Virtual tour guided by the locals is a new type for users on sharing platforms to share their underutilized services (i.e., information or knowledge of the destination). Scholars have extended the research on local experience to food-sharing services and advanced our understanding of meal-sharing experiences with local foods [5, 6] and peer-to-peer dining experiences [7]. For instance, [5] identified a five-component construct of street food experience in local-guided tour, including "local guide's attributes, perceived food authenticity, local culture, perceived cleanliness, and novelty." They further found social interaction, awe, and servicescape can also be the key components of meal-sharing experience with local foods [6]. Such forms of tours are unique with more authentic engagement in the destination because the local experiences are cocreated by the residents (hosts) and visitors [7]. That is, social interaction is at the heart of consumer experience to the tours designated and organized by the locals. However, the standstill of traveling brought by the COVID-19 prevented these peer-topeer social interactions, leading the industry and tourists to embrace the alternative models of traveling such as virtual tourism and online experiences [8]. Although it was noted that consumers' experience in virtual tours amid the pandemic significantly increase their visit or purchasing desire [9], a critical gap exists in the understanding of consumer experience in the new service, virtual tour guided by the locals.

### 3 Methodology

A qualitative approach following the interpretive paradigm was utilized because the phenomenon can be understood from the perspective of individual experiences. Tourists' online reviews about their virtual tours were adopted for the sake of generating primary and insightful data. Three selection criteria were employed to confirm the eligible virtual tours: organized by the locals, available during the pandemic, merge the experience with the local culture. Finally, one of the most popular Online Experiences uploaded in August 2020 and led by a Beijing native on Airbnb was selected. It is focused on experiencing Great Wall from its different sections and history and the host has visited Great Wall for many times. This 45-min activity costs 120 CNY (per tourist) with maximum bookings of 10 persons each time. The listing of the reviews from August 2020 to July 2021 was ordered based on relevance, helpfulness, and length. 190 reviews were obtained and read through, among which 39 reviews in Chinese or other language were translated into English. 21 reviews that have no meaningful units or cannot form a complete sentence were filtered out. The qualitative data selection was ended when no new meaningful understanding on the virtual local experience was read. Finally, 135 reviews (11–150 words) were collected for further analysis.

The narrative information was interpreted with a thematic and paradigmatic data analysis approach. The multidimensional framework of consumer experience proposed by [4] guided the procedure. Given the contextual nature of consumer experience, the distinction in contexts (online vs. offline) and situations (normal vs. non-normal) were particularly addressed when capturing the meaningful units and formulating key themes about tourists' local experience via the virtual tour amid the pandemic. NVivo 12 was applied to code and examine the texts. Trustworthiness of data analysis was confirmed after being checked by an expert in the field of sharing service.

### 4 Findings and Discussion

Three stages embedded in tourists' local experience via virtual tours were concluded, delineating experience encounter, experience evaluation, and behavioral intention (Fig. 1). Experience composition covered four dimensions of the virtual tour experience, namely interpretation quality, host credibility, tourist-host social contact, and peer interaction. Each dimension was further determined by particular factors. Interpretation quality was composed of information quality, orchestration quality, and display quality of the virtual guided tour. A successful interpretation was mainly characterized by informative and insightful understanding of the destination, well-designed orchestration based on story, culture, and gamification, as well as the immersive audio-visual enjoyment; Host credibility was understood through five factors, among which appetency and ardent love to local culture were revealed as the unique reasons that bring praise to the hosts; Tourist-host social contact was qualified by instant Q&A, relationship maintenance, service recovery, and special care from the hosts before, during, and after the virtual tour; Peer interaction mainly occurred between friends or families members and was enhanced by the increasing intergenerational conversation and social bond.

Experience evaluation came from tourists' benefits and satisfaction gained from the virtual tour. Besides the educational function similar to other tourism types, virtual guided tours could offer unique tips to navigate tourist trips after the pandemic, bond their social network during the staycation time, and could also make some tourists recall the wonderful past visits to the same destinations. Tourists' satisfaction was assessed through the comparison to their expectation and their feeling in the past visits in person. It is worthy to note that tourists' sense of telepresence, "feeling like visiting the destination for real with the hosts," became the majority motive of their satisfaction.

Tourists' behavioral intention illustrated behavioral tendencies both online and offline. Tourists tend to recommend or repurchase the virtual tours organized by the same host, or plan to attend other virtual tour activities in the future. The virtual tour experience can also catalyze tourists' offline tour after the pandemic by facilitating them to visit the destination in person whether guided or not guided by the host.

Fig. 1. Conceptual framework of virtual guided tour experience process

Findings of this study revealed that tourists can feel a solid space beyond the plane screen through the immersive experience based on culture and story-based interpretation supported by the local hosts. The consequences of such experiences can accelerate tourists' willingness to recommend or repurchase online experience activities, which may further switch into a real visit or revisit the destinations after the pandemic. Accordingly, a formation process of the virtual guided tour experience for tourists is developed by identifying the constructs and stages of consumer experience (Fig. 1). This process suggests that sociability and interactivity of the virtual guided tours, to a certain extent, satisfy the consumers' desires for travel amid the pandemic and induce the travel desire post-COVID-19. Despite that virtual guided tour is less likely to be substitutes of conventional travel, it can advance the innovation of travel activity by designing high-quality local experiences with the wisdom of the locals.

## 5 Implications

This study enriched the knowledge on virtual tours and sharing economy by developing a conceptual framework of tourists' local experience via virtual tour guided by the locals; it accounted for determinants and consequences specific to the immersive experience of the destination with experience encounter, experience evaluation, and behavioral intention. It also identified the factors constituting tourists' online local experience, which provides a comparison agenda to distinct and understand the differences between virtual tours guided by the locals and conventional tours. More importantly, this study contributed a marketing strategy to navigate tourism crisis recovery by co-creating values between the sharing platform and the locals, which will be helpful for destination marketers, small tourism operators, especially for the small independent operators. Also, it suggested that the virtual tour providers should pursue an immersive experience combining their understanding of the local culture with a high level of interactivity and sociability in designing.

## 6 Limitations and Future Research

Considering virtual tours' diversity, findings in this study are necessary to be further examined in other themes of experience activities guided by the locals, such as online classes about cooking, writing, dance, or other arts. Quantitative approach is need in future to test the feasibility of the proposed virtual guided tour experience process.

## References

Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

# Special Track on Big Data and Smart Tourism

### Data-Supported CRM as a Lever for DMO Success: A Social Exchange Relationship Approach

Birgit Bosio1(&) and Melanie Scheiber2

1 MCI Management Center Innsbruck, 6020 Innsbruck, Austria<EMAIL_ADDRESS>2 Ötztal Tourismus, 6450 Sölden, Austria

Abstract. Customer relationship management (CRM) is proving to be one of the most promising business strategies. However, in the field of destination marketing literature, a problem exists as to how data-supported CRM can be established. While customer data management has already been well exploited in other industries, DMOs lack customer proximity and data sovereignty. The aim of this paper is to fill this research gap and show how a data-based CRM can be deployed by DMOs based on the principles of social exchange theory. In 13 expert interviews, these aspects were examined from the DMO's point of view. The results show that the exchange relationship must be established taking into account the DMO's extraordinary conditions and critical success factors. In order to stimulate guests' desire for dialogue or the willingness to disclose personal data, DMOs should offer high-quality customer benefits. A combination of hedonic and utilitarian benefits are found to be the most effective stimuli. In return, only the most necessary customer information should be requested and subsequently built passively. Only if the cost and benefit ratio of the exchange relationship is positive for both parties, a database for the CRM can be built in order to foster long-lasting relationships with potential and returning guests.

Keywords: Data-based customer relationship management Social exchange theory Destination management

### 1 Introduction

Every day companies lose customers unconsciously [28]. Therefore, customer relationship management (CRM) serves to "… encompass the development and consolidation of long-term profitable customer relationships through coordinated and customer-specific marketing, sales and service concepts with the help of modern information and communication technologies." [35] Due to an even stronger trend for individualization in travel, companies need to know about travelers' needs and wishes. This topic is becoming increasingly important also in view of the current COVID-19 crisis. Customers' wishes and requirements thus become the focus of every company and all its business areas [27]. The fundamental basis for maintaining customer relationships is customer data, which is condensed into customer profiles. These must be aggregated, classified and stored in a customer data platform [60]. The profiles then serve for databased CRM to derive tailored offers and communication [37] based on the individual information such as demographic data or psychographic data. Building a database should be seen as a profitable investment, as customer information significantly increases the efficiency of marketing activities [17, 43, 57] and allows companies to generate a higher return on investment [33]. Early approaches in CRM application in community-based tourism analyzed the degree of CRM implementation in destinations [20]. Other authors stressed the importance of cooperation between various service providers and the DMO in community-based tourism for an integrated CRM [21, 22]. DMOs were defined as "enablers of integrated electronic CRM" and an adoption framework for this cooperation was developed [21]. Also, the visitor relationship marketing orientation among DMOs was researched and a model to operationalize DMO visitor relationship orientation developed [42, 46]. Results showed that DMOs were often "responsive and reactive rather than proactive" [42]. Another author analyzed data-driven CRM for airline and travel agency industries [10] and coffee shops [11] in Taiwan. While bigger companies are already quite successful in strategically collecting customer data, the tourism industry lacks behind in this topic. A study amongst Austrian and Swiss DMOs showed that there is a huge gap between data availability and the strategic use of this data due to legal, know-how and financial constraints [4]. Data is very often still not made available online, not collected systematically, if so stored in silos by other service providers and links between databases are often missing. They can neither process data of guests staying in the regions nor of their activities. As tourism destinations are complex systems [3], they are not in command of data sovereignty [25]. While this field of research is not new for the tourism and hospitality industry [6, 38], the majority of tourism businesses still rely completely on the success of the development of the touristic offer. Their lack of understanding of customer orientation and their dismissive attitude towards modern approaches to creating competitive advantages are to blame [56]. Even the DMOs have resisted the demands of digitalization for too long [36]. Considering the increasing global competition, the trend shift towards short breaks and the decreasing number of regular guests, intelligent approaches such as CRM are immediately required in destination marketing in order to maintain the competitiveness of destinations [2, 36]. Therefore, it is up to DMOs as strategic competitive entities to drive CRM for the benefit of the destination and all its touristic stakeholders [53]. Following the literature on CRM in the tourism and hospitality industry [49], this paper addresses various research gaps: "The majority of published research articles are in the area of hospitality, with a specific focus on hotels and restaurants. (…) Future research in the tourism area, especially at the destination level is also required." [49] Indeed, in literature CRM has gained a foothold in tourism research [49], but unlike the numerous research contributions in the hotel sector [17, 57], CRM in the context of DMOs is discussed in fewer recent publications [2, 36, 46]. "In examining the three components of CRM, the technology aspect has received the most attention, whereas the roles of people and process have been widely neglected" [49]. The general marketing research fields like database marketing, permission marketing, marketing automation, online marketing or data privacy issue aspects of building a database for CRM, focus either on technological aspects [28] or on behavioral aspects [30]. A holistic view on both crucial aspects has not yet been issued. This is the reason why this paper combines both technological and behavioral aspects and stresses the social interaction of both supply and demand side. "The topic of e-CRM is widely researched in the marketing, management and IT fields. However, there is a need for H&T scholars to focus on e-CRM" [49]. Digitalization has become one of the main fields in tourism as an informationintensive, globally-oriented, but locally-delivering industry. Technological advancement is transforming tourism value chains. Whereas technological innovations are doubtless possible, the problem remains in implementing digital services and marketing within the mainly small-structured tourism industry [15]. There is thus still a long way to go for the digital transformation of tourism businesses. Therefore, when establishing a destination-wide CRM, also the interests of service providers as well as their level of digital literacy need to be taken into consideration [50]. In order to also take into account both the DMO's role and the necessary cooperation with local service providers from the supply as well as the customer side of this relationship, this paper focuses on how to establish a balanced relationship between the DMO and the potential or existing guests and tries to answer the following research question: How can social exchange promote the generation of dialogue-ready customer contacts for data-based CRM in DMOs to create a win-win situation for both sides? Which key factors are decisive for the success of this social exchange relationship? The aim of this paper is to show how a data-based CRM can be developed by DMOs from a holistic perspective as well as to consider the challenges of the digital transformation for both DMOs and service providers.

### 2 Building a Customer Database for CRM

This paper addresses technological aspects for both DMOs and small-scale tourism providers as well as the lack of the social dimension of the relationship between guests and the DMO.

### 2.1 Technological Aspects from the Supply Perspective

The instruments for building up a customer database for CRM are primarily located in acquisition management by addressing the target market, identifying interested parties and converting them into customers [16, 51]. It includes the stimulation of interest in the target market, the identification of prospects as well as their processing until the conclusion of a purchase. Through the sales funnel, prospects should be transformed into customers [51]. At the end of the funnel, it is important to bind these customers to the company through the subsequent customer loyalty management [43]. Along the sales funnel, different information about the customer is generated at various touchpoints of the customer journey. This data flows into the company's database, is classified and clustered by predefined segmentation attributes and is condensed into a unique customer profile [17]. The basic motive of creating a customer profile is to present the customer in a holistic picture, because the generated customer profiles are used to initiate, maintain or rebuild customer relationships [4]. Hence, the more data is generated from a customer the better the picture of a customer gets. Which customer information a customer profile should contain depends on the respective objective of a company [32]. Name and email address were identified as the most important and lifestyles as the second most important variables for customer acquisition [58]. Today, the checkbox for obtaining marketing permission also counts as a target variable for lead generation, because personal data may only be stored, processed and analyzed with the explicit consent of the data subject [47]. Therefore, every European company needs to consider the General Data Protection Regulation (GDPR) to initiate and maintain business relationships [23]. While these processes work well for other industries, DMOs mainly are not in direct contact with the customer, as guests usually directly interact with accommodation or other service providers. On the other hand, the small-scale tourism providers often have neither the personal and financial resources, nor the know-how to establish such customer databases. This makes the technological requirements for a databased CRM of a DMO even more challenging.

### 2.2 Behavioral Aspects from the Demand Perspective

Major data leakages and misuse in the past have had a negative influence on the trust of customers in handling personal information [9, 14]. Therefore, from the perspective of customers, also behavioral aspects have to be taken into consideration. Privacy concerns imply a perceived sensitivity to the preservation of one's own privacy and manifest themselves in concerns about storing, using, sharing and publishing personal data [1]. In addition, direct marketing is often leading to customer annoyance [4]. The cause-privacy concern impact model (APCO) explains the emergence of privacy concerns and their influence on customer behavior [55]. Beside experience, awareness, personality, demographics and culture as the drivers of privacy concerns, plenty of authors studied the privacy paradox. It describes the contradictory contrast of personal attitudes to displayed behavior [29], which influences the behavioral intention and is the main cause of contradictory behavior patterns [55]. Thus, customer behavior only partially reflects the conventional assumptions of behavioral psychology, according to which human behavior is based on rational considerations. In fact, customer behavior is based on the outcome of a privacy calculus or a personal cost-benefit comparison [34, 39]. To impact customers' privacy calculus and hence consumer behavior positively, the use of incentives has widely been discussed in literature [30]. Discounts and free products or services are considered as monetary incentives due to their measurable value [41]. Nonmonetary incentives include hedonic incentives, which are described as a psychological benefit component [30] and utilitarian incentives, which are characterized by their functional utility character [44]. All those incentives can be combined in crystallization points [7] such as bonus schemes [26], applications [13], customer clubs [12] or loyalty cards [45]. It is also important to think about where to place these incentives within the customer journey. The cost variable of the privacy calculus includes all risks and negative consequences that arise from data transmission [59]. If the expected benefits exceed the costs, customers are willing to allow data transfer [34]. The cost and benefit calculation in the privacy calculus is based on the principles of social exchange theory [34, 39] as one of the oldest, but still most popular theories to explain social behavior [48]. Parties are mutually interdependent and impose costs and rewards on each other through their behavior [18, 24]. Thus, the least costly, most rewarding option is chosen [54]. While this topic has been studied in CRM in general, studies on guests' behavior as an application to the tourism industry are still scarce [49].

### 3 Method

Given the need for insights into more complex structures of economic and social relationships within the field of data-driven CRM in DMOs, a qualitative research method was applied [8]. In this course, the topic was examined empirically from the alpine community-based DMO's point of view conducting 13 semi-structured guided expert interviews [19]. An interview guideline was developed based on the literature review. The main focus areas were: 1. how can DMOs successfully establish an exchange relationship for databased CRM; 2. what type of customer data must be generated in the initial contact and 3. what type of benefits must be offered in exchange; 4. how would the ideal cost benefit ratio for DMOs and guests look like 5. in which phase of the customer journey must the data generation be located. Experts were chosen, as they are highly qualified to answer the research question. They are seen as "crystallization points" of practical insider knowledge and therefore can be interviewed instead of a large number of subjects [5]. All interviews were held online during spring 2020 and lasted from 40 to 90 min. The following selection criteria of interviewees were established [19]: professional qualification, knowledge of the functions of DMOs and touristic behavior, and a close relation with alpine community-based destinations in the German-speaking area. The sample comprises 13 participants of which four are CEOs in consulting companies for strategic and digital matters of DMOs, two of them professors in tourism marketing management on a collage of higher education, two chief digital officers in DMOs, four marketing employees responsible for CRM in DMOs, one chief marketing officer in a cable car company and leader of a CRM project launched together with a DMO. Not having focused on gender nor on nationalities, the sample resulted in seven male and six female participants, with two of them living in Switzerland, four in Germany and 7 in Austria. All participants fulfilled the qualification criteria. For data analysis, a summarizing content analysis was chosen [40], as it is ideally suited for evaluating expert knowledge in a narrow field of research [52]. The interviews were transcribed [16]. MAXQDA, a common software solution for qualitative data analysis [31], was used to develop a codebook. This was done by paraphrasing relevant text passages from the interview transcripts, generalizing their messages and reducing them to their point of meaning [40]. This method allows to extract expert knowledge from the generated qualitative data and to derive inductive categories in which this coded information is compound. The resulting categories of this research include: important frame conditions of DMOs and key success factors for the establishment of exchange relationships; required customer data to create a customer profile and effective customer benefits in exchange. Based on these categories the experts research results have been discussed. As there is no significant difference between the DMO's managers or employees compared to other experts' perspectives, the results of this research must not be discussed from the different expert group's points of view.

## 4 Results

The research results show that the establishment of an exchange relationship with tourists must be considered in the context of the DMOs' frame conditions and key success factors as well as consider the design of the exchange relationship.

### 4.1 Establishment of the Exchange Relationship

DMOs suffer from a lack of customer proximity as guests usually directly interact with service providers in the destination. Thus, the DMO often has few to no touchpoints with guests who have already been to the destination. Even though all experts view DMOs as an important source of inspiration for guests, they are by nature in an unfavorable position for data generation. Other key players in the destination however, such as accommodations, gastronomy, shops, touristic service providers are in an ideal position for data generation as they are in a legal economic relationship with guests. Therefore, experts refer to establishing networks with services providers within the destination. By means of stakeholder management DMOs have to convince all key players and involve them in the process of data generation for a CRM system. With them bridging the contact between the DMO and tourists, valuable data pools within the destination can be channeled. In addition, a number of key success factors for the establishment of exchange relationships could be identified. These are classified as strategic, conceptional and methodological factors. The strategic key success factors are based on a strategic approach of why data and what data is generated, and how it is going to be used by the DMOs. Otherwise, data is generated randomly and may lack specific insights or it is too broad to be structured usefully. Also, know-how in the field of databased CRM must be implemented in the organizational structures of the DMO to create marketing efficiency to the destination's benefit. The conceptional success factors include facilitators of the exchange relationship. For DMOs it is essential to know that the less data is requested from tourists in exchange for a benefit, the more likely is their willingness for data disclosure. Also, the relevance of the offered benefits must be maximized and exactly meet customers' needs at the specific touchpoint in the customer journey. Even though the inspiration and consideration phases (pre-booking phase) are already targeted by many DMOs, all touchpoints along the whole customer journey should be addressed. All experts see a high and so far not claimed potential for exchange relationships during the stay in the destination. In order to exploit potentials, it is suggested that DMOs become innovative in terms of creating intelligent customer benefit offers. Experts underline the necessity of making best use of the DMOs' frame conditions, rather than emulating common sales funnel strategies of usual single player businesses. The methodological success factors include that DMOs need to guarantee high customer experience at all touchpoints and interact with customers in a very simple context as complexity leads to high drop-off rates even before the actual exchange takes place. In general, experts urge DMOs to act in a helpful and trustful way towards tourists in order to minimize data privacy concerns and to create more confidence by tourists.

### 4.2 Design of the Exchange Relationship

In order to motivate the guests' desire for dialogue, as little data as possible should be requested in an initial active contact. The e-mail address as identity carrier and point of contact, the name, and the marketing permission for the legitimacy of the data use as well as the defined interests that give meaning to the identification data represent the ideal starting point for the creation of a basic customer profile. Experts stress that extending customer data is gained through further touchpoints. Many of these customer data can be tracked passively, without affecting the customer's data privacy concerns and therefore without causing social costs. Findings suggest that for creating a customer profile relevant for CRM, DMOs must at least add the customer's interests. Less but also relevant are preferences or origin. In exchange for customer data, rewards become essential. Results suggest that rewards should include a versatile combination of incentives. There is a clear preference for hedonic and utilitarian incentives to stimulate the willingness to engage in dialogue. Information before or during the journey emerges as one of the most significant incentives as it creates high benefits for customers at low costs for DMOs. Information of this type is classified as hedonic incentive as it provides profound travel experiences. Moreover, tourist communities with options for digital exchange on the DMO website or possibilities to express recommendations and reviews during the post stay phase are considered effective. Hedonic incentives cause low costs for DMOs. Utilitarian incentives provide a more convenient travel experience. Experts claim that assisting technologies generate extraordinary customer benefits in all phases of the customer journey. Also booking systems for tickets, experiences or other services of touristic interest are highly beneficial. Assisting tools or systems cause moderate costs, as licenses or development costs are predictable and limited. While hedonic and utilitarian incentives are considered to generate high customer benefits, five of thirteen participating experts dissuade DMOs from offering monetary incentives as the quality of generated leads is expected to be very low in terms of higher opt-out rates as customers are not really interested in a lasting exchange relationship but rather seek for one-time saving opportunities. However, receiving gifts such as free services, goodies or consumption goods during the journey, appears to have positive effects. For the exchange relationship to be successful, it is important that the cost-benefit-ratio is balanced. This means that guests should not have to disclose an unnecessary amount of personal data and DMOs should not suffer from disproportionate project costs. Therefore, incentives causing low or flat-rate cost for DMOs such as information and assisting technologies are the best option to keep the exchange relationship balanced. Gifts on the other hand, may in high quantities get too cost-intensive.

### 5 Conclusion

The research results show that DMOs are in an unfavorable position for establishing an exchange relationship for databased CRM on their own, due to lacking customer proximity. Even though the DMOs' booking platforms would in fact be an important touchpoint for establishing exchange relationships with tourists, OTAs hold most of the market share while DMOs count few bookings on their own platforms. Nonetheless, DMOs are still in the ideal position to bridge the gap using their networking capabilities and power in the destination. If they successfully collaborate with key players in the destination, they could establish a data-based CRM. DMOs may convince accommodation providers to communicate the DMOs benefits to their guests by linking directly to the DMOs landing pages or registration forms. Thus, the DMO potentially creates touchpoints with all guests in the destination. Solutions of this kind would be game changing, as mediation is an effective and legal way to get in touch with all tourists coming to the destination, no matter whether they booked their holiday on the site of third parties such as OTAs. It is also suggested that DMOs clearly define their goals of a databased CRM system before establishing an exchange relationship. Depending on the goals, relevant touchpoints, customer data, customer benefits and lead quality may differ. For the goal of tailored marketing communication and offers based on customers' needs, a basic customer profile must at least contain the customer's email address, his or her name, the marketing permission and very important – his or her interests. It may be however suggested that customer's interests are gained passively during further touchpoints, because the more data is requested at an initial touchpoint, the higher the dropout rate will be. In exchange for data disclosure, DMOs must offer extraordinary customer benefits at acceptable costs for the DMO in order to keep the benefit-cost-ratio balanced for both parties. As the results show that monetary incentives may lead to high costs or even negative effects, DMOs must channel the power of hedonic and utilitarian incentives. Experts consider information, communities together with systems for holiday administration and planning most effective. Yet it appears that efficiency may be even increased by consolidating all benefits into one crystallization point. This could be a destination app or travel guide, which assists customers along all phases of the journey. It may provide information on activities and individual programs based on the customer's interests, scheduling and booking before the journey. During the journey it offers orientation, while after the journey it allows customers to review their activities. Such a travel guide which includes accumulated hedonic and utilitarian benefits and maybe even - if still cost effective - free services, stimulate the willingness for exchange as they provide high value for tourists and low costs for DMOs.

## 6 Limitations and Implications

This research involves some critical limitations as technical aspects are only addressed in rudimentary form and thus remain largely unsolved. Furthermore, staff of DMOs formed the biggest group within the sample which might cause a bias in the results. Another bias might arise from the time of interviews falling within the COVID-19 crisis. Future studies should take into account the demand side to prove the actual effect of the incentives on the willingness to engage in dialogue as well as on the actual perceived data privacy concerns from the demand side. Another essential aspect would be a holistic analysis of the exchange relationship over a longer period. In addition, surveys should also be carried out outside of the German-speaking area. Based on this research, Ötztal Tourism in Austria used these findings to establish a databased CRM system. As a solution for the problem of data sovereignty through various destination stakeholders, the DMO exploited its stakeholder proximity and built a destination-wide partner network of approx. 1,000 accommodation and 30 service providers, who mediate the contact between the DMO and the tourists. This practical example shows how a DMO can overcome the lack of customer proximity and achieve data sovereignty by creating a network platform amongst service providers, which offers valuable benefits for both existing and potential guests. By applying a combination of mainly hedonistic and utilitarian benefits and creating a customer profile gradually, a balanced social exchange relationship can be developed. This research contributes to the knowledge of alpine community-based DMOs as to how a databased CRM can be established to fully contribute to the destination's marketing efficiency. It shows that not only technical but also behavioral aspects have to be considered and how the principles of social exchange effectively facilitate a win-win relationship for all involved parties.

### References

Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

### Towards a Strengths-Based Personal Informatics Framework for Transformative Tourism Experiences: A Phenomenological Study on Serious Leisure Practitioners

C. K. Bruce Wan1(&) , Cees J. P. M. de Bont2 , Paul Hekkert3 , and Kenny K. N. Chow1

1 School of Design, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong<EMAIL_ADDRESS>2 Loughborough Design School, Loughborough University, Leicestershire LE11 3TU, UK<EMAIL_ADDRESS>3 Faculty of Industrial Design Engineering, TU Delft, Delft, The Netherlands<EMAIL_ADDRESS>
Abstract. Personal technology plays an integral role in shaping people's quality of life which includes leisure and tourism experiences. A number of personal informatics tools can support people in performing their activities by collecting biometric and environmental data; however, little is known regarding the use of psychological data to enrich leisure and tourism experiences. To address this research gap, this study aims to propose a conceptual framework that fosters memorable and meaningful leisure experiences (MMEs) based on theories from serious leisure and positive psychology. In particular, this study probes into the MMEs of serious leisure practitioners who put their efforts and resources into pursuing intrinsically rewarding leisure activities. Excelling at these activities, which may draw upon participants' character strengths, yields sustained fulfillment which fosters personal transformation. The idiosyncratic nature of MMEs demands a phenomenological inquiry that involves in-depth interviews concerning the character strengths used and their development trajectories. Using theory triangulation from both positive psychology and serious leisure allows researchers to gain a holistic view of participants' well-being. Character strengths were found to be the integral factors that contribute to MMEs at different stages of leisure activities. The result identified three aspects of strengths used: strengths well spent, reflection and introspection, and anticipation of the future self, which informs the development of a strengths-based personal informatics framework for leisure and tourism.

Keywords: Positive psychology Character strengths Serious leisure Meaningful experience Conceptual framework Personal informatics

### 1 Introduction

Technology plays an integral role in supporting the tourism experience. Recent information and communication technology innovation highlights include the emergence of smart tourism, which is characterized by the widespread adoption of personal technologies, big data, and networked devices in tourism settings. Future development may offer travelers new social and experiential dimensions by personalizing the provision of memorable and meaningful experiences (MMEs) [1] that are personally significant [2]. More importantly, the attainment of these goals requires technology that is specifically designed and strategically implemented [3]. Compared to mundane experiences, MMEs are vivid and explicit autobiographical memories that arise from exquisite, remarkable, and valuable events characterized by high emotional involvement and frequent rehearsal [4]. Besides tourism activities, serious leisure [5] can be the source of MMEs because practicing serious leisure often involves one's commitment and self-development. This study investigates how people's character strength and serious leisure activities contribute to MMEs, then proposes a conceptual framework for technology-mediated experience that could support people to gain MMEs in their leisure journeys.

### 2 Literature Review

### 2.1 MMEs Through the Lens of Positive Psychology and Serious Leisure

Positive psychology such as character strengths has been recognized as the personality traits that contribute to people's meaningful lives [6]. The values in action (VIA) classification of character strengths [7] proposes six main virtues and 24 related character strengths (see Table 1). Character strengths are conceptualized as a preexisting capacity for a particular way of behaving, thinking, or feeling that is authentic and energizing to the user and enable optimal functioning, development and performance. They are behaviorally based unique personality traits; each individual is affiliated with their own bundle of strengths (top five) known as signature character strengths. The strength-based approach suggests that recognizing and making good use of one's inherent character strengths are the channels through which people generate positive experiences, find meaning and ultimately flourish [8]. One of the most reliable ways to identify MMEs is through the pursuit of intentional activities that match one's personal character strengths [9]. These activities should be intrinsically rewarding and interesting and, when engaged in them, individuals may feel a sense of purpose, curiosity and fulfilment [10].

Serious leisure (SL) [5] can be the activity which allows people to develop their character strengths [11]. SL is regarded as the systematic pursuit of an amateur, hobbyist or volunteer activity sufficiently substantial, interesting and fulfilling for a participant to find a (leisure) career there in acquiring and expressing a combination of its special skills, knowledge and experience [5]. SL delineates six characteristics which describe its inherent quality: 1. the need to persevere with the activity; 2. possibility to develop a leisure career; 3. the need to put substantial effort into gaining skills and knowledge; 4. unique ethos and community; 5. identification with the pursuit; and 6. gaining valuable outcomes and benefits. Despite practitioners often being confronted with difficulties and challenges in their pursuit, serious leisure activities are intrinsically rewarding and interesting, and when engaged in them, individuals may feel a deep sense of purpose and fulfillment leading to self-transformation [12]. This study uses the two bodies of knowledge to probe into how people gain MMEs through their character strengths development in their serious leisure pursuits.

Only recently MME has gained traction in tourism research for its enduring wellbeing benefits [13] which lead to self-transformation [14]. Also, eTourism study [15] has called for a transformative research agenda that incorporates transparency, plurality and creativity to foster sustained well-being to be developed for the tourism industry.

Table 1. Values in action classification of character strengths and virtues [7]

### 2.2 Potential of Using Technology to Support MMEs

Personal technology plays an integral role in shaping people's quality of life which includes leisure and tourism experiences. It refers to a class of tools that help people to collect personally relevant information for the purpose of self-monitoring and selfreflection [16]. Tourism researchers [17] have suggested that the ubiquitous nature of technology gives it the potential to create MMEs via individual empowerment [3]. For instance, wearable devices support people to perform their activities by capturing and analyzing biometric, environmental, and social data. However, little is known on using psychological data, such as character strengths, to enrich leisure and tourism experiences. Wan and his colleagues [18] demonstrated a strengths-based digital diary which allowed people to journal and savor memorable and meaningful tourism moments with photos and texts provided by users. The journal platform supports users to reveal meaning by making implicit psychological dimensions of MMEs explicit. As such, the incorporation of psychological dimensions in personal informatics could foster transformative tourism experiences. The goal of this study was to propose a conceptual framework that incorporates character strengths into informatics that may foster MMEs in leisure and tourism. Especially, this study explored how the system of smart things can be used as a mediator to nurture people's character strengths. This study addressed the following questions:

RQ1: How do individuals draw upon their character strengths in their sustained pursuits of leisure activities to generate memorable and meaningful experiences during their travels?

RQ2: What opportunities are there for personal informatics to foster MMEs using the themes identified in RQ1?

## 3 Research Methodologies and Methods

This study acknowledged that individual sense-making and experience of SL are highly contextual and influenced by the complex and ever-changing social phenomena encountered [19]. Using an idiographic approach, the research objective was to determine how character strengths contribute to the generation of MMEs through the pursuit of SL activity in the context of tourism. The data collection involved a questionnaire and one-on-one thematic in-depth interviews. The questionnaire introduced character strengths literacy to the participants so that they could recognize their signature character strengths through self-nomination [20]. The in-depth interviews, on the other hand, invited the participants to introduce their serious leisure activities and explain why their activities are attractive, engaging, and meaningful to them. Also, the participants were invited to associate their character strengths with key memorable and meaningful moments of their leisure practices. Interpretative phenomenological analysis (IPA) [21] was performed to identify the participants' meaning and sense-making from their personal standpoint at the idiographic level. The analysis drew upon the fundamental principles of phenomenology and hermeneutics and captured the participants' memorable and meaningful SL experiences through their use of character strengths as personal resources. In a hermeneutic phenomenology-informed framework, researchers must explore, describe, interpret, and identify the means by which participants make sense of their own experiences [21]. The IPA process defines five interconnected stages, from transcription to theme generation, based on the recorded interviews. In this study, stage one consisted of becoming familiar with the transcript to gain a keen sense of the SL world of the participants. Then, based on the transcripts, we generated codes and made notes on our observations and reflections about items that may have potential significance. In stage three, these codes and notes were transformed into emerging themes and were connected with positive psychology conceptualizations. Then relationships and patterns among the identified emerging themes were identified. Lastly, based on representative interview data, we generated case narratives featuring these themes. The result supported the development of a conceptual framework for a strengths-based informatics system.

### 3.1 Sampling, Data Collection, and Analysis

This exploratory study considered the sample to represent the breadth of the SL landscape. This study used non-probability and purposive samples and considered that SL can be practiced regardless of age, educational background, household composition, or profession. Although people's sense-making may have cultural influence, this study examined the process of sense-making by making their character strengths explicit. Therefore, the participants deemed suitable for this study had to fulfill two criteria: they were to be SL practitioners in any of the domains identified by Stebbins and they must have practiced their SL, either partially or entirely, on one or more of their journeys. The participants were recruited through social networks using convenience and snowball sampling methods to connect with different SL communities. Seven participants were involved in this study, who engaged in different SL genres and demonstrated varying degrees of commitment. All participants were of Chinese ethnicity and lived and worked in Hong Kong at the time of the interview. Each interview lasted for around 90 min, and the interview sessions were audio-recorded, translated, and then transcribed into verbatim English transcripts for further data analysis. The following are questions from the interview protocol:

"The assessment showed that these are your signature strengths. Do you think that these strengths describe you well?"

"Can you share with me what made you devoted to your serious leisure?"

"What are your most memorable and meaningful experiences? Do you see that any of your character strengths take part in these experiences?"

"What do you enjoy most in your pursuit?"

"What motivates you in your serious leisure activity?"

"Why is that experience valuable to you? Can you see any of your character strengths in that experience?"

"What are the turning points in your pursuit? How did you overcome these challenges? How does it relate to your character strengths?"

"What did you learn from that experience?"

"Do you think that your serious leisure activity made you a better person? How?"

Table 2 lists the participants' backgrounds, SL activities, years of experience and personal statements regarding their pursuits.

Table 2. List of participants, activities, and signature strengths regarding their serious leisure pursuits

Table 2. (continued)

a Name and details of the participants are changed to preserve confidentiality. b

Statements were formulated based on the data collected in the interviews.

c WWOOF refers to Worldwide Opportunities on Organic Farms, a network of organizations that facilitate overseas work placements on organic farming.

## 4 Results

### 4.1 Different Roles of Character Strengths in the Generation of MMEs

In response to RQ1, three core themes and six sub-themes were identified (Table 3). The results show that MMEs are multidimensional. As a measure of their credibility, all themes were supported by at least five participants [21]. Below, each theme is elaborated upon with a detailed description, and examples in the participants' own words are provided along with the researchers' interpretations. Discussions are offered at the end of each theme.

Theme 1: Strengths Well Spent. This refers to the purposeful use of one's character strengths in the creation of specific and distinctive experiences during one's journey. The experience must be specific enough for the person to have a clear goal they wished to achieve and character strengths are purposefully used for the person to achieve a desirable outcome, even though the final outcome may not fulfill the initial expectation. Two sub-themes were identified: on producing positive experiences (i.e., seeking sustained fulfillment) or on problem-solving (i.e., pain avoidance). Emily's story helped to illustrate how character strengths were well spent for realizing sustained fulfillment. Since Emily loves to connect with nature, WWOOFing trips allow her to dedicate herself to this connection. To make her experience more intellectual, she once took a butterfly guidebook with her:

I bought a butterfly field guidebook to take with me so I could learn how to distinguish between various species of butterfly from the tiny differences I observed… sizes and patterns… I really enjoyed the self-learning process. (Emily)

The excerpt highlights Emily's character strengths (i.e., curiosity and love of learning) used for the purpose of seeking positive experiences (i.e., seeking autonomy and knowledge). In contrast, Shane's experience is characterized by solving immediate problems. Shane connects creativity with her experience at the rock-climbing site in this way:

You need to be creative in everyday life situations because you must do things with very limited resources at your disposal. For example, using the same piece of cloth as a dress one day and as a tablecloth another. (Shane)

Lastly, character strengths are used for both problem solving and sustained fulfillment in the context of competition and performance. Evan's dinghy racing showed that bravery, self-control, and perseverance were needed in one of her offshore competitions:

The wind was unexpectedly strong! I really felt in danger when racing in such conditions. I also felt the pressure of being the pilot... For that competition, I required medical treatment every day because my whole body was so tense and overworked... But participating in competitions is what I like in this sport. (Evan)

The experience is comparable to flow, for which a balance of skill and challenge can lead to an optimal experience. Evan's experiences illustrate that character strengths can play a part in people's skill development in the pursuit of excellence. Nevertheless, the participants had divergent attitudes and behaviors toward their pursuits of excellence.

These anecdotes also highlight how one's affect and emotional responses play a role in formulating these MMEs. Furthermore, MMEs are not purely subjective; they are the result of constant interactions between the participant (i.e., strengths, affects, and emotional responses) and his/her surroundings (i.e., other people, objects, the environment). Moreover, these MMEs are significant to the participants, even when their initial goals are not (totally) fulfilled. These goals can be explicit and well-defined, as in Evan's dinghy racing (i.e., be the first past the finish line), or they can be implicit and not clearly defined (or even improvised) as in Shane's story (i.e., creative use of cloth has no limits). To conclude, this theme describes how people draw upon their character strengths to have MMEs.

Theme 2: Reflection and Introspection. This refers to the integration of the MMEs in one's life. These experiences can be either positive or negative and the related character strengths are not always obvious. The experience can emerge from one particular event (as shown in theme 1), an aggregation of multiple events, or as an overall impression of the experience. Through reflection and introspection, individuals try to make sense of these experiences by analyzing and interpreting them as valuable and meaningful in their lives—whether by learning a new aspect of life, gaining perspective on one's life, personal growth, or enriching one's life experience as a whole. Two sub-themes have been identified—savoring positive experiences [22] and reappraising negative experiences [23]. Andy shared an account of a mentally handicapped child who lived in the village where a school construction project was taking place. The child was unable to take care of himself and the villagers mostly ignored him or, at worst, bullied him. He worked in that village for two consecutive years and what he encountered this year was a personal epiphany:

Last year, I found the child annoying because he often disturbed us at the construction site. This year, we have a volunteer who is a mother and a social worker in a special education school. Instead of ignoring him, she welcomed him with open arms and spent time with him. The child became happier than ever before, and her kindness was spread throughout the volunteer group. This experience inspired me in many ways: first, love and care are contagious. Second, problems can be solved in positive ways… the child was only seeking love and care. In fact, this is what we are all looking for. (Andy)

Through the savoring of a positive experience, Andy's illumination is rooted in connecting a particular experience with his past experience and with the wider scope of life. This became one of the most profound experiences in his years of volunteer work.

MMEs are not always positive; painful experiences, difficult times, and failure are all common aspects of serious leisure pursuits. Our interviews showed that the participants had managed their negative experiences by finding them to be beneficial and rewarding aspects of their lives. This process is known as the positive reappraisal of negative experiences [23], which helps individuals to transcend negative experiences and to transform them into something meaningful and purpose-filled such that they contribute to personal growth. Orion shared how her chronic illness (i.e., negative experiences), which impeded her further meditation practice, had been transcended into something worthwhile and personally significant.

I felt completely disorientated after my diagnosis. I lost my goal because I was totally devoted to meditation at that time… but my sickness also made me somewhat more positive-minded because I realized that I needed to accept my sickness. I have to get through it with mindfulness and to learn how to build awareness in everyday life. (Orion)

These anecdotes illustrate how remarkable experiences, as a result of character strengths well spent, become meaningful, worthwhile, and purpose-filled by their integration into individuals' life experiences and beliefs. The savoring process focuses on cherishing, enjoying, and relishing positive experiences and elevates the experience of pleasure to a higher order of awareness. It allows people to appreciate their experience as involving something deeper than the immediate personal reactions and sensations. The positive appraisal of negative experiences, on the other hand, transforms an outcome previously perceived as negative into a meaningful and growth-promoting outcome that helps one to build resilience, act positively, and overcome adversity.

Theme 3: Anticipation of Future Self. This refers to the seeking out and planning for experiences that are congruent with the individual's personal interests [24] and that fit into the individual's development trajectory [25]. Here, character strengths also play a role in identifying such experiences. This anticipation allows individuals to pursue activities that foster eudaimonic growth. Two sub-themes were identified: seeking commitment and seeking alternatives. Over the course of our interviews, the participants shared their experiences in their development trajectory. Those with the intention to seek commitment are likely to connect their pursuits with a career path. Kelly shared her experiences of finding her future self in connection with her potential career development:

I wanted to integrate swing dance somehow into my performance and to be a swing dance teacher for college students. Swing dance can help them to build a dynamic social network. (Kelly)

However, Orion reacted to situations differently when attempting to project her future self:

I need to find an activity that allows me to meditate and develop my awareness. I recently began running, an activity in which I previously had no interest. By integrating self-awareness and setting up small challenges, I was able to better enjoy running. I hope to develop myself as a runner with the same approach and attitude as I did in meditation. (Orion)

In contrast to the other participants, Orion wanted to explore alternative activities in which their personal interests and character strengths are valued. Instead of deepening her commitments, she wanted to broaden their fields of activity and experience new things. This attitude is somewhat echoed in the broaden-and-build theory [25] in which positive emotions allow people to be open to new experiences and, thus, build enduring personal resources by undertaking new challenges. The difference may be that meaning and self-worth, in addition to positive emotions, are motivators for their decisions.

Table 3. Summary of themes and sub-themes

### 4.2 Towards a Strengths-Based Personal Informatics Framework

In response to RQ2, this study proposed a strengths-based personal informatics framework (Fig. 1) that supports individuals to generate, appreciate, and pursue MMEs in their leisure and tourism activities based on the themes identified. The framework focuses on personally relevant characters which could facilitate a self-reflection process through breaking down memorable and meaningful experiences, inquiring about the character strengths involved and fostering self-transformation with strengths interventions. The framework is compatible with current studies [3, 18] on digital wellbeing informatics systems. The following provides recommendations for developers to implement strengths-based personal informatics. Above all, building awareness of character strengths should be an important step for strengths-based personal informatics in order to make users familiar with character strengths (e.g., definition and characteristics). It can be achieved by introducing users to character strengths literacy, establishing a strength profile, and using character strengths as the system language.

Fig. 1. Conceptual framework for strengths-based personal informatics

Guideline 1. Living in and exploring the present moment. This aspect of informatics systems is to support users to immerse themselves in the present moment and capture the moment for later reminiscing. Technology can take account of the user's character strengths and combined with situation-awareness technologies support users' immersion in their experiences [26]. Technologies may also collect onsite data relevant to the activity for users to savor the moment.

Guideline 2. Appreciating one's character strengths through reflection and introspection. This is probably the easiest way for people to connect their strengths with external stimuli (e.g., people, activities, environments, etc.) and their internal psychological states (e.g., values, goals, feelings). Reflection and introspection can be an effective way to allow users to recognize the character strengths they draw upon in gaining valuable experiences [18]. Reflection allows people to bring unconscious aspects of experience to conscious awareness, and thereby gain self-knowledge.

Guideline 3. Anticipating one's future self with character strengths. Being aware of one's implicit character strengths may also inspire one to cultivate them [27]. Technology may provide strengths-based recommendations to users so that they can broaden their perspectives or deepen their commitment to the activities. The system may facilitate users to generate goals that are valuable and meaningful to them.

### 5 Limitations and Future Research Direction

This study has a few limitations. First, the idiosyncratic nature of MMEs limited this research by requiring it to start with a small sample size. Future research can consider using a larger sample size and a diverse user group. The proposed framework suggested directions for a developer to incorporate character strengths into an informatics system. Nevertheless, this study demonstrates that character strengths are a necessary but not sufficient condition for generating meaningful experiences. Interview data showed that, in addition to the purposeful use of strengths, the participants garnered meaningful experiences through constant interaction with a complex network of activities, environments, objects, and people. Also, further investigations on managerial and ethical implications are necessary even if the informatics system can support people's wellbeing. After all, the strength-based approach is as yet little explored in tourism studies. More research is needed to incorporate the framework into personal informatics applications.

### References

Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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### Destination Image of DMO and UGC on Instagram: A Machine-Learning Approach

Roman Egger(&) , Oguzcan Gumus, Elza Kaiumova, Richard Mükisch, and Veronika Surkic

Salzburg University of Applied Sciences, Salzburg, Austria {roman.egger,ogumus.imte-m2019,ekaiumova.imte-m2019, rmuekisch.imte-m2019<EMAIL_ADDRESS>
Abstract. Social media plays a key role in shaping the image of a destination. Although recent research has investigated factors influencing online users' perception towards destination image, limited studies encompass and compare social media content shared by tourists and destination management organisations (DMOs) at the same time. This paper aims to determine whether the projected image of DMOs corresponds with the destination image perceived by tourists. By taking the Austrian Alpine resort Saalbach-Hinterglemm as a case, a netnographic approach was applied to analyse the visual and textual posts of DMO and user-generated content (UGC) on Instagram using machine learning. The findings reveal themes that are not covered in the posts published by marketers but do appear in UGC. This study adds to the existing literature by providing a deeper insight into destination image formation and uses a qualitative approach to assess destination brand image. It further highlights practical implications for the industry regarding DMOs' social media marketing strategy.

Keywords: Machine learning Instagram Destination image

### 1 Introduction

The rise of social media has changed the process of information creation and communication, which affects consumer behaviour, marketing strategies, and brand image [1]. Social media further fosters the production of user-generated content (UGC), referring to any content created by consumers online [2]. Meanwhile, UGC has become a more critical source of information for consumers due to its richness, diversity [3], and authenticity [4] compared to traditional advertising and official sources. One industry that relies heavily on communication technologies is tourism. Since UGC can influence brand image creation and consumer behaviour [3, 5], social media is earning a leading role in the multiphasic travel stages, from pre-, during-, to post-travel experiences, for information gathering and sharing [1]. Recent literature further reinforces that a destination's online image positively affects consumer behaviour in increasing one's intention to visit, revisit, or recommend the destination [5–7]. Notably, destination image has become a multifaceted concept by considering both the attributes of a destination as well as the sum of beliefs and impressions a tourist has [8]. Seeing that official information provided by destination marketing organisations (DMOs) no longer has absolute control over image creation [5], DMOs are suggested to be aware of tourists' perception of the destination in order to develop quality marketing campaigns [2]. This can be determined through UGC analysis, which enables marketers to view destinations from tourists' perspectives and discover what they are most interested in [9]. Yet, despite the importance of image congruence [10], scholars in the field of destination marketing mainly analyse the image created by tourists [2] or DMOs [11] rather than comparing both contexts at the same time [12].

To close the aforementioned research gaps, this study aims to identify destination image on social media by analysing both UGC and content published through official tourist board channels. With a particular focus on Instagram, one of the many channels heavily used by (young) tourists [3], this study adopts the destination Saalbaach–Hintergelmm in the Alpine region of Austria as its research context. Specifically, through the use of netnography supported by machine learning approaches, this paper evaluates whether tourists' image of the destination corresponds to the image the DMO attempts to promote. Meanwhile, this study also examines how UGC can be used to plan and develop social media marketing activities for DMOs. Shaping destination image is vital for official institutions in order to attract tourists, consumers, events, and investors [2]. This study advances methodological approaches by using machine learning techniques to shed light on the differences between projected and perceived destination image on Instagram. By outlining the textual and visual content analysis, this research contributes to tourism marketers optimising social media storytelling and marketing strategies.

#### 2 Literature Review

The ubiquity of communication technologies and social media has changed users' attitudes and behaviours, and provides everyone with an opportunity to generate online content. Social media platforms such as Instagram, Facebook, and Snapchat involve common instances of UGC in tourism, where users can create their own content in the form of texts, images, comments, or messages [10]. In the tourism industry, UGC not only reflects the preferences, beliefs, and emotions of tourists regarding their travel experience [13], but it also shapes the image of a destination. As tourists actively look for inspiration and explore other users' experiences, the association of images delivered through pictures or texts on social networks plays an important role in influencing visitor satisfaction and future behaviour [14].

Due to globalisation and increasingly fierce competition, various branding strategies are now being developed in most destinations [15]. One way to position a destination better is to adapt to the development of online communication tools. More specifically, seeing that social media has weakened the traditional role of DMOs as a leading source of information for visitors [16], marketers nowadays are inclined to include social platforms in their marketing activities. In doing so, DMOs can co-create content with tourists so as to maintain competitiveness and gain online visibility [17, 18]. The significance of DMOs' social platforms is evidenced by the fact that it is embedded in tourist activities' planning processes [19]. The delivered content can support visitors during their travel [18], thereby reinforcing the need for DMOs to optimise social media marketing strategies and to face high competition in the tourism industry [20].

Amongst the various available channels, Instagram has not only been embraced by tourists as a trendy platform [4] but is also well-liked by marketers to create compelling marketing strategies [11, 21]. Characterised as a highly visual platform, approximately 1 billion monthly active users and 95 million photos shared per day on Instagram were recorded, as of 2020 [22]. In tourism marketing, the implication of online photography is to shape a positive perception of a particular destination. Moreover, this platform offers a space where the projected and perceived destination image are intertwined. The UGC as an agent of perceived destination image formation is a key factor in the destination choice process. Thus, it is crucial to consider the effect of UGC on the destination image when setting up marketing strategies.

A number of studies focus on comparing the destination image positioned by official sources with the destination image perceived by users of various kinds of social media, by applying content analysis. For example, the studies conducted by Stepchenkov and Jean [23] and Tussyadiah [24] compared images gathered from the DMO website and Flickr, while Song and Kim [25] contrasted the image of Guangzhou, positioned by the DMO on Twitter, with its image on Pinterest. The relevance of the comparison between the promoted destination image and the destination image revealed from the UGC has been proved by Jiménez-Barreto et al. [6] and Chang J-H, Wang S-H [26]. These studies confirmed that congruence between the projected and perceived destination images decreases the possible deviation of expectation from reality, thus affecting brand credibility, tourist satisfaction, and visit intentions.

Despite the fact that the destination image has been the subject of debate since the last century [27], content analysis for destination image marketing insights is fairly novel. The current study complements the body of work on this topic by applying content analysis combined with the use of machine learning.

#### 3 Methodology

To explore destination image presented by DMOs and tourists on Instagram, this study applied netnography as a research method. Additionally, the Alpine resort Saalbach– Hinterglemm in Austria was chosen as the research context. The following section outlines the data collection and analysis procedure.

#### 3.1 Data Collection

Data was collected from public posts shared on Instagram using Phantombuster, an automated data crawling software. Figure 1 outlines the data collection process. For the collection of UGC, posts captioned with the hashtag #saalbachhinterglemm were extracted. Although the destination Saalbach–Hinterglemm has a notable summer and winter season, this study was narrowed down to include solely the posts from the 2019/2020 winter season so as to compare the posts published by users and the DMO within a defined time frame. In addition, only posts written in English were considered. The language recognition was performed in Python using the langdetect module.

Next, Phantombuster was used to obtain publicly available information about Instagram users who published the collected set of posts. This step was to filter out business accounts, whose posts might have been of commercial nature. The filtering process included the removal of profiles with the words "saalbach", "hinterglemm", "leogang", and "fieberbrunn" in the profile name or the bio, and the removal of profiles with an enlisted business email. Because the neighbouring villages Leogang and Fieberbrunn are parts of the same ski resort, those keywords were included. Ultimately, the filtering process resulted in a final set of 1,448 posts. A similar procedure was performed to obtain the Instagram posts published by the DMO in which a total of 2,091 posts shared via the official Tourist Board Saalbach-Hinterglemm account (@saalbach\_com) were retrieved. Likewise, the posts were filtered to include the winter season and posts written in English, reaching a final number of 85 posts.

Fig. 1. Data collection process for UGC (left side) and DMO (right side) Instagram posts.

#### 3.2 Data Analysis

For further analysis, both the DMO's and the users' Instagram posts were split into two elements (images and textual description), and the data was organised into four datasets: (1) DMO image annotations, (2) UGC image annotations, (3) DMO textual description, and (4) UGC textual description. The textual description refers to the caption of a post. To analyse pictorial content, Google Vision API was used to retrieve textual annotations of the images.

The annotations and the textual description were analysed with Orange 3, an open source machine learning software that enables textual data to be converted into features (i.e., vectors) [28]. In this research, the textual description and annotations of the images were treated as documents. As such, document embedding, which generates a vector for the document by embedding the words in the document [29], was applied using the pre-trained fastText model [31]. K-means clustering was then applied to group similar data points (vectorised annotations or vectorised textual descriptions) into clusters [32]. This method in particular was chosen to examine whether the posts could be divided into distinct clusters according to their content.

When applying the k-means algorithm, silhouette scores were calculated to identify an optimal number of clusters and to assure the reliability of the content analysis results. After obtaining the clusters, t-SNE dimensionality reduction was used for cluster visualisation in a scatter plot. The scatter plot thus presents the size and layout of the clusters in addition to which DMO posts overlap with the ones published by tourists, and, more importantly, where the DMO lacks posting coverage. The entire process was performed in the same manner for each of the four datasets mentioned above.

Subsequently, content analysis was carried out to identify emerging themes amongst the posts. A classical NLP pipeline [33] with lowercasing, removing stopwords, lemmatizing etc. was applied to pre-process the corpus. It included naming and categorising all the obtained clusters for both DMO and UGC annotations and textual descriptions based on TF-IDF (term frequency–inverse document frequency) weighting. Although state-of-the art NLP approaches such as BERT are available for text representation, studies show that for simple classification and clustering tasks conventional methods such as TF-IDF provide equivalent results [34]. Specifically, TF-IDF quantifies a word in the documents that implies the significance of a word to a document in the corpus. The results of each cluster were visualised with word clouds to gain a better understanding of data interpretation. Finally, the cluster categories were compared to find similarities and differences between the DMO and UGC Instagram posts. In this way, it was possible to assess the extent to which the DMO presentation on social media matched those of the users' destination image.

#### 4 Results

#### 4.1 Comparison of the DMO and UGC Image Annotations

The results suggest 8 clusters for the DMO image annotation and 3 clusters for the UGC annotation according to the silhouette scoring. Each of the 8 identified DMO clusters were named and categorised based on TF-IDF (i.e., words contributing to a cluster the most) as the following: Mountainous winter landscape (5 clusters); Winter sports (1 cluster), and People and events (2 clusters) (see Table 1). However, the clusters vary in size; clusters 1, 2, and 3 are more extensive than other clusters. Thus, the primary number of images represents the winter mountain setting and the slopes, whereas a smaller number of images portray a person or a group engaged in winter activities. Therefore, it can be concluded that the DMO concentrates mostly on creating a winter mountain ambience.

The same procedure was conducted for UGC annotations. Although UGC images' sample size is larger, the content seems to be more homogeneous. Thus, only 3 clusters were obtained. The clusters were named as follows: People enjoying winter sports; Winter sports; Mountain landscape (see Table 1). Compared to the amount of nature represented on the DMO images, the UGC images feature mainly people.

Table 1. Categorisation of clusters for DMO and UGC annotations.

Fig. 2. Scatter plot of DMO and UGC overlaying images.

Next, this study visualises cluster layout/overlays (see Fig. 2) to which the scatter plot revealed 4 clusters. The cluster marked in red refers to the DMO image annotations, whereas the other 3 clusters reflect the UGC annotations. The plot indicates that the red dots representing the DMO posts overlap across the 3 UGC clusters, suggesting that the photos from the DMO match pictures posted by tourists. Yet, because several DMO photos in the orange and the green cluster do not overlay with UGC, further analysis was conducted to see which photos posted by tourists are not covered by DMO.

Cluster 4 (orange) represents the UGC content of People at the ski resort. Since the area involving cluster 4 does not overlay with cluster 2 (red colour), this was analysed further. The findings show that these photos refer to leisure, entertainment, and people, with the most prominent annotations being selfie, eyewear, helmet, smile, equipment, drink, beverage, clothing, etc. In other words, this sub-cluster represents the photos of people in their ski clothing taking pictures during their refreshment break at the restaurants and ski-huts on the slopes (see Fig. 3).

Cluster 3 (green) relates to winter sports, with photos depicting people during their skiing activities or engaging in other winter sports. The analysis of the DMO photos has similar categories (Winter sports; Ski equipment), meaning that the DMO posts also encompass this category. This is confirmed by the overlaying cluster 2 (DMO) and cluster 3 (UGC). However, the scatter plot implies that the photos in this category are represented to a far lesser extent by the DMO posts than the UGC posts.

Cluster 1 (blue) represents the UGC posts that overlay the most with those from the DMO (see Fig. 4). These photos represent the mountain landscape and show mostly mountainous panoramas and skiing resorts in a winter setting. The sub-clusters with no overlaying DMO posts are mostly photos of the Alpine village or the property and accommodation, especially during the night hours, as well as snowboarding and selfies, or photos of the people on the slopes in the skiing equipment doing winter sports.

Fig. 3. Examples of UGC images not overlaying with DMO images.

Fig. 4. Examples of overlaying UGC and DMO images.

### 5 Comparison of the DMO and UGC Textual Image Description

The comparison of DMO and UGC textual image description was conducted in the same manner as described for DMO and UGC annotations. Overall, key topics for the DMO include winter and snow, the promotion of Salzburgerland and Skicircus areas, the slogan 'Home of lässig', and the events FIS Alpine World Cup in Saalbach and the Freeride World Tour. UGC has a broader topic of a winter wonderland and the mountains, snowboarding and skiing activities, and a seemingly well-accepted slogan of the ski resort 'Home of lässig'. Overall, the results reveal a 5-cluster solution for the DMO and a 2-cluster solution for UGC. Similar to image annotations, there is a lower number of clusters for UGC textual content than DMO's, implying that UGC is more homogeneous and random, whereas the DMO posts are rather structured and planned.

The following categories for the DMO clusters were revealed: The view from the local mountaintops, Nice conditions & invitation to come, Promotion of the FIS World Cup and the Freeride World Tour, A perfect day (see Table 2). Cluster 2 (Nice conditions & invitation to come) is the largest and represents most of the DMO's content when it comes to textual descriptions. Cluster 3 contains a single post with no significant difference in the content; thus, it was assigned to cluster 2.

The two clusters from the UGC textual descriptions are approximately equal in size with the following categories: Appreciation of nature and the winter activities during the winter holidays at the destination and Fun with friends and family (see Table 2). Similar to the analysis with the image annotations, the DMO textual descriptions highlight nature and landscape, while UGC focuses more so on activities and people.

Table 2. Categorisation of clusters for DMO and UGC textual description.

#### 6 Discussion

This study aims to compare the extent to which the marketed destination image corresponds to tourist experiences on Instagram. Specifically, UGC suggests topics such as fun, social interaction, casual environment, outdoor activities, and winter sports. These themes indicate that tourists perceive the resort as a relaxing and casual destination. In comparison, some other ski resorts build an image of a high-end resort, party destination, or family resort.

This study presents congruency between the projected and perceived destination image. Hence, this research affirms the importance of tourists' destination brand image, as mentioned in previous literature [6, 10, 12]. If tourist experiences correspond to the stories delivered by DMO, the brand credibility increases and consequently, user intentions to visit, revisit, or recommend the destination also increase [6]. Moreover, tourists create an emotional bond with a destination according to its personality by choosing the brands or destinations that fit their own style [18]. Destination personality is usually described using human characteristics based on the brand experience, such as cool or exciting [35].

This research reveals tourists' acceptance of the destination's logo Home of lässig [Home of cool]. The critical aspect of the DMO's social media activities is communicating the values that determine the destination's personality and thus facilitating this emotional bond with the visitors [30]. In this case study, the communication of the destination's personality can be seen in the DMO's activity and posts. Moreover, the positive response of the users to such communication can be witnessed. Thus, this research confirms the impact of destination's personality communication so that visitors can identify with a destination.

Furthermore, the comparison of the DMO with users' posts reveals that the DMO generally delivers mostly nature and landscape-related content, whereas tourists tend to include both nature and people in their posts. The images for both UGC and DMO could be categorised into three themes: winter mountain atmosphere, winter sports, people. However, the majority of the DMO posts presented the slopes and the snowy mountains in the first category. A great deal of UGC posts relates to images of socialising, be that either selfies, people during winter activities, or people at a restaurant, bar, or in the street. Such content could be interpreted the following way: tourists come to the resort not only to enjoy winter sports but to also experience the immersion into a warm and cosy environment; to enjoy social activities with friends and family, take selfies, enjoy contemporary accommodation facilities, and visit trendy restaurants where they can talk about various topics and try delicious dishes. Undoubtedly, the main reason to visit a ski resort is to engage in winter sports, but without these add-ons, customers would be missing out on a peak experience [36].

#### 7 Conclusion

This work provides deeper insights into destination image creation and user behaviour on social media and contributes to understand the effect of social media on DMO marketing strategy development. According to existing literature, social media marketing efficiency has been measured by user involvement: their interaction, influence, and intimacy [6]. DMOs most commonly measure the return on investment of social media effectiveness by counting the number of 'followers', 'likes', and the rate at which those numbers increase [1, 6]. Typically, netnographic research provides no insights on how the brand positioning strategy should be conducted. Thus, this study incorporates a qualitative analysis instead of the measurements mentioned above, thereby offering an alternative approach to the destination brand image assessment. This attempts to provide an in-depth insight into consumer behaviour on social media. The findings suggest values and beliefs embedded in the posts instead of the quantifiable interacting aspects. In that case, market research, such as a visitor survey combined with a netnographic study, might be helpful.

Furthermore, this study provides several implications for DMOs by analysing similarities and differences between the Instagram posts created by tourists and the DMO. Although the projected image highly matches tourist experiences, not all the UGC posts' themes are covered by marketers, and vice versa. Such insights indicate opportunities for the improvement of a DMO's marketing strategy regarding their storytelling. A DMO could utilise the study's findings and adjust their marketing strategy by promoting the services and content appearing in the visitors' posts. For instance, an image of a cup of coffee amidst a winter scenery with an attractive caption could influence a prospective visitor by creating anticipation of fulfilling this desire [9].

Including and highlighting additional activities the destination has to offer aside from primary ski activities would be a strategic decision regarding the DMO's marketing activities promote the destination. For example, an additional offer may refer to ski huts, local dishes or activities such as night tobogganing.

Further managerial implications include promoting properties on the DMOs social media channels. The importance of a professional marketing strategy lies in the fact that DMO's social media activities influence the destination image and the intention to visit [7]. Essentially, this research presents deeper insights into tourist experiences at the destination and confirms their impact on adding value to the destination image.

However, this research is, naturally, not without its limitations. First, the analysis was not incorporated through the most commonly used performance indicators (e.g., user engagement), nor did it provide quantifiable data (e.g., the exact percentage to which the perceived user image corresponds to the projected destination image). For future research, we encourage an assessment of user engagement in regard to DMO and UGC matching content. Similarly, a quantitative measurement of destination image perception and intention to visit regarding content congruence is recommended. Saalbach-Hinterglemm has a clear, one-dimensional profile as a ski destination. For more diverse destinations, future studies could perform multilingual text analysis utilizing BERT in order to provide deeper insights. Despite its exploratory nature, this study offers valuable insights into the role of UGC on destination brand image.

#### References

Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

### Topic Modelling of Tourist Dining Experiences Based on the GLOBE Model

Roman Egger , Angela Pagiri, Barbara Prodinger(&) , Ruihong Liu, and Fabian Wettinger

University of Applied Sciences Salzburg, Puch/Salzburg, Austria<EMAIL_ADDRESS><EMAIL_ADDRESS>
Abstract. The needs of travellers vary across cultures. When it comes to culinary aspects, there is a strong connection between gastronomy and culture. To optimise service offerings, investigation of the essential aspects of dining experiences in relation to cultural backgrounds is of great importance. In the age of digitalisation, tourists share their dining experiences throughout their multiphasic travel journey via online platforms. By considering nine distinct cultural backgrounds, this research aims to investigate tourist experiences based on TripAdvisor restaurant reviews through topic modelling, using the city of Salzburg as its study context. Depending on one's cultural circumstances, the findings demonstrate that the most important aspects include staff, food-menu items, value for money, restaurant physical appearance, food authenticity, overall service, menu offers, food quality, atmosphere, and recommendations. This study advances the state-of-the-art knowledge of societal culture as a variable in the target market analysis of restaurant customers. Findings allow restaurant owners, other tourism service providers, and destination management organisations to analyse and adapt their service offerings and strategies accordingly.

Keywords: TripAdvisor Dining experience Societal culture GLOBE

### 1 Introduction

Visitors from different countries vary in their service expectations and travel behaviours due to cultural backgrounds, which subsequently influences their travel experience [1, 2]. Thus, identifying those needs is essential in order to contribute to up-todate services and products [3]. Literature has provided insights on service quality and customer satisfaction in a restaurant setting based on widely used models such as SERVQUAL [4] and DINESERV [5, 6]. However, in this process, guests fill out a predefined questionnaire before and after the service, leading to mostly small sample sizes caused by the challenge of persuading guests to participate [7].

Seeing that the rapid development of information and communication technologies allows visitors to share their experiences in the form of user-generated content (UGC) on various online platforms [8], researchers and marketers can take this as a valuable opportunity since these technologies facilitate deeper access to a broad range of insightful data [9]. For instance, existing studies have examined TripAdvisor reviews to define the sentiment of customers' feelings towards dining experiences [10] and online ratings on Yelp to uncover different motivations as well as the satisfaction of customers coming from the USA and China [11]. Such investigations refer to predefined themes from existing service quality models to unveil customers' feelings, satisfaction, or perception of a dining experience and then correlate it to countries or continents. A worldwide cross-cultural comparison is, however, widely missing. Hence, this research seeks to contribute to the field of dining experiences by analysing online reviews from a bottom-up approach in order to discover which aspects of the dining experience are critical for visitors in relation to their cultural backgrounds.

To achieve the stated objectives, this study adopted the city of Salzburg as its research context for the following reasons: Salzburg ranked first on the "Best in Travel 2020" list of the world's most attractive cities thanks to its historical sightseeing spots and local cuisine [12]. In the summer season of 2019, nearly 2 million arrivals and more than 3 million overnight stays were recorded in the city of Salzburg. In addition, Salzburg attracts international visitors from a wide variety of countries, including Germany, followed by the Netherlands, Arab countries, Czech Republic and USA [13], currently gaining momentum again after the COVID-19 pandemic. In this study, we apply a mixed method approach by conducting data visualisation, data mining, and topic modelling techniques, to transform unstructured online reviews into interpretable patterns.

### 2 Literature Review

### 2.1 Tourist Dining Experience

During this era of the experience economy [14], businesses should design their products and services while also taking into consideration the full range of effects that can be evoked from an interaction between consumers and service offerings [15]. This is particularly important in the tourism and hospitality industry, which is heavily based on experiences [16]. In the context of restaurants, scholars have established different service quality models to identify elements that are influential to customers' satisfaction and experiences, among which the SERVQUAL instrument represents the most widely used model [4]. More specifically, service quality is evaluated based on five dimensions, namely, reliability, responsiveness, assurance, empathy, and tangibles [4]. Despite its popularity, the SERVQUAL model was primarily developed for banks as well as credit card, repair, maintenance, and telephone companies [4]. Therefore, since scale items should be adjusted to fit specific industries [17], scholars subsequently developed the DINESERV model so as to investigate visitors' expectations of quickservice, fine-dining, and casual-dining businesses [18].

A modified version of the DINESERV model showcases further factors of customers' expectations and perceptions at restaurants. The implementation of the overall categories, price and satisfaction, explains customers' thoughts on paying more than expected and the price of food items, while the satisfaction of the dining experience can be confirmed through customers revisiting the restaurant and in the recommendation itself. Other tangible factors include a clean parking area and nice building exterior, restaurant decoration, easily readable menu, comfortable seating, clean dining area, and neat staff [7]. Concerning the environment, evaluation of physical and human surroundings in a restaurant emphasises the aesthetics of the facility, ambiance, table setting, lighting, and the service staff [19]. Moreover, current literature reinforces that, in order to achieve high customer satisfaction, the interaction between customers and employees should not be overlooked [20]. In addition to the service itself, beverage and food attributes are also found to be critical factors in relation to customer fulfilment and post-dining behavioural intention [21]. Today, tourists have more opportunities to share their holiday experiences on social networks [10], allowing individuals to express their thoughts and opinions and make them accessible to the online global community [22] via review platforms such as TripAdvisor. Not only do these review platforms play a key role in tourists' decision-making processes [23], but they also provide managers with a tremendous amount of data that can be used to better understand customers [10] through advanced text mining techniques [24]. A recent study, for instance, explored customers' feelings shared on TripAdvisor when dining in local restaurants [10]. The importance of location and service quality was explored using topic modelling; however, such experiences cannot be standardised, nor do they apply to everyone. Albeit the significance of acknowledging that expectations regarding food, environment, and interpersonal interaction vary across cultures [11], understanding customer experiences from different countries remains scarce.

### 2.2 Cultural Dimensions and Clusters

To classify people with different cultural backgrounds, one of the most common approaches is based on Hofstede's cultural dimensions theory [25]. This cross-cultural communication framework covers the dimensions of individualism-collectivism, uncertainty avoidance, power distance, masculinity-femininity, and long-/short-term orientation. Subsequently, other researchers modified and transformed the Hofstede model into the GLOBE model [26, 27], with the dimensions uncertainty avoidance (fear of ambiguity), power distance (acceptance of an unequal distribution of power), institutional collectivism (more validation of broad societal interests than of individual goals), in-group collectivism (loyalty towards families and organisations), gender egalitarianism (equal treatment of genders), assertiveness (level of directness, forcefulness, or aggression), future orientation (planning, delaying gratification), performance orientation (appreciation for setting and reaching goals), and humane orientation (fairness, generosity, kindness) [26, 28, 29]. In order to make the GLOBE model applicable for practical use in multinational societies, a model of regional clusters across the world was developed as well. The clusters and their characteristics [28] are outlined in Table 1 below.

Table 1. The GLOBE model.

### 3 Methodology

### 3.1 Study Context

The city of Salzburg thrives from the tremendous amount of income generated by the gastronomy branch, with over 3,502 culinary businesses currently running in Salzburg [30]. Thus, with highly concentrated tourists, this destination offers sufficient data for this study to explore tourists' perceptions of dining experience from different cultural backgrounds by mining their content with regards to travel expectations, motivations, and satisfaction on TripAdvisor.

### 3.2 Data Collection, Pre-processing, and Analysis

The web scraping software Octoparse was used to collect restaurant reviews and attributes from TripAdvisor. Restaurant attributes include names, review content, restaurant URLs, published dates and reviewers' locations. All available restaurant reviews, written in English, from the city of Salzburg were scrapped, resulting in 27,626 reviews. This study selected only reviews published between May 1 and October 30, 2019, leading to a total of 1,901 reviews. This timeframe was chosen because of school holidays within and around Austria, where high tourism activities take place, and to view data before the outbreak of the COVID-19 pandemic. Afterward, based on reviewers' nationalities, all reviews were classified into different cultural clusters according to the GLOBE model. Customers who did not disclose their locations on TripAdvisor were removed, resulting in a final dataset consisting of 1,461 reviews.

Next, Orange 3, an open-source machine learning toolkit, was applied for data preprocessing and analysis. To transform unstructured reviews into structured forms for analysis [31], the following three steps were conducted: (1) tokenizing texts and turning all the text into lowercase, (2) removing punctuations, numbers, stop words, and, in addition to general stop words, a list of custom stop words specifically developed for this study, and, lastly, (3) normalising words by removing suffixes.

In order to discover hidden topics in online reviews, this study applied Latent Dirichlet Allocation (LDA), one of the most popular topic modelling techniques in tourism and hospitality [32]. LDA was conducted on each of the cultural clusters so as to uncover a corresponding set of attributes or themes through the corpus-based guest reviews. To determine the number of topics in each cluster, multidimensional scaling was applied to analyse each topic's distance between each other and to investigate duplicate or recurring topics. Thus, different clusters yielded various numbers of topics. Finally, a list of keywords, which represent a topic in the topic modelling process, was used as a reference for labelling its representative topics. Subsequently, the extracted keywords of the respective geographical areas were vectorised using document embedding (fastText), followed by a dimensional reduction using tSNE (Perplexity = 15, Exaggeration = 1, PCA components = 25, Normalised Data, and preserved global structure) in order to visualise the GLOBE spaces. The optimal tSNE hyperparameters were chosen after a visual inspection with the Tensorboard Embedding Projector.

### 4 Findings

### 4.1 Overview of the Topic Modelling Results

Table 2 outlines the ten identified topics generated from LDA for a total of nine cultural clusters, as the Sub-Saharan Africa cultural cluster was dropped due to scarce data sampling.

Table 2. Identified topics per cultural cluster.

The naming of the topic was based on a list of keywords contributing the most to a specific topic. Additional topics/themes were also added due to a prevalent theme, which had not been previously found via topic modelling, being discovered in the reviews. Yet, it is important to note that the number of reviews was not equally distributed and may have influenced the number of the extracted topics. Overall, Staff, Food Menu Item, and Value for Money presented themselves as the top aspects when tourists shared their dining experience.

### 4.2 Topic Modelling Results per Cultural Cluster

The topics per cultural cluster shown in Table 2 are based on up to 5000 keywords. Figure 1 shows the topics per cultural cluster after tSNE dimensionality reduction and locates them on a map. Interestingly, the word embeddings of these keywords reflect the proximity of the individual GLOBE spaces very well. As such, the two Asian clusters can be seen grouped very close to each other on the left side, while the Middle East is strongly separated from all other areas on the bottom left, and the AngloAmerican area on the opposite top right is also entirely homogeneous. In between, Latin Europe and Latin America are separated but in close proximity, and the European regions are somewhat mixed but still clearly recognisable. This confirms that the cultural features described in detail below can indeed be clearly teased apart from each other and can be perceived as their respective typical characteristic.

Fig. 1. Topic keywords word embedding across GLOBE cultures

Anglo For Anglo cluster, the staff plays an important role which can be seen from several comments (e.g., "The chef was very accommodating to our gluten free needs" and "The staff was friendly and attentive"). Food menu items display a high degree of significance and seen to be followed with critiques and recommendations such as "Choice of 3 dishes, had the sardine pasta, and it was fantastic". This observation is consistent with the GLOBE Model findings of the Anglo cluster which possess a highperformance orientation, showing appreciation for an achieved standard. This cluster is attentive to a restaurant's physical setting which shares similarities with the Southern Asian cluster. Different from the Southern Asian cluster, the Anglo finds the restaurant setting and location more important than the décor, which is represented by (e.g., "We ate outside and had a delightful dinner" and "Not too far from the centre of the city").

Confucian Asia For this cluster, value for money is an important aspect, observed in "We think the pricing of the food was reasonable". This characteristic is similar to the Southern Asia cluster, where the price paid outweigh the food portion. Also, Staff is considered an integral part, proved by "The owner is very friendly". Congruent with the GLOBE model, the performance orientation, more specifically, their deliberate expression of appreciation to the staff seems up to par. Meanwhile, food authenticity is another prevalent factor, which can be observed in the excerpts: "We went there for dinner and food is good traditional Austrian" and "Very authentic and delicious Korean food!". It is worth noting that, interestingly, Confucian Asian tend to search for their own culture's cuisine, and it should also meet their authenticity expectation. This is consistent with the GLOBE model's high score of institutional and in-group collectivism, by showing loyalty to their own origins despite being outside of their home country.

Southern Asia This cluster considers the physical restaurants appearance most important, emphasising on the decor or interior, as seen in "richly decorated" and "friendly US-style diner". Food menu items are another prevalent topic which can be seen from the specific mentions of food, such as "Dal Tarka", "Beef Pho", followed by a recommendation to visit, echoing this culture' humane orientation nature. "Reasonable rate" and "value for money" represent value for money aspect, which is also mentioned by the Confucian Asia, Latin Europe, and Eastern Europe. Interestingly, not only the attitude of the staff, but also on the appearance and facial expression is important, (e.g., "Served by a bearded guy with several tattoos" and "The owner around with a very unhelpful angry expression"). Lastly, several dissatisfied expression emerge, "lousy service" and "aggressive staff" in addition to positive experience reviews such as "comfort", "the service was very friendly", and "humble servings".

Eastern Europe Interaction with the staff and their friendliness is crucial for this cluster, as seen in: "The waiter in the lounge was very grumpy" and "That manager was very impolite". Notably, the presence of negative reviews towards the staff are in line with the characteristics of assertiveness given in the GLOBE model. Nevertheless, this cluster appreciates food authenticity, "I would recommend it for anyone visiting Salzburg and wants to enjoy a traditional Austrian dish". Food menu items with implicit reference for or against recommending the place also emerge, as seen in: "Very nice options for platters to have with your wine" and "If you are looking for a great schnitzel off the beaten path, this is the place". Finally, value for money is a vital aspect for the Eastern European contrasting with the Asians where price sensitivity outweighs portion generosity, proved in "It's a little pricey but, given the rest of the prices in Salzburg".

Latin America For Latin Americans it is important for businesses to deliver their brand promise in terms of (food) authenticity, for example, "Make sure you go to this typical Austrian restaurant. Serve good Austrian food" and "The food is really good. Austrian dishes and drinks". Another salient aspect is the menu offers, e.g. available options, types of drinks, and cuisine types (e.g., "The menu was excellent- it was hard to decide what to order" and "All kind of seafood and in any possible way"). The findings show consistency with GLOBE model in terms of the low score in performance orientation (whether people are rewarded for delivering good performance) due to the fact that important dining aspects revolve around the food itself rather than the staff.

Germanic Europe The appearance and location of restaurants are evidently important aspects for this cluster, as seen in "One of the most modern restaurants in Salzburg" and "The restaurant has a very good flair". This implies that this culture appreciate the comfort and pleasant atmosphere. Concerning the staff, attentiveness and attitude are the most appreciated traits, for instance, "We were greeted by a nice waiter who showed us to our table" exhibiting deliberate expression of appreciation which is congruent with their high performance orientation's GLOBE characteristic. Moreover, menu offers and food quality (e.g. "Excellent meat dishes. Good selection of drinks") are important but inconsistent food availability is not appreciated, as seen in "Limited menu". The quality of the food served in terms of flavour, presentation, and ingredients are also notable, "The creamy spinach was so good and the meat had a high quality".

Latin Europe Value for money is the most important aspect, as seen in "Good service at a reasonable price" and "Pizzas are really huge, tasty and at a very good price". Although this is consistent with the Southern Asian and Eastern Europeans, the Latin Europeans emphasise price points rather than the food generosity. Food menu items are mostly followed with a critique, for instance "Burger was good though not amazing" and "We chose white asparagus which was excellent". This cluster recognises service as a significant factor, encompassing larger spectrum of a dining experience: staff-, food-, and restaurant-related, seen in the generality of review contents such as, "The place is nice and the court is a great place, but the food was mediocre (restaurant- and foodrelated)" and "The staff is very friendly and the wiener schnitzel was one of the best we've had (staff- and food-related)".

Nordic Europe The overall service (e.g., "service is immaculate", "super service", and "quick service") with a strong focus placed on services provided by the staff emerge, as seen in "The two women who run it are super kind and really cares about their food". The flavour, ingredients, and the presentation thereof are key factors for this cluster, for instance "Traditional food with lots of flavour!". Moreover, menu offers are equally important, proved by frequent references to modern Austrian kitchen, vegetarian food, local wines, home-brewed beer, and gluten-free beer, e.g. "Amazing little beer garden with solid food and amazing home-brewed beer" and "Nice place for some typical Austrian food, gluten-free beer available and a few but very tasty food options". Lastly, the atmosphere is proved to be as important, as seen in "historical environment" and "hidden gem", which is congruent with the GLOBE model's uncertainty avoidance characteristic, since authentic local atmosphere meets this cluster's expectations.

Middle East Food menu items are of great significance for this cluster (e.g., "Shrimp pizza at the bar, and it tastes lovely" and "Beautiful wholesome food"). The interaction with the staff is as influential, as seen in "The host has been the perfect one in all way" and "The owner of the restaurant and staff are friendly and accommodative". Recommendations are significant for the Middle Eastern cluster, for instance "We went to this restaurant on recommendation" and "We found this restaurant from TripAdvisor". This finding transpires the common practice among Middle Eastern tourists to go to places upon recommendation and correspondingly recommend places to others upon dining satisfaction. In line with the GLOBE model, this aspect displays a certain degree of consistency for high in-group collectivism since, by giving honest opinions about their experiences, this behaviour shows loyalty towards their own family or organisation.

### 5 Discussion

Seeing that various aspects of touristic experiences, such as dining or visiting sights, can be sourced from online review portals, and connections to a place of origin or culture can be drawn from the differences in behaviour [33], this study analyses online restaurant reviews so as to make generalisations regarding different cultures. In this way, when addressing and catering to a certain country or culture, one can resort to a set of recommendations on what specific aspects they tend to pay attention to. Overall, the most important aspects related to customer dining experiences are staff, food menu items, value for money, restaurant physical appearance, food authenticity, overall service, menu offers, food quality, atmosphere, and recommendation.

The study's findings partly differ from the literature in that food was mentioned regularly in reviews, with food even being considered the most important factor for those who enjoy dining. Unlike the dimensions in the SERVQUAL and DINESERV model, which focus more on the interaction between customers and employees rather than the products themselves (e.g., food items), this research is consistent with other scholars who emphasise that attributes of food, regarding the quality, freshness, tastiness, and temperature, are seen as the most influential criteria among customer fulfilment and post-dining behavioural intention [20, 21].

Yet, notably, the priority of these aspects varies across cultures. This study shows that societal cultures can provide valuable insights, e.g., for gastronomy businesses when trying to target a certain market. Moreover, it might aid in guiding employee training, especially in regard to the specific treatment of certain target groups (grooming recommendations, welcoming rituals, etc.). The analysis further reveals that societal culture might be a new variable in market research, especially in target market analysis, in addition to established ones such as demographics and lifestyle milieus. Finally, this study supports results from recent literature, suggesting that machine learning can give valuable insights by processing large amounts of UGC from review sites [33].

To conclude, this study is novel in that cultural background was incorporated, using an established scientific concept, namely, the GLOBE clusters. Different from previous literature focusing on limited cultural groups [33], the findings of this research allows for the generalisation of all regions within a given cluster. By using machine learning and drawing connections to the culture of customers, this study concludes that analysing online restaurant reviews can give valuable insights for professionals in the field.

### 6 Conclusion

This research contributes to the tourism industry through the use of machine learning techniques, thereby showcasing the possibilities of transforming UGC into structured patterns so as to reveal tourist experiences shared online. As such, the revealed insights provide restaurant managers with the exact gastronomical preferences of their target groups, which, in turn, can be used to optimise business strategies and service offerings. On a wider scale, this study is also beneficial for destination management organisations to promote gastronomy in foreign countries. More specifically, destination marketers now have the opportunity to check the exact aspects of a dining experience that a certain cultural cluster may be interested in and tailor promotional texts, images, and videos accordingly. Ultimately, this research expands upon the existing knowledge of the use of text mining and machine learning to process and analyse large amounts of user-generated data in tourism contexts.

Regardless, this study is not without its limitations. First, the sample was narrowed down to include English reviews only, and the city or country of residence was taken from TripAdvisor. As such, the assumption that a reviewer belongs to a particular cultural cluster is solely based on his/her stated place of residence. Whether or not that region represents their "true" culture, or if they were merely expatriates living in a certain place at that time, cannot be validated. For future research, it is recommended to investigate the preferences of the cultures from where large data density, that represent all 10 GLOBE cultural clusters, can be obtained, for instance major cities e.g. New York or Tokyo. This will increase the robustness of the cultural cluster analysis. Moreover, further studies could explore other aspects of tourism, such as accommodation or attractions, that can benefit from this approach in similar ways.

### References

368 R. Egger et al.

Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

### **Content-Based Recommendations for Crags and Climbing Routes**

Iustina Ivanova(B) , Marina Andri´c, and Francesco Ricci

Free University of Bozen-Bolzano, Bolzano, Italy<EMAIL_ADDRESS>
**Abstract.** Climbing is a popular sport for active tourists and recreational sportsmen. Alpine climbing areas, such as the Alps, can attract tourists from all over the world. Various websites, mobile applications, and books are used by climbers to obtain information on important aspects of the available climbing routes, including their properties, location, and especially their difficulty. Considering this large amount of information and options, it is in reality difficult for climbers to properly select which routes to climb. Hence, we propose recommendation technologies aimed at supporting climbers in this decision task. The developed system prototype constructs a climber's profile with preferences derived from climber's logbook data collected by a mobile app. Then, the system can recommend suitable crags and climbing routes within the selected crags. The designed interface and the basic computational models for such a system prototype are presented. The proposed technology aims at complementing existing electronic climbing guidebooks and providing decision support to climbers.

**Keywords:** Climbing tourism · Difficulty assessment · eTourism · Recommender system · Outdoor tourism decision support

#### **1 Introduction**

Nowadays, there is a growing interest in sport climbing. Specifically, outdoor climbing has become a popular tourism activity for novices and experts. In some countries, such as Italy, Greece, Spain, and Turkey, climbing has become a foremost advertised activity that is used for attracting many tourists. Thousands of rock-climbing regions have been developed and registered in electronic climbing guidebooks, which have been made available worldwide. In this scenario, some companies have been focusing their business on actively supporting climbers, by providing them reliable, easily accessible, and updated information, even via novel information technology tools.

For example, a local company Vertical-Life1 in South Tyrol (Italy) offers to prospective visitors an electronic climbing guidebook, which is accessible through

1 https://www.vertical-life.info.

c The Author(s) 2022

J. L. Stienmetz et al. (Eds.): ENTER 2022, *Information and Communication Technologies in Tourism 2022*, pp. 369–381, 2022. https://doi.org/10.1007/978-3-030-94751-4\_33

a rich website2. In addition to the e-guidebook, climbers can find there e-services that allow them to leave feedback in the form of comments, ratings, and grades for the routes that they have climbed (logbook functionality). Another similar example of such type of information tools is illustrated by UKClimbing3. Their website provides online descriptions and maps for many climbing areas, mostly located in Europe. Furthermore, in Australia, climbers can browse 'the Crag'4 website, which focuses on outdoor climbing routes in this country.

By complementing these websites, ancillary mobile apps have been developed; they allow to discover and log climbing routes [1–5]. Climbers can use them to track their progress in training. These apps are also used to maintain updated information on the climbing routes, in collaboration with local guides, by collecting crowd-based feedback on the featured routes.

This information repository is evolving day by day and is of great interest to the companies operating in this tourism sector. They aim to expand their penetration and role by providing climbers with the most essential information, and in the most easily usable way. In particular, they would like to match climbers' needs with personalized recommendations for routes that suit the climbers' expectations and limitations, such as the maximum difficulty level of the route the climber can climb, the desired duration and length of the route, or it's safety level, which is influenced by the changing mountain rocks' state. It is worth stressing that the available technologies and tools use manual input acquired via the system GUI (query) for establishing a match between a target climber (user's preferences) and the recommendable routes. This is burdensome and tends to decrease the usage of the existing tools.

To address this problem, we illustrate here a range of techniques and tools that enable us to learn semi-automatically climbers' preferences, by leveraging their explicit feedback given in a climbing app. Moreover, we illustrate how the routes recommendations can be delivered to climbers in specialized websites and apps. We focus on a system prototype and its GUI, that we are developing for one of the above-mentioned companies, namely, Vertical-Life. Recommendations are also tailored to the climber by considering one of the most important aspects, i.e., the desired difficulty level of the searched routes. Moreover, since the difficulty of a route is often subjective, this subjectivity is estimated by machine learning models that predict how difficult a given route will be perceived, specifically by each climber. Exploiting that estimation module, we have developed an interface for personalized recommendations for outdoor climbing. Ultimately, the recommendations given to a user are based on the knowledge of the user's preferred routes, which is derived from the logged climbing activities in the app, and by the goal of the climber (e.g., routes useful for training).

The paper is structured as follows: in Sect. 2, we discuss the related work. In Sect. 3, we describe the building blocks used for computing recommendations. In Sect. 4, we sketch the GUI which have been designed to illustrate and explain

2 https://www.8a.nu.

3 https://www.ukclimbing.com.

4 https://www.thecrag.com.

the recommendations. Finally, Sect. 5 discusses the contribution and concludes the work by listing some future developments.

#### **2 Related Work**