Journal of Environmental Psychology and Environmental and behaviour are the leading journals in this field. Basically, the majority of the journals are based in tourism, environment, and psychology. Future researchers who are interested to work on PETB in the future may look at the analysis of citation burst and keywords. It is found that pro-environmental behaviour is the most common keyword with 112 frequencies, followed by attitude (48), planned behaviour (44), climate change (28), intention (27) and habit (21), which can be considered as the research hotspots in this field. Psychological variables such as planned behaviour, intention and habit all have huge research potential. Due to the global concerns on natural calamity and environmental pollution, “environmental problem” is a great research area at present and also in the future. Climate change is another hotspot since PETB can contribute to reduce the greenhouse gas emissions. Moreover, COVID-19 is a new keyword that came up in 2021 due to the outbreak of COVID-19. With the ongoing pandemic, more scholars started to study the effects of COVID-19 on PETB. Besides, some new keywords are probably the future research spots in PETB field, such as value orientation, biospheric value orientation, negative spillover, carbon footprints affect (Whitmarsh et al., 2020) and adolescent (Balunde_ et al., 2020). Whitmarsh et al. (2020) studied climate scientists’ carbon footprints, which can be replicated to examine other individuals’ carbon footprints such as bankers, educators, travellers, etc. Balunde_ et al. (2020) studied the relationship between adolescents’ environmental concern and their proenvironmental behaviour. Studies to understand adolescents’ pro-environmental behaviour are scant, although children also take part in the tourism activities and play significant role to mitigate climate change. Therefore, understanding adolescents’ pro-environmental behaviour can be a good future research direction. Conclusion, implications and limitations Using CiteSpace, this study provides a holistic and comprehensive knowledge mapping in PETB for academics. This study not only helps scholars to understand the definition of PETB, collaboration network, co-citation network and emerging trends but also visually displays the knowledge for the interested researchers. It will help scholars to see the research status of the past and will enable them to have a general understanding of the future research trend. The results also suggest that researchers need to improve their collaboration with each other, especially in transnational and interdisciplinary research. Furthermore, this study can help interested scholars to improve their research efficiency and save research time. The most contributing scholars and institutions are highlighted in this study, which can help scholars find the proper partners to conduct future studies in the field. The most cited journals can serve as the suitable literature source and publication platforms for the scholars. Moreover, this study illustrates that PETB is a potential research area for scholars. Psychological variables and environment problem are currently the focus of scholars, which have great value in VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 17

the future, such as attitude, planned behaviour, climate change, intention and habit. This study also suggests potential research directions to combine research topics such as COVID-19, value orientation, negative spillover, carbon footprints affect, biospheric value and adolescents, all of which are found to be the latest keywords in the present literature. This study considered only “pro-environmental travel behaviour” as the search keyword. Future studies can expand the research scope by adding more keyword, such as sustainable travel behaviour. It should be noted that the logic of research cannot be fully analysed by bibliometric software such as the relationship between variables. Therefore, a systematic literature review or metaanalysis should be carried out to summarize the existing literature in the field. Lastly, different paradigms, metrics and methods are suggested to be used to explore and explain the notion of PETB by future scholars. References Abbas, J., Mubeen, R., Iorember, P.T., Raza, S. and Mamirkulova, G. (2021), “Exploring the impact of COVID-19 on tourism: transformational potential and implications for a sustainable recovery of the travel and leisure industry”, Current Research in Behavioral Sciences, Vol. 2, p. 100033. Abrahamse, W., Steg, L., Gifford, R. and Vlek, C. (2009), “Factors influencing car use for commuting and the intention to reduce it: a question of self-interest or morality?”, Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 12 No. 4, pp. 317-324. Adnan, M., Ahmed, S., Shakshuki, E.M. and Yasar, A.-U.-H. (2019), “Determinants of pro-environmental activity-travel behavior using GPS-based application and SEM approach”, in Shakshuki, E., Yasar, A. and Malik, H. (Eds), 10th Int Conf on Emerging Ubiquitous Syst and Pervas Networks (Euspn-2019)/the 9th Int Conf on Current and Future Trends of Informat and Commun Technologies in Healthcare (Icth-2019)/ Affiliated Workops, Vol. 160, pp. 109-117. Ahmed, S., Adnan, M., Janssens, D. and Wets, G. (2020), “A personalized mobility based intervention to promote pro-environmental travel behavior”, Sustainable Cities and Society, Vol. 62, p. 102397. Alcock, I., White, M.P., Taylor, T., Coldwell, D.F., Gribble, M.O., Evans, K.L., Corner, A., Vardoulakis, S. and Fleming, L.E. (2017), “‘Green’ on the ground but not in the air: pro-environmental attitudes are related to household behaviours but not discretionary air travel”, Global Environmental Change, Vol. 42, pp. 136-147. Azam, M., Mahmudul Alam, M. and Haroon Hafeez, M. (2018), “Effect of tourism on environmental pollution: further evidence from Malaysia, Singapore and Thailand”, Journal of Cleaner Production, Vol. 190, pp. 330-338. Bae, S.Y. and Chang, P.-J. (2021), “The effect of coronavirus disease-19 (COVID-19) risk perception on behavioural intention towards ‘untact’ tourism in South Korea during the first wave of the pandemic (March 2020)”, Current Issues in Tourism, Vol. 24 No. 7, pp. 1017-1035. Balunde, A., Perlaviciute, G. and Truskauskait _ e-Kunevi _ cien  e, I. (2020), _ “Sustainability in youth: environmental considerations in adolescence and their relationship to pro-environmental behavior”, Frontiers in Psychology, Vol. 11, p. 582920. Barr, S., Shaw, G., Coles, T. and Prillwitz, J. (2010), “‘A holiday is a holiday’: practicing sustainability, home and away”, Journal of Transport Geography, Vol. 18 No. 3, pp. 474-481. Bauer, A., Garman, E., McDaid, D., Avendano, M., Hessel, P., D
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“Use of aviation by climate change researchers: structural influences, personal attitudes, and information provision”, Global Environmental Change, Vol. 65, p. 102184. Wu, G., Hong, J. and Thakuriah, P. (2019), “Assessing the relationships between young adults’ travel and use of the internet over time”, Transportation Research Part A: Policy and Practice, Vol. 125, pp. 8-19. Wu, J., Snow), Font, X. and Liu, J. (2021), “Tourists’ pro-environmental behaviours: moral obligation or disengagement?”, Journal of Travel Research, Vol. 60 No. 4, pp. 735-748. Xu, H. and Sofield, T. (2016), “Sustainability in Chinese development tourism policies”, Current Issues in Tourism, Vol. 19 No. 13, pp. 1337-1355. Yang, Y., Cao, M., Cheng, L., Zhai, K., Zhao, X. and De Vos, J. (2021), “Exploring the relationship between the COVID-19 pandemic and changes in travel behaviour: a qualitative study”, Transportation Research Interdisciplinary Perspectives, Vol. 11, p. 100450. Further reading Cui, Y., Mou, J. and Liu, Y. (2017), “Bibliometric and visualized analysis of research on e-commerce journals”, Proceedings of the International Conference on Electronic Commerce, pp. 1-7. Doran, R. and Larsen, S. (2016), “The relative importance of social and personal norms in explaining intentions to choose eco-friendly travel options”, International Journal of Tourism Research, Vol. 18 No. 2, pp. 159-166. Dryhurst, S., Schneider, C.R., Kerr, J., Freeman, A.L.J., Recchia, G., van der Bles, A.M., Spiegelhalter, D. and van der Linden, S. (2020), “Risk perceptions of COVID-19 around the world”, Journal of Risk Research, Vol. 23 Nos 7-8, pp. 994-1006. Holden, A. (2009), “The environment-tourism nexus: influence of Market ethics”, Annals of Tourism Research, Vol. 36 No. 3, pp. 373-389. Mi, L., Zhao, J., Xu, T., Yang, H., Lv, T., Shang, K., Qiao, Y. and Zhang, Z. (2021), “How does COVID-19 emergency cognition influence public pro-environmental behavioral intentions? An affective event perspective”, Resources, Conservation and Recycling, Vol. 168, p. 105467. Zhao, Y., Liu, B., Zhao, Y. and Liu, B. (2020), “The evolution and new trends of China’s tourism industry”, National Accounting Review, Vol. 2 No. 4, pp. 337-353. About the authors Jiale Zhang is a doctoral student at Azman Hashim International Business School, Universiti Teknologi Malaysia. His research focus is pro-environmental behavior, green marketing and tourism marketing. Jiale Zhang is the corresponding author and can be contacted at: [email protected] Farzana Quoquab (Dr) is an Associate Professor of Marketing at Azman Hashim International Business School, UTM. Since 2014, she has been actively working on the issues of green and sustainability marketing. Her works have appeared in high-impact publications such as Asia Pacific VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 21

Journal of Marketing and Logistics, Journal of Electronic Commerce Research, Internet Research, Employee Relations: The International Journal, SAGE Open, Personnel Review, Cross Cultural and Strategic Management, Journal of Fashion Marketing and Management and Journal of Product and Brand Management. She is also a prolific case writer. Dr. Farzana is one of the Associate Editors of “Emerald Emerging Market Case Studies” and Editor-in-Chief of “International Journal of Innovation and Business Strategies”. She has successfully served as a guest editor for the reputed journals like Young Consumers (Emerald) and Journal of Global Marketing (Routledge Publishing). She is also a member of Editorial Advisory/Review Board of several internationally reputed journals. For instructions on how to order reprints of this article, please visit our website: www.emeraldgrouppublishing.com/licensing/reprints.htm Or contact us for further details: [email protected] PAGE 22 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

Future strategies for tourism destination management: post COVID-19 lessons observed from Borobudur, Indonesia Jasper Hessel Heslinga, Mohamad Yusuf, Janianton Damanik and Menno Stokman Abstract Purpose – The purpose of this viewpoint paper is to show practical post COVID-19 observations as lessons for the future of tourism destination management and help inspire the tourism industry and academic community. Design/methodology/approach – This paper is based on observations by, and discussions among, both international and Indonesian tourism experts and relate to the case of the famous UNESCO World heritage site, the Borobudur temple, in Indonesia. Findings – As a result, the authors observed the following measures that have been taken by the local authorities; setting limits to the amount of visitors, increase the visitor area, provide guided tours only, work with price mechanism, mitigate the physical impacts of visits and involve the local community in the value chain. The paper shows that the COVID pandemic has unintentionally created urgency and an opportunity for the local authorities to deal with already ongoing and structural overtourism related issues. This demonstrated that a lockdown was needed to get out of a lock-in. Originality/value – This paper fits in the ongoing debate on the effects of COVID-19 pandemic on the tourism sector. As it provides a practical case, the values of this paper lie in bridging the gap between conceptual contributions to the debate and practical observations. Also many links with the continuation of the overtourism debate are made. Keywords Future policy, Post-pandemic tourism, Tourism management, UNESCO World Heritage, Overtourism, COVID-19 Paper type Viewpoint Introduction What does the future of tourism management look like after COVID-19? Are we striving for business-as-usual, or will it be business-as-unusual (Heslinga et al., 2020; Postma et al., 2020, 2023; Yeoman et al., 2022)?. The COVID-19 pandemic has had an immense impact on the global leisure, tourism and hospitality sector (van Leeuwen et al., 2020). Especially in those destinations that are dependent on international travel the impact has been severe, as borders have been closed for a long time and the recovery of international tourism arrivals is still not back on the levels pre COVID-19. Despite crisis impacting the sector, some considered the pandemic to be a wakeup call and as an opportunity to rethink tourism. As Winston Churchill was working to form the United Nations after Second World War, he famously said, “Never let a good crisis go to waste”. In another context, that of tourism recovery after COVID-19, this reflects the using of a crisis as an opportunity to bounce forward, and thereby build tourism destinations back better and not bounce back to the initial situation running into the same potential problems. Many publications have been produced the past three years about the impacts of COVID-19 on the tourism and hospitality sector and whether this is a game changer or not (Cheer et al., 2021; Lew (Information about the authors can be found at the end of this article.) Received 15 June 2023 Revised 24 June 2023 Accepted 8 August 2023 © Jasper Hessel Heslinga, Mohamad Yusuf, Janianton Damanik and Menno Stokman. Published in Journal of Tourism Futures. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http:// creativecommons.org/licences/ by/4.0/legalcode Since acceptance of this article, the following author(s) have updated their affiliation(s): Jasper Hessel Heslinga is at the Centre of Expertise Leisure and Hospitality (CELTH), Breda, Netherlands. DOI 10.1108/JTF-06-2023-0144 VOL. ▪▪▪ NO. ▪▪▪ , pp. 1-7, Emerald Publishing Limited, ISSN 2055-5911 j JOURNAL OF TOURISM FUTURES j PAGE 1

et al., 2020; Papp et al., 2023; Tomassini et al., 2021; Yeoman, 2023). Given that the COVID pandemic is quite a recent phenomenon affecting tourism, most of these papers remain conceptual show scenarios, visions and potential outlooks. Not surprisingly the translation into a practical setting remains still under researched. With this paper, we try to bridge this gap by showing practical observations of bold changes that were made at the Borobudur Temple close to Yogyakarta, Indonesia. The purpose of this viewpoint paper is to use these observations as input to rethink the future of tourism management. Why looking the Borobudur? This iconic temple in Indonesia is one of biggest and most impressive Buddhist temples in the world, is one of the most well-known UNESCO World heritage sites in the world, and because of that, an enormous tourism magnet that attracts many visitors per year (Damanik and Yusuf, 2022). The increasing number of visitors has had major economic impacts, but it also has been creating overtourism related problems (Peeters et al., 2018). Crowding is, for example, a huge problem; the temple has been suffering from overcrowding as 10.000 visitors per day was not uncommon. For many visitors paying a visit to the Borobudur is on their bucket list. Apart from a bad visitor experience due to annoyance of the many other visitors, overcrowding also lead to physical damage to the holy temple. Of course there is the physical damage to the temple due to tourists that walking and some even climbing on the structure. Moreover, littering has become a big problem as cigarette buds are found everywhere and even chewing gum has been stuck on the temple by people in some places. These problems have been steadily increasing over the past years. The COVID pandemic and the lockdowns ensured that visitors were not coming anymore (Figure 1 shows Borobudur temple almost deserted) and gave the authorities some time to rethink the way Borobudur could be visited in a more sustainable way. This paper shows field observations from this particular case study to assess what has been done so far manage Borobudur better. Figure 1 Borobudur temple with very limited visitors PAGE 2 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

As a method, field observations were combined with group discussions and policy analysis. The observations are based on a fieldtrip taking place in October 2022 where tourism experts from the Netherlands and Indonesia gathered to visit the Borobudur area. Together they have been doing observations at the temple and have been engaging in discussions with the local authorities. To support these observations, the new policies that have been implemented were consulted. Rethinking tourism destination management using 5 observations from Borobudur temple, Indonesia Observation 1: set a limit The first observation is the installation of the regulation of the capacity of the visitors that can enter the temple. Before COVID-19 hit, it was not uncommon that 8,000–10,000 visitors per day would pay a visit to the temple. In the newly designed regulation, it says that only 1,200 visitors per day could enter. In addition, after the closure of the temple due to COVID-19 pandemic and for conservation purposes, visitors could not enter at all due to a special permit from the national government in Jakarta. However, there has been a new policy that allows tourists enter the temple limited to only 200 visitors, and it will gradually reach to maximum 1,200 visitors per day. The duration of visits is limited from 09.00 to 17.00. The restriction was made to maintain the carrying capacity of the temple based on recommendations of a study by the temple management authority, PT Taman Wisata Candi Borobudur. Setting a maximum number of visitors reflects the ideas behind thresholds in the Doughnut Destination (Hartman and Heslinga, 2023) and is something that is occurring in other destinations in the world (for example the city of Amsterdam). Observation 2: make “the cake” bigger Second, it was observed that the authorities invested in the idea of spreading visitors (UNWTO, 2018) across a larger space by making use of zoning and trying to get visitors away from “the honeypot”. In practice, this means that more attention was given to the buffer zones around the temple, ensuring that visitors are not coming for just one thing (the temple itself), but have a longer and better experience that they gives them more joy. For example, by launching the Borobudur Tourism Authority Board, the central government intended to immediately spread tourists from the center of the temple to outside Zone 5, the version designed by JICA in 1979. One of the new areas, in the form of a luxury camping area, was built about 15 km south of the temple ground. Access to this area is even easier thanks to its proximity to the land transportation route from the new international airport to the temple area via the 63 km long Menoreh hills. In addition, around 20 Village Economic Centers (Balai Ekonomi Desa/Balkondes) were developed. The Balkondes were created particularly to invite a bigger community participation to the tourism development in the villages surrounding the temple. Therefore, visitors will have diverse attractions in addition to the temple itself. For Borobudur to remain the primary destination brand and to attract visitors, a number of local and international events themed on music, sports and writing could be helpful in increasing the offer (and spread the visitor in time and place) and make the experience for visitors even better. Observation 3: provide guided tours only A third observation is that the Borobudur temple can only be visited with a guide, before it was possible to do this on an individual basis. Apart from guided tours lead to better and more responsible behaviour by the tourist, it also brings an educational element to the experience, as the guides will inform them about the culture and history behind the temple. This led to a better experience than only taking a selfie for the bucket list. In addition, the involvement of guides in visiting the temple is also a response from the temple authorities to the protests of local guides who cannot benefit from visitors to the temple. Therefore, visitors are required to use the services of a certified guide and are subject to a charge of around USD3.5 per person. This fee is only charged if VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 3

visitors go up to the temple platform. In addition, more signages informing do’s and don’ts for visitors are placed surrounding the temple. The management has informed that this is part of the way the visitors were educated and involved in the temple conservation. Observation 4: use the price mechanism Another observation was the increase of the price visitors need to pay as the entrance fee (UNWTO, 2018). Before COVID-19, the price for entranceticket rates differ based on the origin of tourists, where international tourists are charged an entry fee of USD25 for adults and USD15 for children whereas just about USD3.5 for the local visitors. This changed in 2022, when COVID-19 cases started to decrease, the government announced to increase ticket prices to USD100 for international visitors and USD50 for local visitors. This measure is, on the one hand, about using prices to find a new balance and has two effects; a higher price will discourage visitors to come and decrease visitor numbers, but at the same time a higher price increasesthe revenues that can be used for conservation and maintenance purposes. On the other hand, the price increase is not realistic in times when people want to make up for the deficit in tourist experience during COVID-19, and will form a new social segregation, that ‘only rich people can go to Borobudur temple’. Due to a huge protest coming from the tourism actors complaining about the decrease of visitors coming to the temple, the government is considering a new price mechanism, which is likely to be less than 46 USD. Observation 5: access with damage free footwear only The authorities have announced that the temple can only be accessed with a special type of shoe, namely Upanat. These Upanat are slippers made from pandan and are produced by local community in the temple area and is an actualization of the Karmawibhangga relief panel 150 of Borobudur Temple. Before the pandemic anyone could enter the temple leading to physical damage of visitors walking and climbing the temple. According to the analysis of the Borobudur Conservation Center, every year there has been physical depletion of the temple stones of 0.042 cm (Suhartono and Brahmantara, 2020). Therefore, urgent action was required to reduce more severe damage. With these new shoes, visitors can enter Borobudur, but it will do not any serious harm to the temple. Every visitor will receive their entrance ticket, including the Upanat shoe and brochure of the temple, which they can take home with them as a souvenir. Observation 6: involve the local community and take them seriously Finally, a cross-cutting observation is that when taking these bold measures, it is essential to involve the local community, in line with UNWTO’s policy recommendations to manage tourism growth, “stressing the integration of local communities in the tourism value chain to ensure that tourism translates into wealth creation and decent jobs” (UNWTO, 2018). It also seems important to do so throughout the entire process, from policymaking, the implementation and execution of measures. Initially there was a lack of sufficient involvement of the local community in the planning process, which led to criticism from the local population in choices about, among other things, the price increase. Gradually, involvement of the local inhabitants has been given a lot of scope in the new management setup of the site, for instance, by providing the guided tours concept and within the production of the Upanat shoe. Conclusion and future challenges These observations from Borobudur show that the authorities are taking the problem of overtourism and crowding very serious. These strategies for dealing with those problems are considered to be some bold measures. But are these strategies observed completely new? No, not really. Academics and practitioners have been discussing these for years now Koens et al. (2018), Peeters et al. (2018), UNWTO (2018). However, implementation in such a way that the measures are effectively solving the issues is often problematic (for many reasons). For many years, destinations have been in a certain PAGE 4 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

lock-in situation, where it was difficult to make big changes that could provide alternative paths of development steering away from overtourism related issues. This study showed that COVID-19 created the urgency and opportunity the get out of this lock-in (Wilson, 2014), by hitting pause and critically rethink how destinations can be managed differently. A lockdown was needed to get the areas out of a lock-in and alterthe course of development into a more sustainable one. This was a bold move from the authorities, as it takes guts to do this, but it in the long run, it will lead much more control than before. COVID-19 was unforeseen and unintentionally, but what destinations elsewhere in the world can learn from the Borobudur case is that destinations could intentionally and strategically build in a moment to “hit pause” and letting communities and landscapes recover and regenerate to enhance the destinations’ resilience (Heslinga, 2020, 2022). Although designing and implementing new policies is great, but that does not mean the job is done. In order to work more effectively, the Borobudur case also showed that there are some issues here that need attention for the coming future. These issues are not limited to the Borobudur case, but are relevant for any tourism destination worldwide that is in the process of redesigning their vision, policies and plans for tourism. 1. The involvement of local communities. In the process of designing the new measures, local communities were not fully consulted and involved. Many communities around the site are dependent on the visitors coming to Borobudur and the decrease of visitor numbers was not received well by everyone, as they might feel the risk of losing their business and jobs. 2. Change of jobs. These changes will very likely affect the type of jobs in and around Borobudur. With the management shift there will be a higher need for education programs that support the change of profession. Instead of street vendors selling souvenirs, there should be more focus on the education of tour guides that need to learn about culture, history and hospitality. A stronger focus on the site itself also means more jobs in maintenance and conservation. 3. Ethical dilemma about pricing of heritage. In times where accessibility, inclusiveness, fairness and equity are increasingly important discussion points in tourism, the questions should be raised whether increasing the price of heritage make a visit only possible for the elite and exclude those that cannot afford access to their heritage. 4. Destination governance. For the management of the Borobudur UNESCO Heritage site, there are multiple organizational bodies responsible. There are tourism, conservation and administrative units, but getting them constantly aligned remains a challenges. For better management of the destination, there should be more clarity on the roles and responsibilities each body has (Heslinga et al., 2019; Heslinga and Hartman, 2021). 5. Opportunities for VR. With the closure of some sensitive parts of the temple or the temple simply being too expensive to visit, there is a possibility in virtual reality to give visitors the best possible experience. At the moment, this has not yet been developed, but could be a potential new step. References Cheer, J.M., Lapointe, D., Mostafanezhad, M. and Jamal, T. (2021), “Global tourism in crisis: conceptual frameworks for research and practice”, Journal of Tourism Futures, Vol. 7 No. 3, pp. 278-294, doi: 10.1108/ JTF-09-2021-227. Damanik, J. and Yusuf, M. (2022), “Effects of perceived value, expectation, visitor management, and visitor satisfaction on revisit intention to Borobudur Temple, Indonesia”, Journal of Heritage Tourism, Vol. 17 No. 2, pp. 174-189, doi: 10.1080/1743873X.2021.1950164. Hartman, S. and Heslinga, J.H. (2023), “The Doughnut Destination: applying Kate Raworth’s Doughnut Economy perspective to rethink tourism destination management”, Journal of Tourism Futures, Vol. 9 No. 2, pp. 279-284. Heslinga, J.H. (2020), “Towards resilient regions: policy recommendations for synergy between tourism development and nature protection”, Land, Vol. 9 No. 2, p. 44, available at: https://www.mdpi.com/2073- 445X/9/2/44 VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 5

Heslinga, J.H. (2022), “Resilient destinations”, in Buhalis, D. (Ed.), Encyclopedia of Tourism Management and Marketing, Edward Elgar Publishing, Cheltenham. Heslinga, J.H. and Hartman, S. (2021), “Improving governance systems of national parks: how the instrument of a ‘governance scan’ can contribute”, Sustainability, Vol. 13 No. 19, 10811, available at: https:// www.mdpi.com/2071-1050/13/19/10811 Heslinga, J.H., Groote, P.D. and Vanclay, F. (2019), “Strengthening governance processes to improve benefit sharing from tourism in protected areas by using stakeholder analysis”, Journal of Sustainable Tourism, Vol. 27 No. 6, pp. 773-787, doi: 10.1080/09669582.2017.1408635. Heslinga, J.H., Postma, A. and Hartman, S. (2020), “De bezoekerseconomie na COVID-19? Scenarioplanning biedt lange termijn perspectieven voor de toekomt”, Vrije tijd studies, Vol. 38 No. 3, pp. 11-16. Koens, K., Postma, A. and Papp, B. (2018), “Is overtourism overused? Understanding the impact of tourism in a city context”, Sustainability, Vol. 10 No. 12, pp. 1-15. Lew, A.A., Cheer, J.M., Haywood, M., Brouder, P. and Salazar, N.B. (2020), “Visions of travel and tourism after the global COVID-19 transformation of 2020”, Tourism Geographies, Vol. 22 No. 3, pp. 455-466, doi: 10.1080/14616688.2020.1770326. Papp, B., Neelis, I. and Heslinga, J.H. (2023), “Don’t hate the players, hate the system! – The continuation of deep-rooted consumption patterns in the face of shock events”, Journal of Contemporary Hospitality, Vol. ahead-of-print No. ahead-of-print, doi: 10.1108/IJCHM-09-2022-1177. Peeters, P., Gossling, S., Klijs, J., Milano, C., Novelli, M., Dijkmans, C., Eijgelaar, E., Hartman, S., Heslinga, € J., Isaac, R., Mitas, O., Moretti, S., Nawijn, J., Papp, B. and Postma, A. (2018), Research for TRAN Committee - Overtourism: Impact and Possible Policy Responses, European Parliament, Policy Department for Structural and Cohesion Policies, Brussels. Postma, A., Heslinga, J.H. and Hartman, S. (2020), Four future perspectives of the visitors economy after COVID-19, Centre of Expertise Leisure, Tourism and Hospitality (CELTH), Breda. Postma, A., Heslinga, J.H. and Hartman, S. (2023), “Using scenario planning as a tool to futureproof the visitor economy after the COVID-19 ‘corona’ crisis”, in Innerhofer, H.P.E. (Ed.), From Overtourism to Sustainability Governance: A New Tourism Era, Taylor & Francis, London. Suhartono, Y. and Brahmantara (2020), “Pembatasan Kunjungan di Puncak Candi Borobudur (limits of visitor’s number on the Borobudur temple”, available at: https://kebudayaan.kemdikbud.go.id/bkborobudur/ wp-content/uploads/sites/12/2019/05/Rilis-Pers-Pembatasan-Kunjungan-di-Puncak-Candi-Borobudur.pdf Tomassini, L., Schreurs, L. and Cavagnaro, E. (2021), “Reconnecting the space of tourism and citizenship: the case of tourists’ hubris”, Journal of Tourism Futures, Vol. 7 No. 3, pp. 337-349, doi: 10.1108/JTF-10-2020-0176. UNWTO (2018), Overtourism? Understanding and Managing Urban Tourism Growth beyond Perceptions, UNWTO, Madrid. van Leeuwen, M., Klerks, Y., Bargeman, B., Heslinga, J.H. and Bastiaansen, M. (2020), “Leisure will not be locked down – insights on leisure and COVID-19 from The Netherlands”, World Leisure Organization, Vol. 62 No. 4, pp. 339-343, doi: 10.1080/16078055.2020.1825255. Wilson, G. (2014), “Community resilience: path dependency, lock-in effects and transitional ruptures”, Journal of Environmental Planning and Management, Vol. 57, doi: 10.1080/09640568.2012.741519. Yeoman, I.S. (2023), “Editorial: how COVID-19 changed the world of tourism research”, Journal of Tourism Futures, Vol. 9 No. 1, pp. 2-3, doi: 10.1108/JTF-03-2023-286. Yeoman, I.S., Postma, A. and Hartman, S. (2022), “Scenarios for New Zealand tourism: a COVID-19 response”, Journal of Tourism Futures, Vol. 8 No. 2, pp. 177-193, doi: 10.1108/JTF-07-2021-0180. Author affiliations Jasper Hessel Heslinga is based at the European Tourism Futures Institute (ETFI), NHL Stenden University of Applied Sciences, Leeuwarden, Netherlands. Mohamad Yusuf is based at the Department of Tourism Studies, Universitas Gadjah Mada, Yogyakarta, Indonesia. Janianton Damanik is based at the Center for Tourism Studies, Gadjah Mada University, Yogyakarta, Indonesia and Department of Social Development and Welfare, Gadjah Mada University, Yogyakarta, Indonesia. PAGE 6 j JOURNAL OF TOURISM FUTURESj VOL. ▪▪▪ NO. ▪▪▪

Menno Stokman is based at the Centre of Expertise Leisure and Hospitality (CELTH), Breda, Netherlands. Corresponding author Jasper Hessel Heslinga can be contacted at: [email protected] For instructions on how to order reprints of this article, please visit our website: www.emeraldgrouppublishing.com/licensing/reprints.htm Or contact us for further details: [email protected] VOL. ▪▪▪ NO. ▪▪▪ j JOURNAL OF TOURISM FUTURESj PAGE 7

Game of algorithms: ChatGPT implications for the future of tourism education and research Stanislav Ivanov and Mohammad Soliman Abstract Purpose – The paper aims to evaluate the ways ChatGPT is going to disrupt tourism education and research. Design/methodology/approach – This is a conceptual paper. Findings – ChatGPT has the potential to revolutionize tourism education and research because it can do what students and researchers should do, namely, generate text (assignments and research papers). Universities will need to reevaluate their teaching and assessment strategies and incorporate generative language models in teaching. Publishers will need to be more receptive toward manuscripts that are partially generated by artificial intelligence. In the future, digital teachers and research assistants will take over many of the cognitive tasks of tourism educators and researchers. Originality/value – To the authors’ best knowledge, this is one of the first academic papers that investigates the implications of ChatGPT to tourism education and research. Keywords ChatGPT, Tourism education, Tourism research, Intelligent automation, Large language models Paper type Viewpoint 1. Introduction ChatGPT was developed by the San Francisco-based OpenAI, a tech and research company, and made freely available at the end of November 2022 (Vanian, 2022). ChatGPT is a well-known generative artificial intelligence (AI) platform or application using the most recent version of GPT-4 (Generative Pretrained Transformer 4). According to Stokel-Walker (2023), ChatGPT can be described as a large language model (LLM) that creates convincing phrases by imitating the linguistic statistical patterns seen in a sizable body of literature gathered from the internet. With its ability to respond to a variety of themes and subjects, ChatGPT could be a helpful tool for chatbots, academia, customer support and a variety of other applications (Gilson et al., 2023). Consequently, the platform has gained a lot of attention from early adopters (e.g. students and scholars) and has even been termed a disruptive technology in a number of sectors (Haque et al., 2022), including academia and education. Once ChatGPT debuted, users were amazed at how it could generate material such as short stories and dialogs based on the user’s simple instructions (Topsakal and Topsakal, 2022). ChatGPT has a disruptive effect on the entire educational system and scientific research. Since its release, it has been utilized at numerous universities and colleges to write summaries, essays and even full theses, raising concerns about the validity of these works and the worth of academic degrees. In this regard, it starts to generate big concerns about the future of education and research among different disciplines and areas, involving tourism and hospitality. The main concern is associated with some aspects such as essay and assignment writing as well as the Stanislav Ivanov is based at the Varna University of Management, Varna, Bulgaria and Zangador Research Institute, Varna, Bulgaria. Mohammad Soliman is based at the University of Technology and Applied Sciences, Salalah, Oman and Fayoum University, Fayoum, Egypt. Received 12 February 2023 Revised 14 February 2023 Accepted 15 February 2023 © Stanislav Ivanov and Mohammad Soliman. Published in Journal of Tourism Futures. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and noncommercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/ licences/by/4.0/legalcode PAGE 214 j JOURNAL OF TOURISM FUTURES j VOL. 9 NO. 2 2023, pp. 214-221, Emerald Publishing Limited, ISSN 2055-5911 DOI 10.1108/JTF-02-2023-0038

quality and quantity of academic research (Stokel-Walker, 2023). On the other hand, ChatGPT has a number of advantages for education and research (e.g. Anders, 2022a) such as better equity as all students and/or researchers have more access to aid, personalization, critical thinking skills development (if the app is utilized properly), development of teacher and student AI literacy, and motivational enhancement. In addition, the world-sweeping ChatGPT has made its official debut in the scientific literature, earning at least four authorship credits on preprints and published works. The appropriateness of citing the ChatGPT as an author and the presence of such AI tools in the published literature are currently topics of discussion among journal editors, academics and publishers (Stokel-Walker, 2023). In this context, the current viewpoint looks at the implications of ChatGPT and the future similar LLM-based chatbots for tourism education and research. 2. ChatGPT implications for tourism education ChatGPT can be used as an effective tool in teaching and learning due to its ability to reject inappropriate requests, challenge inaccurate responses and keep track of what the user stated previously in the chat for follow-up queries. It communicates with the users in natural language, does not require coding skills and its interface is extremely easy to use (Haque et al., 2022). Thus, its incorporation in tourism and hospitality programs can be implemented without significant hurdles. Additionally, ChatGPT offers explanations, solutions and responses to challenging topics, including possible approaches to develop code, address optimization requests and resolve layout issues (Haque et al., 2022). In their study, Gilson et al. (2023) exhibited ChatGPT’s capacity to offer justification and background data for the vast majority of answers, presenting a strong argument and justification for ChatGPT’s potential use in medical education. Consequently, there are some practical guidelines and implications (see Anders, 2022a) to adopt ChatGPT in tourism education. For instructors, ChatGPT can serve as a virtual teaching assistant by giving students immediate feedback on a specific task. In addition, it can help them in preparing several exams and quiz versions, student learning assessments, syllabi, rubrics and so forth. Moreover, the application can be utilized as an assessor for students’ assignments and other virtual tasks. For students, ChatGPT can be used to ask questions to get clarification on a particular piece of the course material or to have explanations repeated or given in a different and new manner. In addition, if the app can swiftly produce a passable response to a prompt or assignment, students will be able to use their skills and knowledge more effectively to do the task (e.g. Anders, 2022b). There are some disadvantages of ChatGPT for tourism and hospitality education. First, the algorithm is trained with data up to 2021 and does not have access to real-time data. Hence, the answers it provides might be irrelevant, incorrect or simply outdated. Second, it might lack information about a particular query at all. Third, it does not provide references to the original sources of the texts used to generate the answer. Fourth, the authors’ experience with the tool shows that its answers are usually descriptive and lack sufficient depth and critical analysis. Therefore, students and lecturers should not put too much trust in the texts ChatGPT generates but rely on their expertise, other (academic) sources and common sense. ChatGPT’s capabilities in generating text challenge the assessment modes. A few universities have publicly announced any policy toward the application, but those who have done it explicitly forbid its use. Naturally, exceptions do exist because while ChatGPT can write students’ assignments and deprive them of learning some skills which they would have otherwise learned if they had written the assignments by themselves, ChatGPT allows students to gain other skills, especially digital skills that are vital for the tourism industry (Carlisle et al., 2021). For example, students need to break down their assignments into prompts for which ChatGPT can write 100–300 words of relevant text. Therefore, an assignment of about 3,000 words would be generated by over 20 prompts. By using ChatGPT in their assignments, students learn how to operationalize tasks and give precise instructions, that is, their planning and communication skills might increase. Of course, at this early stage of development and adoption of ChatGPT in education, it is difficult to speculate about the impacts of ChatGPT on assessments. In order to gain data and make an informed decision about the use of ChatGPT by students, Varna University of Management, Bulgaria, for VOL. 9 NO. 2 2023 j JOURNAL OF TOURISM FUTURESj PAGE 215

example, is testing its contribution to the learning experience of students and is currently allowing them to use it for writing assignments in a couple of modules only as long as the use of the application is explicitly stated in the assignment. The insights gained from this experiment will inform the future policy of the university toward the adoption of ChatGPT and similar tools by students. Other higher education institutions incorporate ChatGPT in their curricula as well and ask students to use the application in order to learn about the capabilities of AI. 3. ChatGPT implications for tourism research ChatGPT, in contrast to earlier chatbots, generates text automatically from typed inputs (Vanian, 2022). As a result, users (i.e. researchers) can input text instructions into the platform, and it will return text responses. To this end, scholars in tourism and hospitality can adopt this platform while conducting their scientific research. First, tourism researchers can use it to generate research ideas. As ChatGPT is trained on a vast amount of data from multiple disciplines, its output as research ideas could go beyond the narrow perspectives of individual researchers and inspire new studies. Second, it can be used by tourism researchers to write and review certain literature on a specific subject, formulate and develop hypotheses or advance the theoretical underpinnings of a certain discipline. Despite the application’s ability to gather significant and relevant information, however, in such cases, it can be argued that ChatGPT has advanced to the point where it is able to deceive academics by producing scientific studies that are indistinguishable from authentic publications. In addition, some users assert that one of the main challenges to utilizing the platform professionally is citation issue. In this regard, Gao et al. (2022) emphasized that while ChatGPT is capable of producing more correct information, its accuracy and integrity when used in scientific writing are unclear. In their work using the application, Gao et al. (2022) indicated that even though its scientific abstracts are entirely made up of generated data, ChatGPT writes them convincingly. Moreover, although there was no evidence of plagiarism, these were original, but they were frequently recognized by human reviewers who were dubious, and by an AI output detector. Moreover, ChatGPT can make up nonexistent sources. For instance, when asked by the authors of this viewpoint to provide references on robots in tourism, ChatGPT hallucinated and delivered the following made-up sources (see Figure 1), none of which actually exists. When asked to provide the links to the sources, ChatGPT redirected the authors to the academic databases. Third, ChatGPT could provide advice about the use of advanced statistical analysis or a particular methodology. It can also help researchers generate questions and respective scales to be included in questionnaires (see Figure 2). In that way, the application can be very useful to researchers because it will not only give them methodological ideas and insights, but it will save time as well. The lack of references, though, is a significant issue because there is no transparency about where the questions and scales come from, something that is a must in academic papers. Fourth, ChatGPT could reword texts and improve the writing style. This is especially beneficial to tourism and hospitality researchers who are not native English speakers. Naturally, caution is needed because the AI may produce texts with repeating patterns that, although grammatically correct, might be quite boring to readers. A major issue related to the use of ChatGPT in scientific research is the authorship and ethical considerations. Some researchers who are using ChatGPT to help write scientific publications even include it as a co-author (e.g. Ali and OpenAI, 2023), while the majority of authors do not do so (e.g. Iskender, 2023). Since AI platforms (e.g. ChatGPT) cannot be held accountable for the integrity and content of scientific publications, publishers agree that they do not meet the requirements for research authors. Some publishers, however, assert that acknowledging an AI’s role in helping to write a paper in places other than the author list is acceptable (see Stokel-Walker, 2023). Similar to other tools, such as statistical software, the use of AI needs to be mentioned in the methodology section of the paper. Some publishers may also require a dedicated explicit PAGE 216 j JOURNAL OF TOURISM FUTURESj VOL. 9 NO. 2 2023

declaration about the use of AI in generating the text of the manuscript similar to the declarations on funding and conflict of interests. 4. Tourism 2030 and large language models: the rise of the digital teachers and research assistants Thanks to ChatGPT, tourism educators and researchers have started to experience the power of LLMs. Considering the different arguments concerning the impact of using ChatGPT in tourism education and research elaborated in the previous section, the following question is raised: How will large LLMs reshape tourism education and research in the future? Figure 1 Conversation with ChatGPT about references on the topic of “robots in tourism” VOL. 9 NO. 2 2023 j JOURNAL OF TOURISM FUTURESj PAGE 217

LLM-based chatbots, including ChatGPT, will transform tourism education and research in the long run. If they are applied skillfully and efficiently, they can be effectively used as digital instructors, curriculum creators, assessors/markers and writers of academic publications. In addition, LLMs will play a crucial role in redesigning tourism education from “teacher-student” interactions to “teacher-AI-student” co-creation and will shift the focus of human educators on creating innovative tasks and activities. In the context of tourism education, chatbots and voicebots with integrated LLMs might be adopted as digital teachers to give students more engaging and efficient learning experiences and outcomes. Unlike human lecturers, they can repeat and reword the texts they generate as many times as necessary without complaints. In this vein, tourism-related digital teachers can be built to engage with students and deliver individualized and interactive lectures or classes on a range of themes and subjects within the field. Due to their ability to be taught in a variety of languages, these digital teachers will be qualified to teach tourism to students of different nationalities and origins. In addition, they will be able to evaluate written submissions and offer guidance on language use, grammar and style, leading to assisting students in developing their academic writing skills. LLMbased digital teachers can also make learning more accessible and provide valuable information for students concerning their tasks and research-based activities. Also, digital teachers would be able to grade tests, assignments and other course assessments, giving students prompt and precise results. Thus, the likelihood of human bias can be diminished and assessment fairness can be enhanced, although it will not be completely eliminated due to biases in the algorithm and training data set, for example (see Ivanov and Umbrello, 2021). This might eventually improve the efficiency and effectiveness of assessments and give students more individualized and insightful feedback by utilizing LLM-based digital teachers as assessors or markers in tourism education (wouldn’t this be fantastic?). For tourism educators, LLM-based chatbots would be used to automatically develop up-to-date and high-quality draft educational content and materials, such as interactive assessments, examinations and course outline plans, which will be further improved by the human lecturers if needed. Additionally, they will provide personalized tourism-linked curricula based on the needs and interests of each student; instructors can assess student progress and achievement and Figure 2 ChatGPT generated questions to measure the attitudes toward robots PAGE 218 j JOURNAL OF TOURISM FUTURESj VOL. 9 NO. 2 2023

modify the classes as necessary to create a more individualized and productive learning environment. While LLM-based digital teachers can accurately grade some tests, it is crucial to keep in mind that for more complex or innovative activities, humans will still be required. Therefore, the rumors that they will go extinct (Ivanov, 2016) might be exaggerated. The digital teachers would support the human lecturers and will lead to “human lecturer-AI-student” co-creation of educational experience and value. With regard to tourism scientific research, LLM-based digital research assistants will be capable of writing research papers (see, for example, the first academic book written by an AI, Writer, 2019). They will support tourism researchers in writing the draft literature reviews, provide justification on methodology, prepare tables and charts and so forth. This means that the coming years will witness a great evolution in the number of research publications on tourism. Consequently, the body of knowledge and literature on new trends and themes in tourism will be reinforced. However, although LLMs are capable of producing good academic writing, it is crucial to consider that human authors will still be required in the future to revise and assess the work for originality, style and overall quality. 5. Conclusion ChatGPT is only the forerunner of the AI tsunami that is going to hit tourism education and research in the coming decade. Although there are many AI systems, virtual assistants and chatbots, none of them have been as efficient or user-friendly as ChatGPT (Adamopoulou and Moussiades, 2020). It is a major disruptor in education and research. Higher education institutions and researchers need to adapt and embrace AI because it will not be the AI that will replace lecturers and researchers but lecturers and researchers who actively use AI will replace lecturers and researchers who do not use AI. In that sense, ChatGPT and other LLM-based chatbots will be enhancing rather than replacing tourism educators and researchers and will transform their work making it easier, more inspiring and intellectually challenging. In the long term, tourism educators’ work and life satisfaction would improve. In practical terms, to harvest the benefits of ChatGPT, universities need to acknowledge the reality and allow students and lecturers to use it rather than go against the stream. Tourism and hospitality programs have already started to include robotics in their curricula in one way or another (Murphy et al., 2017); now they will need to adjust ChatGPT and generative language models. Student assessments need to be revised in several directions. Some assignments might be focused on the application of ChatGPT and other language models in a tourism context in order to help students improve their digital skills. Other non-AI-focused assignments could be less generic and more specific, case-study based and require more critical appraisal rather than description. This will allow educators to evaluate what is really important to students and their employability (critical thinking and application of theory into business practice) while leaving AI to deal with repetitive and generic tasks. Policies and courses for students and educators on the ethical and responsible use of AI are needed. Academic journals in tourism and hospitality need to face a new reality as well. Their publishers and editors have to acknowledge that parts of the texts in the manuscripts can be generated by AI (see, for example, Ivanov, 2021). They need to accept the fact that ChatGPT and other LLM-based chatbots are tools like any other tool that researchers use – sophisticated but yet tools. The fact that the AI-generated text which the researcher used in his/her publication does not remove the researcher’s responsibility for the content of that same text. Of course, the use of AI for text generation needs to be duly acknowledged in the manuscript as relevant. 6. Future research directions The aforementioned issues concerning the use of ChatGPT in education and research lead to various directions for future work on the subject within the tourism context. To begin with, future VOL. 9 NO. 2 2023 j JOURNAL OF TOURISM FUTURESj PAGE 219