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This paper aims to explore the implications of integrating humanoid service robots into hospitality service encounters by evaluating two service prototypes using Softbank Robotics’ popular service robot Pepper™: to provide information (akin to a receptionist) and to facilitate order-taking (akin to a server). Drawing both studies together, the paper puts forward novel, theory-informed yet context-rooted design principles for humanoid robot adoption in hospitality service encounters.

Adopting a multiple method qualitative approach, two service prototypes are evaluated with hospitality and tourism experts (N = 30, Prototype 1) and frontline hospitality employees (N = 18, Prototype 2) using participant observation, in situ feedback, semi-structured interviews and photo-elicitation.

The adoption of humanoid service robots in hospitality is influenced by the following four layers of determinants: contextual, social, interactional and psychological factors, as well as extrinsic and intrinsic drivers of adoption. These empirical findings both confirm and extend previous conceptualizations of human-robot interaction (HRI) in hospitality service.

Despite using photo-elicitation to evoke insight regarding the use of different types of service robots in hospitality, the paper mostly focuses on anthropomorphized service robots such as Pepper™.

Adopting humanoid service robots will transform hospitality operations, whereby the most routine, unpleasant tasks such as taking repeat orders or dealing with complaints may be delegated to service robots or human-robot teams.

Working with and receiving service from Pepper™ changes the service encounter from direct practical, technical considerations to more nuanced social and psychological implications, particularly around feelings of self-esteem, social pressure and social judgment.

This paper presents one of the first empirical studies on HRI in hospitality service encounters using Softbank Robotics’ Pepper™. In doing so, the paper presents a novel framework for service robot adoption rooted in first-hand user interaction as opposed to previous, theory-driven conceptualizations of behavior or empirical studies exploring behavioral intention.

The study aims to review how the use of technology enhances the authentic tourist experience. Technology and digitalization have enhanced tourist experiences. However, critiques comment on its ability to over-commercialize activity and lack of authenticity. Thus, there is a need to synthesize knowledge of technology usage to increase authentic tourist experience.

The study carries out a bibliometric review of the studies focusing on the use of technology in enhancing tourist experiences. Two hundred journal articles, published between 1997 and 2023 were retrieved from the Web of Science (WoS) database to carry out descriptive and network analysis using the Gephi, VOSviewer and Science of Science (Sci2) software. The components of authentic tourism experience are identified from the literature through a content analysis.

The findings of the study are broadly classified into two: first, the most frequently used keywords in the study include tourist experience and satisfaction, co-creation, virtual reality, smart tourism, technology, authenticity and heritage tourism. Second, the five major themes studied in the topic include virtual reality and tourist experience; media, tourist experience and encounters; technology, smart tourism and tourist experience; digital transformation, social media and tourist experience; and virtual reality and tourist experience which are still relevant in the literature because of the presence of study gaps.

The findings are used to develop a conceptual framework for the role of technology in enhancing authenticity in tourism typologies where authenticity is critical.

This paper aims to outline a map of all the research that exists on mobile technology and tourism archived in the two main databases worldwide (Web of Science and Scopus). Accordingly, with the identification of all the scientific articles that deal with both mobile technology and tourism, the authors seek to ascertain the evolution of mobile technology in the tourism sector through the years, countries, universities and authors and determine the various collaborations brought about between authors, universities, institutions and/or companies in various research projects. Finally, it also allows the authors to distinguish the main topics under study within the scope of ‘mobile tourism’.

A mixed methodology has been carried out. The search focused on the principal databases of bibliographic references and citations of periodical publications, such as articles from scientific journals, books and other types of printed material. Once the results were obtained in the respective databases, it was necessary to be able to work with them. In this respect, the authors had to extract the relevant data and dump it in a bibliographic reference manager, for which they chose Mendeley. After this, the tabulation of data was performed in Excel and tables and graphs were created from all the data collected.

The main results obtained and analyzed are the number of articles per year, countries and universities. In the same way, it is interesting to highlight the number of countries and universities that participate in each article under study. On the other hand, an analysis has been carried out regarding the number of articles per author, as well as the topics dealt with in the different articles.

This analysis reveals the role that has been played by mobile phones in tourism since the first scientific article was recorded in 2002. In this regard, in recent years there has been a significant increase in the number of articles, finally resulting in moderate figures in relation to countries (40) and universities (233) that have formed part of the subject matter under study. In contrast to other areas of research in tourism, the relevance of this subject is therefore evident, as is the need for greater background knowledge to establish research models adapted to the new reality of tourism in a world of ever-increasing mobility.

The literature review reveals that lake tourism and lake-destination areas (LDA) have been particularly absent from destination image (DI) studies over 45 years of research. In fact, there is a lack of research concerning the characteristics of lake tourism, particularly related to the attributes involved in the formation of lake-DI. Therefore, this paper aims to explore lake tourism and lake-DI based on the Alqueva Lake more thoroughly, it being the biggest man-made lake in Europe, as an emerging lake-destination area located in the south of Portugal.

Within this, the perceptions of stakeholders professionally involved with this type of destination were examined through 17 semi-structured interviews based on content-analysis as a qualitative technique. Framed by the important contribution of visual-based research in tourism studies, this study adopts two approaches: an attribute-based approach (textual data) and a photo-based approach (visual data), to strengthen the concept, characteristics and dimensions of lake tourism and image attributes applied to this type of destinations. Multiple techniques of extracting data were used, demonstrating the importance of using various techniques in obtaining image attributes as a first step in assessing DIs.

The findings revealed textual and pictorial attributes related to lake tourism and LDA, which confirms that although image attributes are universally important, depicting specific attributes is important considering particular types of tourism, such as lake tourism.

This is a very recent sub-field of DI studies, which justifies its investigation on a theoretical as well as on a practical management level.

While the importance of social media will continue to grow, the purpose of this study is to provide a retrospective systematic literature review of the social media research published in major hospitality and tourism journals over a specific time period.

The study conducted a bibliometric analysis to review the literature of 439 social media articles published in 51 hospitality and tourism journals over a 15-year time span (2002-2016).

Ulrike Gretzel authored the highest fractional citations. The results indicated that social media-related research was mostly published in top-tier journals. The International Journal of Contemporary Hospitality Management was amongst the four leading journals in terms of the percentage of published social media articles. While inter-country social media research collaborations were relatively modest, interestingly, inter-country collaborations have been steadily increasing in the past five years. Another finding indicated that social media research in hospitality and tourism journals has been predominantly quantitative. The results revealed six new areas within the consumer behaviour research theme, namely, eWOM, service recovery, customer satisfaction, brand/destination image and service quality. Finally, it is important to note that four new trends in social media research appeared between 2011 and 2016, namely, big data, netnography, Travel 2.0 and Web 2.0.

While this study made significant contributions to the social media literature, some limitations do exist. For example, the current research excluded publications from major conferences, books, book chapters and dissertations. Additionally, it is not within the scope of this paper to take into account issues related to self-citations.

The results obtained from analysis contribute to a comprehensive understanding of social media research progress in hospitality and tourism. For example, evaluating the performance of individual scholars helps educational institutions to compete in the global university ranking system. Additionally, to compete for funding opportunities on the topic of social media, institutions can use citation counts to demonstrate their competitiveness. Furthermore, due to the expected future growth in the number of social media platforms, practitioners need to understand motivating factors and tourists’ needs in different countries, target market segments, age groups and cultures to create highly engaging communities around their brands.

To the best of the authors’ knowledge, the sample of this study synthesized the largest selection of social media articles published in hospitality and tourism journals. This is the first study to apply the fractional score at the author level, the adjusted appearance score at the university level and the average citation score at the journal and inter-country levels in the analysis. In addition, prevalent research orientations and research trends in social media made significant contributions to existing literature.

The purpose of this study is to reveal the research trends in guest experiences of service robots in the hospitality industry.

In this study, a review was carried out on the Web of Science (WoS) database with the assistance of bibliometric analysis techniques. Cluster analysis was also employed for this to group important data to determine the relationships and to visualize the areas in which the studies are concentrated. The thematic content analysis method was used to reveal on which customer experiences and on which methods the focuses were.

On the subject of experiences of service robots, the greatest number of publications was in 2021. In terms of country, China has come to the fore in the distribution of publications. As a result of thematic content analysis, it was determined that the leading factor was the main dimension of emotional experience. In terms of sub-dimensions, social interactions attracted more attention. Most of the studies discussed were not based on any theory. Apart from these, the Technology Acceptance Model (TAM), the Service Quality Model (SERVQUAL) and Perceived Value Theory (PVT) were featured more prominently among other studies.

In this study, only the WoS database was reviewed. In future studies, it would be possible to make contextual comparisons by scanning other databases. In addition to quantitative research designs, social dimensions may be examined in depth following qualitative research methods. Thus, various comparisons can be made on the subject with mixed-method research designs. Experimental research designs can also be applied to where customers have experienced human-robot interactions (HRIs).

In the hospitality industry, it is critical to uncover every dimension of guests' robot acceptance. This study, which presents the current situation on this basis, guides future projections for the development of guest experiences regarding service robots in the hospitality industry.

The hospitality industry in developed countries is under pressure due to labor shortages and it is likely more food and beverage operations will have to be automated in the future. This research investigates the public’s perceptions of the use of robots in food and beverage operations to learn about how the public perceives automation in food and beverage.

Data were collected from a survey disseminated online in 12 languages, resulting in a sample of 1,579 respondents. The data were analyzed using factor analysis and OLS regressions.

The data also reveal that generally positive attitudes toward the use of robots in tourism and hospitality is a strong indicator of positive attitudes toward the use of robots in an F&B setting. The data also illustrate that the public’s perception of appropriateness of the use of robots in F&B operations is positively related to robots’ perceived reliability, functionality and advantages compared to human employees.

The implications illustrate that the public seems to be generally accepting robots in food and beverage operations, even considering the public’s understanding and acceptance of the limitations of such technologies.

The research suggests that a critical element in terms of incorporating automation into future food and beverage operations is encouraging consumers to have generally positive attitudes toward the use of robots in hospitality and tourism industries.

This survey is based upon the data gathered in multiple countries to learn about how individuals perceive the use of robots in food and beverage operations, illustrating the attitudes that will assist or hinder the automation of this service industry.

This paper aims to investigate potential consumers’ willingness to pay for robot-delivered services in travel, tourism and hospitality, and the factors that shape their willingness to pay.

An online survey yielded a sample of 1,573 respondents from 99 countries. Independent samples t-test, Analysis of variance (ANOVA), cluster, factor and regression analyses were used.

Respondents expected to pay less for robot-delivered services than human-delivered services. Two clusters were identified: one cluster willing to pay nearly the same price for robotic services as for human-delivered services, whilst the other expected deep discounts for robotic services. The willingness-to-pay was positively associated with the attitudes towards robots in tourism, robotic service experience expectations, men and household size. It was negatively associated to travel frequency, age and education.

The paper’s main limitation is its exploratory nature and the use of a hypothetical scenario in measuring respondents’ willingness to pay. The data were gathered prior to the COVID-19 pandemic and do not reflect the potential changes in perceptions of robots due to the pandemic.

Practitioners need to focus on improving the attitudes towards robots in tourism because they are strongly and positively related to the willingness to pay. The marketing messages need to form positive expectations about robotic services.

This is one of the first papers to investigate consumers’ willingness to pay for robot-delivered services in travel, tourism and hospitality and factors that shape their willingness to pay.

The purpose of this paper is to propose sentiment annotation at sentence level to reduce information overloading while reading product/service reviews in the internet.

The keyword-based sentiment analysis is applied for highlighting review sentences. An experiment is conducted for demonstrating its effectiveness.

A prototype is built for highlighting tourism review sentences in Chinese with positive or negative sentiment polarity. An experiment results indicates that sentiment annotation can increase information quality and user’s intention to read tourism reviews.

This study has made two major contributions: proposing the approach of adding sentiment annotation at sentence level of review texts for assisting decision-making; validating the relationships among the information quality constructs. However, in this study, sentiment analysis was conducted on a limited corpus; future research may try a larger corpus. Besides, the annotation system was built on the tourism data. Future studies might try to apply to other areas.

If the proposed annotation systems become popular, both tourists and attraction providers would obtain benefits. In this era of smart tourism, tourists could browse through the huge amount of internet information more quickly. Attraction providers could understand what are the strengths and weaknesses of their facilities more easily. The application of this sentiment analysis is possible for other languages, especially for non-spaced languages.

Facing large amounts of data, past researchers were engaged in automatically constructing a compact yet meaningful abstraction of the texts. However, users have different positions and purposes. This study proposes an alternative approach to add sentiment annotation at sentence level for assisting users.