Robotics in the Travel, Tourism, and Hospitality Sector: A Bibliometric Analysis of Publications from 2014 to 2023

Robotics in the Travel, Tourism, and Hospitality Sector: A Bibliometric Analysis of Publications from 2014 to 2023 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Robotics in the Travel, Tourism, and Hospitality Sector: A Bibliometric Analysis of Publications from 2014 to 2023 Corina Monica Pop This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5300051/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study aims to conduct a bibliometric analysis of research publications (Virkus et al. 2023 ) on the application of robotics in the hospitality and tourism industry (Sharma 2024 ). Robotics is transforming various industries, including tourism, where technologies such as service robots, social robots, intelligent robots, and mobile robots are increasingly adopted (Ladeira 2023). Publications from 2014 to 2023 were collected from the Scopus database and analyzed (Carè and Cumming 2024 ) based on several criteria, including document type, language, publication year, country of origin, authorship, affiliations, sources, citations, keywords, and research areas. VOSviewer was used to visualize research trends related to the application of robots in hospitality and tourism. An analysis of 110 documents revealed a consistent increase in publications over the past decade, with China leading in publication output, followed by the United Kingdom and the United States. The International Journal of Hospitality Management emerged as the most prolific journal in this field, and the University of Surrey, Guildford, was identified as the leading institution in terms of publication volume. Keyword analysis underscored the primary research areas associated with service robots in tourism. This bibliometric study highlights the expanding literature on robotics applications within the tourism sector and serves as a valuable resource for researchers and industry stakeholders seeking to understand the current state and trends in the field (Valeri and Albattat 2024 ). tourism hospitality robotics service robots bibliometric analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction With the advancement of new technologies, the use of service robots to deliver human-centered services is drawing growing interest from companies in the tourism and hospitality sectors. Thanks to robotics and artificial intelligence, tourism benefits from modernization in order to improve the services offered. Thus, language translation, audio tours and online shopping create much more interesting and engaging travel conditions. (Samala et al. 2020 ) The integration of robotics and artificial intelligence in the hospitality and tourism industry can lead to improved operational efficiency, cost reductions, enhanced safety measures, and better customer service (Núñez et al. 2024 ). Hotel owners, as well as the related staff, offer modern conditions and services, based on novel technologies, such as: intelligent room technology, artificial intelligence and robotic devices. “Robots can help with everyday tasks such as guests greeting, housekeeping, room service and luggage delivery” (Lacalle 2024 , p.1; Callarisa-Fiol et al. 2023 ). This bibliometric analysis seeks to offer a quantitative overview of research and publications related to robotics in the tourism and hospitality sector from 2014 to 2023. “A bibliometric analysis is a type of study that uses statistical analysis to evaluate and measure the influence and impact of publications or research within a particular field, and is often considered the most appropriate method for studying the evolution of areas of scientific research (Grabowska et al. 2022 ; Rojas-Sánchez et al. 2023 ). It can be useful to understand research effort, structures, growth and impact (Sandnes, 2021 ), such as trends in article and journal performance, collaboration patterns, intellectual structures of a given field (Donthu et al. 2021 ), research priorities and references, research networks and geographical location” (Ospina-Mateus et al. 2019 ; Postelnicu and Boboc 2024 , p.2). In this context, the present analysis seeks to offer insights into the current state and future trends of robotics in tourism and hospitality by examining the field's development, identifying key contributors, and assessing their impact. A bibliometric analysis was conducted to assess the current advancements and identify potential research avenues concerning the use of robotics across various industrial sectors, including healthcare (Liu et al. 2022 ), tourism (Dey et al. 2022 ), apparel (Goel et al. 2023 ), construction (Seyman Guray and Kismet 2023 ), engineering education and training (Lai et al. 2020 ), lean manufacturing (Alsadi et al. 2023 ), and the built environment (Zhang et al. 2020 ), among others (Núñez 2024). However, to the best of our knowledge, there is still no bibliographic study on the application of robotics in tourism, although there are numerous review articles on different topics: historical context: Reviewing the evolution of robotics technology and its applications within various industries. current applications: Examining how robotics is currently being used in tourism, such as in hotel service robots, robotic tour guides, and automated check-in/check-out processes. impact analysis: Evaluating the impact of these technologies on the tourism experience, customer satisfaction, and operational efficiency. future trends: Investigating emerging trends and future directions for the use of robotics in tourism. Gathering data from academic journals, industry reports, and conference proceedings could be a starting point for such a study. To address the gap in the scientific literature regarding the bibliometric analysis of robotics applications in tourism, this study investigates the following questions: What are the overall publication trends in the field of tourism utilizing robotics? Who are the most prolific authors, how intense is the cooperation between them, how are the papers assigned with respect to the number of those who authored them? (González-Alcaide 2014 ) Which are “the most cited publications, the most cited authors and the most cited institutions”? (Reis et al. 2017 ). Which sources “have published the highest number of articles on this topic”, and what types of publications are most prevalent? (Malik et al. 2024 ) Additionally, what are the primary keywords associated with research on the application of robotic technology in tourism? (Mukunda and Sahoo 2024 ) 1. Materials and methods 1.1. Data source and search strategy This research employed the Scopus database to conduct the bibliometric analysis. Scopus is a comprehensive repository of abstracts and citation data, covering a wide range of academic fields such as engineering, medicine, social sciences, and the arts and humanities, including journals, conference proceedings, and books. For bibliometric studies, “citation data is primarily sourced from Clarivate Analytics' Web of Science (WoS) and Elsevier's Scopus (Mongeon and Paul-Hus 2016 )” (Albadayneh et al. 2024 , p.3; Postelnicu and Boboc 2024 ). While “WoS was the first database established and is widely recognized” (Albadayneh et al. 2024 , p.3) within academia, Scopus has emerged as a strong alternative (Harzing and Alakangas 2016 ) due to its broader, more inclusive, and comprehensive content coverage, which in some fields surpasses that of WoS (Shome et al. 2023 ; Kumpulainen and Seppänen 2023, Hashem et al. 2023 ). Additionally, “Scopus offers individual profiles for authors, institutions, and serial sources (Anugerah et al. 2022 )” (Carè and Cumming 2024 ; Kumar et al. 2024 ) and “features a more recent and extensive selection of journals (Umeokafor et al. 2022 ). To minimize errors arising from the integration of data from various databases with differing formats, this study utilized a single database for data retrieval” (Albadayneh, et al. 2024 , p.3). This approach is consistent with the methodology outlined by Mühl and de Oliveira ( 2022 ) and Postelnicu and Boboc ( 2024 ). The search conducted in the Scopus database aimed to identify documents related to service robots, social robots, intelligent robots, and mobile robots, specifically in the context of tourism, hospitality, leisure, and travel. The travel and tourism sector encompasses a wide array of products and services, including both leisure and business travel (Sharma et al. 2024). The hospitality sector is a diverse segment of the service industry, encompassing a wide range of services such as lodging, food and beverage provision, event management, theme parks, travel services, tourism, hotels, restaurants, nightclubs, and bars. The author deliberately selected these four terms to comprehensively capture relevant documents from the database, filtering results based solely on the “Title, Abstract, and Keywords fields”. The search was conducted using the following query: “TITLE-ABS ( "service robots" OR "social robots" OR "intelligent robots" OR "mobile robots" ) AND TITLE-ABS-KEY ( "tourism" OR "hospitality industry" OR "leisure" OR "travel") AND PUBYEAR > 2013 AND PUBYEAR < 2024 AND ( LIMIT-TO (DOCTYPE, "ar" ) OR LIMIT-TO ( DOCTYPE, "cp" ) )”. The subsequent section will outline the abbreviations utilized in this study. This search yielded a total of 620 documents within the specified timeframe, and it was performed on March 28, 2024. “The publication records were extracted in CSV format through the advanced search feature provided by Scopus. This file was then imported into MS Excel, and VOSviewer software (version 1.6.20) (2024) was employed for mapping analysis” (Postelnicu and Boboc 2024 , p.3). 1.2. Inclusion and exclusion criteria From the initial set of 620 documents, the author examined each paper to assess its relevance to both the robotics domain and the tourism sector. All abstracts were reviewed, and the content was analyzed to determine if they met the specified criteria. The study does not include publications that do not meet the previously mentioned criteria, nor those that represent reviews (surveys) or presentations of the current state of research. Only research papers with contributions to the tourism and robotic fields were considered, and finally, a total of 110 documents were selected based on the established criteria (Valeri and Albattat 2024 ). The criteria for inclusion required that the articles focus on tourism research involving robotic technology, covering publications from January 1, 2014, to December 31, 2023. Excluded from this review were conference reviews ("cr"), literature reviews ("re"), book chapters ("ch"), entire books ("bk"), notes ("no"), retracted papers ("tb"), and any articles that did not fit the designated keywords. The analysis was limited to journal articles ("ar") and conference proceedings ("cp"). An initial search, conducted without these restrictions, resulted in 679 documents. Figure 1 depicts “the process for identifying and selecting the relevant studies” (Heirene et al. 2024 , p. 13). The retrieval of articles followed “the PRISMA ( P referred R eporting I tems for S ystematic Reviews and M eta- A nalyses ) guidelines” (Page et al. 2021 ; Postelnicu and Boboc 2024 , p.3). This approach facilitated the identification of key articles relevant to the study topic, organized systematically as a bibliometric analysis rather than a bibliographic presentation. Bibliometric analysis involves measuring, tracking, and analyzing scholarly literature using quantitative methods (Rojas-Sánchez et al. 2023 ; Postelnicu and Boboc 2024 ). It offers a comprehensive understanding of “the bibliometric and intellectual landscape of a field by analyzing the social and structural connections between key research components, such as authors, countries, institutions, and topics” (Donthu et al. 2021 ; Hernández-Perlines et al. 2023 , p.4; Postelnicu and Boboc 2024 ). 1.3. Data analysis Eligible articles according to the established criteria were studied using a dedicated program. The analysis yielded several bibliometric indicators, including document type, language, publication year, document and author counts, publication numbers by country and international collaboration, affiliation-based publication counts, authorship metrics, citation counts, publication sources, co-citation analysis, and keyword co-occurrence. Source: Adapted from Postelnicu and Boboc ( 2024 ) The bibliometric analysis followed these steps: Database selection: Scopus Search fields: Article Title, Abstract, and Keywords Timeframe: January 1, 2014, to December 31, 2023 Data collection: Data was extracted as a CSV file from Scopus Analysis tools: VOSviewer and Microsoft Excel were used for data analysis Results presentation: The findings were displayed in tables, graphs, and diagrams (Postelnicu, et al. 2024). 2. Results and discussion This section outlines the research results and provides a discussion of the bibliometric analysis, offering a detailed overview of the quantitative scientific output in the field of robotics as it pertains to the tourism and hospitality sectors (Jain et al. 2024). 2.1. Overview of bibliometric information The bibliometric analysis identified 110 articles sourced from Scopus, authored by 347 different individuals and published across 67 journals. The majority of these publications are classified as “journal articles” (79.09%), with “conference papers” comprising the remaining 20.91% (Fig. 2a). Most articles were written in English (108 records, 98.18%), while 2 were published in Japanese (1.82%). The types of papers that were excluded are depicted in Fig. 2b. The findings indicate a substantial increase in robotics research within the tourism sector over the past decade. Approximately 59.83% of the total articles were published in the last three years, with yearly publications exceeding 20 (Fig. 3a). The peak publication year was 2023, accounting for 37% of the total. A similar upward trend is seen in the “number of authors” indicator (Fig. 3b), with the highest number of authors recorded in 2023 (16.36%). 2.2. Geographic distribution of publications The research on robotics applications in the tourism and hospitality industry (Mukherjee et al. 2023; Ivanov et al. 2019) originated from 40 countries. These included 18 from Asia, 15 from Europe, 3 from Africa, 2 from North America, 1 from South America, and 1 from Oceania. Fig. 4 illustrates the global distribution of the articles analyzed in this study. Asia emerges as the leading continent, contributing 45.00% of the total publications, followed by Europe (37.50%), Africa (7.50%), North America (5.00%), South America (2.50%), and Oceania (2.50%). Out of the countries studied, 33 (82.50%) produced between 1 and 5 publications, while 6 countries (15.00%) published between 6 and 20 articles, and only 1 country (2.50%) generated more than 20 publications. Notably, China contributed approximately 32.73% (n=36) of the included studies, followed by the United Kingdom at 14.55% (n=16) and the United States at 13.64% (n=15). Among those countries with 6 to 20 publications, the United Kingdom (16 publications) and the United States (15 publications) were the most prolific. Table 1 Top 12 contributing countries that published more than 3 papers. The analysis reveals that China makes the most significant contributions to the field. Table 1 lists the top 12 countries based on their contributions, detailing both the number of publications and citations. It is important to note that the total citation counts reflect data retrieved from the Scopus database on March 28, 2024. To provide a clearer picture of the most active countries, Fig. 5 illustrates the "cooperation network" indicator. This analysis was conducted using VOSviewer software, with a minimum publication threshold of 4 documents per country, resulting in 12 countries that met this criterion. In Fig. 5, the size of the circles represents the volume of publications for each country, while the connecting lines indicate collaborative efforts with other nations. The analysis identifies five main clusters: the first includes China and Australia (blue), the second comprises the United Kingdom, Spain, and Italy (green), the third encompasses the United States and Turkey (purple), the fourth features India, France, and Malaysia (red), and the fifth cluster includes Hong Kong and South Korea (yellow). China, United Kingdom and United States are the most influential countries with a total link strength (TLS) of 9 for each country, followed by India and Australia. As predicted, the Fig. exemplifies an evolution towards an increased number of papers written with the contribution of several authors. 2.3. Affiliation-based distribution of publications The analysis identified a total of 196 research institutions associated with the publications. Among these, 154 institutions (78.57%) contributed only one article, while 39 institutions (19.90%) published two or three studies, and 3 institutions (1.53%) published more than three papers. The University of Surrey in Guildford emerged as the most prolific academic institution, with six publications. It was followed by Sun Yat-Sen University in Guangzhou, which produced five publications, and Sakarya Universitesi in Sakarya, with four publications. Collectively, the top 12 institutions (Table 2) contributed 42 papers, representing 38.18% of the total articles published. Although most institutions involved in research on robotic technologies applied to tourism are universities, the landscape also includes private and governmental organizations, research centers, and various institutes (Ospina-Mateus et al. 2019). Table 2 Top 12 most productive institutes according to the number of publications and number of citations 2.4. Authors and their cooperation As previously noted, the 110 publications involved a total of 347 authors. The number of authors per study varied from 1 to 8, with an average of 3.15 authors per article. Table 3 provides a summary of the publications categorized by the number of authors and the citations each group received. Most articles were authored by 2, 3, or 4 individuals, with the highest citation counts associated with works authored by 3 and 4 authors. Notably, 94.24% (n=327) of the authors published only a single article, while 4.32% (n=15) authored 2 articles, and 1.44% (n=5) published 3 studies. Table 3 Distribution of publications based on the number of authors Table 4 Most-productive authors according to the number of citations Table 4 shows the first 10 of the most prolific authors, considering the number of citations. This table provides information on the selected papers, including author affiliations, countries, the number of publications, citations, and the Scopus h-index. Within this context, Dogan Gursoy (n=394), Daniel Belanche (n=160), and Stanislav Ivanov (n=118) are the top three authors. Based on their Scopus h-index, Dogan Gursoy, with 2 publications, leads the ranking with an h-index of 67. His most cited paper is (Lu et al. 2019), which has received 390 citations. Following him, Daniel Belanche, also with 2 articles, has his most cited work (Belanche et al. 2021) attracting 119 citations. Stanislav Ivanov ranks third, with 2 publications as well, the most cited being (Ivanov et al. 2020a), which has garnered 102 citations in Scopus. Fig. 6 details the model relative to the cooperation of the authors. The co-authorship analysis conducted using VOSviewer reveals a network of the 10 authors who have published at least one paper. This analysis identifies three distinct clusters, each represented in different colors. Huang Dan emerges as the most prominent author, with a Total Link Strength (TLS) of 3. It can be mentioned that there is collaboration between authors from the same institution or organization belonging to China. 2.5. Document citation Table 5 presents data for the most cited articles, including their titles, publication sources, total citations as of 2023, and "Field-Weighted Citation Impact (FWCI)" (Cantú-Ortiz 2017). The FWCI is a metric that reflects the average citation impact of a document, indicating how often it is cited in comparison to similar works (Purkayastha, et al. 2019). It is calculated using the following formula: where c i represents “the number of citations received by publication i and e i denotes the expected number of citations per publication received by similar publications” (Postelnicu and Boboc 2024, p.7). Table 5 Top 10 highly cited papers Among the ten highest-impact articles, three were published in "Tourism Management" while one article each appeared in the following journals: "International Journal of Hospitality Management", "Tourism Geographies, Computers in Human Behavior", "International Journal of Contemporary Hospitality Management", "Annals of Tourism Research", "Electronic Markets, and Information Technology and Tourism". The article “by Lu et al. (2019) received” (Husain et al. 2023) the highest total citation count, with 390 citations, and also ranks first in terms of average citations per year, averaging 78 citations. The publications listed in the table were released between 2017 and 2021. Table 6 Top 10 most active publications (journals and conference proceedings). “A ranking of the top 10 most cited publications, encompassing both journals and conference proceedings, has been compiled (Table 6) to illustrate the influence of these works due to their significant scientific impact. This table includes details such as the source name, ISSN, publisher, number of articles related to the selected topic, percentage of the total articles, total citations received by those articles, journal impact factor, quartile ranking, and CiteScore according to Scimago Journal Ranking” (JCR 2022) (Postelnicu and Boboc 2024, p.10). The "International Journal of Hospitality Management" led with the highest number of publications in the designated timeframe, contributing 9 articles (8.18%). Following it, the "International Journal of Contemporary Hospitality Management" ranked second with 7 publications (6.36%), trailed closely by "Tourism Management" ("International Journal of Tourism Management") in terms of the number of papers. In total, 110 articles were published across 67 sources. Among these, 10 sources (14.93%) published more than 2 papers, while 57 sources (85.07%) contributed 1 or 2 articles. Fig. 7 illustrates the annual publication count for the ten most active sources, including both journals and conference proceedings. 2.6. Subject area publications The 10 most significant subject areas from the Scopus database, according to their distribution by domains, are presented in Table 8. The analysis revealed that "the Business Management Accounting field made the largest contribution to research" (Olowoselu and ElSayary 2024) on robotics in tourism and hospitality, followed by Computer Science and Social Sciences . It is important to note that some publications span multiple subject areas, resulting in a total publication count that exceeds the 110 selected documents. Table 8 The top 10 subject areas Fig. 8 illustrates the keywords co-occurrence network, generated through the full counting method. Among the 361 keywords analyzed, 10 met the criteria of appearing at least twice, resulting in a keyword network categorized into 6 distinct clusters. These clusters highlight themes with numerous interconnected elements. “The size of each circle corresponds to the frequency of the keywords used: the more frequently a keyword appears, the larger the circle” (Agyei et al. 2024, p.10). Additionally, “a smaller distance between keywords indicates a stronger relationship”, based on how often the terms co-occur (Lehner et al. 2023). The diagram reveals that "service robots," "artificial intelligence," and "human-robot interaction" are among the most frequently used terms. Specifically, "service robots" appears 47 times with a Total Link Strength (TLS) of 59; "artificial intelligence" occurs 22 times, resulting in a TLS of 50; and "human-robot interaction" has 15 occurrences with a TLS of 29. Other notable terms include "COVID-19" and "robot," both with 9 occurrences (TLS of 20 and 12, respectively), as well as "robotics," which appears 7 times and has a TLS of 17. The yellow cluster is associated with service robots and anthropomorphism, encompassing themes like technology acceptance and social presence. The green cluster focuses on artificial intelligence, robots, and service automation. Terms related to human-robot interaction, social robots, and trust are found in the red cluster. The turquoise cluster addresses aspects related to COVID-19 and safety, while the purple cluster includes topics related to robotics, automation, and big data. Lastly, the orange cluster pertains to hospitality and tourism, and the blue cluster features terms linked to hotel service automation and autonomous robots. Fig. 9 shows trends of the top 12 keywords from January 1, 2014, to December 31, 2023. In addition to the established term ("service robots"), there are growing trends for topics related to "human-robot interaction" with the most occurrences. It can also be seen that keywords such as "artificial intelligence", "COVID-19" and "robotics" start to be used later (from 2020) in tourism research, which experiences a staggering collapse in 2020. After clustering the author's keywords, it is possible to highlight the most prominent research areas currently using robotic technologies in tourism and hospitality. These emerging technologies are used in many areas of tourism: airports, travel agencies, flight booking, hotel booking, airport security, hotel robots, robot porters, cleaning, food preparation and guests greeting are all areas where robots can be used. Robots are very efficient because they reduce working time and ensure that the work is done correctly. Robots reduce the workload as less manpower is required to do the work. The bibliometric analysis revealed a significant gap in systematic reviews within the scientific literature regarding the use of robotics in tourism and hospitality (Mukherjee et al. 2023). As such, this paper may serve as a valuable foundation for conducting a systematic literature review. Looking forward, it is clear that the incorporation of robotics into the tourism and hospitality (Ndhlovu et al. 2024) industry holds considerable promise, albeit accompanied by certain challenges. To lay the groundwork for future research, a detailed investigation plan will be developed, concentrating on key issues identified through a thorough keyword analysis. Below is a brief overview of the research agenda, designed to aid both scholars and practitioners in comprehending the evolving "relationship between robotics and the tourism and hospitality sector", which is increasingly influenced by technological advancements (Jerez-Jerez and Foroudi 2024). Robotics is affecting this industry in various ways: 1. Enhanced guest experience: · Robotic concierge: Robots can act as concierge assistants in hotels, providing guests with information about the hotel, local attractions, and even making reservations. These robots can make personalised recommendations based on guest preferences. · Room service robots: Robots can deliver room service items like food, beverages, and amenities directly to guests' rooms, ensuring a fast and efficient service experience. 2. Operational efficiency: · Automated check-in/check-out: Self-service kiosks and robotic systems can streamline check-in and check-out processes, decreasing wait times and allowing "staff to concentrate on providing more personalized guest interactions" (Saranya et al. 2025). · Cleaning robots: Hotels are increasingly using robotic vacuums and floor cleaners to maintain cleanliness and hygiene efficiently, especially in high-traffic areas. 3. Cost reduction: · Labour cost savings: Although the initial investment in robotics may be substantial, these technologies can lead to significant long-term savings on labor by automating repetitive and time-consuming tasks. This shift enables human employees to focus on roles that require personal engagement. · Inventory management: Robots can help manage inventory and supplies, ensuring that stock levels are maintained efficiently and reducing waste. 4. Personalised services: · Data collection and analysis: AI-powered robots can analyse guest data to provide tailored recommendations and services. For example, a robot could suggest local dining options based on previous guest reviews and preferences. · Language translation: Robots can offer real-time language translation, facilitating communication for international guests and improving their overall experience within the hotel or tourism environment. 5. Attraction and entertainment: · Interactive exhibits: In tourist attractions and museums, robots can serve as interactive guides, providing educational and engaging experiences. They can provide information, answer questions, and even entertain guests. · Themed experiences: Robots can be integrated into themed entertainment experiences, such as robot-themed shows or events, adding a futuristic element to attractions. 6. Safety and hygiene: · Sanitation robots: Particularly relevant to health and safety, robots can be used to disinfect and sanitise public spaces, helping to ensure a clean and safe environment for guests. 7. Accessibility: · Assistive robots: Robots can help guests with disabilities by assisting with navigation, carrying luggage, or providing information, thus improving the accessibility of tourism and hospitality services (Sharma, 2024). Overall, robotics has the potential to transform the tourism and hospitality sectors by enhancing operational efficiency, improving guest experiences, and introducing innovative services. Nevertheless, it is vital for businesses to strike a balance between automation and personal interaction, as these human connections remain essential to the guest experience. Interdisciplinary collaboration among computer scientists, psychologists, ethicists, and engineers will be crucial for advancing these research initiatives. Additionally, establishing “a robust ethical framework throughout the research and development processes will be essential to ensure the responsible application of robotic technologies within the travel, tourism, and hospitality industries” (Ivanov et al. 2020a; Herawan et al, 2023). 3. Limitations The research conducted for selecting representative articles was confined to the Scopus database. While this database encompasses a broad spectrum of publications across various disciplines, future studies “should consider including additional databases to achieve a more comprehensive” (Prasad and Subramanian 2024, p. 23) overview while ensuring the quality of the sources. Furthermore, this study provided a quantitative analysis without delving into the content of the articles, which is a notable limitation of bibliometric analyses. Lastly, the extensive number of publications reviewed raises “the possibility of including articles that may not align perfectly with the topic” (Postelnicu and Boboc 2024, p.13), despite the authors' efforts to adhere to the defined selection criteria Nevertheless, the authors believe that the analysis presented is sufficiently conclusive. 4. Conclusions Robotics, a key technology associated with Industry 4.0 (Dammacco et al. 2020), has demonstrated its capacity to deliver numerous advantages to “the tourism and hospitality sectors, including hotels (e.g., front desk agents, concierges, delivery robots, porters, and housekeepers), restaurants (e.g., chefs, hosts, waitstaff, food runners, bartenders, and food delivery robots), events (e.g., guest entertainment and physical presence for virtual attendees), attractions (e.g., museums), and travel (e.g., airports and autonomous vehicles)” (Ivanov et al. 2020b). “This study offers a comprehensive overview of research concerning the applications of robotics in tourism and hospitality over the past decade” (Gökçe, et al. 2024). The bibliometric analysis reveals a notable surge in research and development efforts in this domain. Findings indicate an increasing interest in robotic technologies and a significant level of international collaboration among authors and organizations. Additionally, there is a rise in interdisciplinary research, bringing together specialists from various fields. Overall, this study provides valuable insights into the current role of robotics in tourism and hospitality. The key findings include: · The majority of the analyzed documents are published in English. · The number of publications has accelerated significantly in the last five years. · Authors from Asia and Europe (notably China and the United Kingdom) lead in publication volume, with a strong collaborative relationship between them. · China ranks as the top country in terms of the number of organizations affiliated with authors who have published research. · Most articles have three authors, with a nearly equal number of four-author papers, and these tend to have the highest citation counts. · The most frequently cited documents are published in academic journals. · Elsevier dominates in terms of both the number of papers published and total citations (Hanganu-Bresch et al, 2022; Hernández-Perlines et al. 2023; Siriwardhana and Moehler 2024). · Among journals, the “International Journal of Hospitality Management” has the highest publication count. 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Automation in Construction , 118 , 103311. https://doi.org/10.1016/j.autcon.2020.103311 Tables Tables 1 to 8 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Tables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5300051","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":369743182,"identity":"3c951847-e18c-46ce-a960-91b2eb999f64","order_by":0,"name":"Corina Monica Pop","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwElEQVRIiWNgGAWjYPACCQYG9gYGhgSGA6Ro4QGqTkggXgtIVwKQIEaLOXvvwQ8f91jk8c98Y/bg4Y87iQ3Sh/Hrs+w5lyw545lEscTtHHODhIRniQ18aQl4tRjcyDFj5jkgkdhwO8dMIiHhsDEDD48BcVrm3zxDqpYNN3jAWuQIaoH4Bahl45m0MomEtGdybDxs+P0CDrEPB+oS5x0/vE3yh80dHn4e5gP4HcbAgybChlc9Vi2jYBSMglEwCtABAFLlRPOej/DPAAAAAElFTkSuQmCC","orcid":"","institution":"Transilvania University of Brașov","correspondingAuthor":true,"prefix":"","firstName":"Corina","middleName":"Monica","lastName":"Pop","suffix":""}],"badges":[],"createdAt":"2024-10-20 22:08:06","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5300051/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5300051/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":67503942,"identity":"2ce0d4eb-5c75-41de-ad6d-31f0045968a9","added_by":"auto","created_at":"2024-10-25 17:58:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":89163,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of the methodology used for the bibliometric analysis.\u003c/p\u003e\n\u003cp\u003eSource: Adapted from Postelnicu and Boboc (2024)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5300051/v1/a7c43a05339483934606e243.png"},{"id":67504738,"identity":"b92c4c27-437c-44c6-ad04-2b9ea7ef4e2b","added_by":"auto","created_at":"2024-10-25 18:14:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":34576,"visible":true,"origin":"","legend":"\u003cp\u003eClassification of papers by type: a) selected paper; b) excluded papers\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5300051/v1/a4bd4652b146a908512bc350.png"},{"id":67504277,"identity":"cb95275e-0c15-4c7c-8f28-dc2d73a28511","added_by":"auto","created_at":"2024-10-25 18:06:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":51093,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in the number of publications (a) and the count of authors (b) across different time period\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5300051/v1/6eddd8da7cf06cc3ae891dbc.png"},{"id":67504275,"identity":"e42703d1-3b8a-4a8d-95f2-d3d3dde68e5c","added_by":"auto","created_at":"2024-10-25 18:06:24","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":225349,"visible":true,"origin":"","legend":"\u003cp\u003eCountries with over three published articles\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5300051/v1/cc084731ed3927a483e98fa9.png"},{"id":67504273,"identity":"34544913-31cb-4f02-b3eb-6e91380659ac","added_by":"auto","created_at":"2024-10-25 18:06:24","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":98813,"visible":true,"origin":"","legend":"\u003cp\u003eCollaborative network among the twelve leading countries\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5300051/v1/7a08b5df69ed72705584f847.png"},{"id":67503950,"identity":"d1796c90-070f-459e-b615-67422ae5bdb0","added_by":"auto","created_at":"2024-10-25 17:58:24","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":88831,"visible":true,"origin":"","legend":"\u003cp\u003eVOSviewer network of author collaborations\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5300051/v1/d69dabd255356246e8479ce9.png"},{"id":67503944,"identity":"3c989f9c-2d11-413d-97b1-6281c1348823","added_by":"auto","created_at":"2024-10-25 17:58:24","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":171051,"visible":true,"origin":"","legend":"\u003cp\u003eAnnual publication count for the ten most active sources\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-5300051/v1/7c541d8c4a286b0fe5cd9802.png"},{"id":67504740,"identity":"c7abff4a-c830-4c05-8280-f14c004aa0e2","added_by":"auto","created_at":"2024-10-25 18:14:24","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":222085,"visible":true,"origin":"","legend":"\u003cp\u003eKeywords co-occurrence network\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-5300051/v1/07537fe976b0ffc4d0a5c897.png"},{"id":67504739,"identity":"7eefd93b-e5e6-4386-a1d5-411419c6e882","added_by":"auto","created_at":"2024-10-25 18:14:24","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":150580,"visible":true,"origin":"","legend":"\u003cp\u003eTrends of the twelve most prominent keywords in the analysed papers during the selected timeframe.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-5300051/v1/ebe2a71b2b9906141048ad8a.png"},{"id":69700291,"identity":"b83460a2-3c13-4d76-a959-c59c839cc401","added_by":"auto","created_at":"2024-11-23 14:16:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1436500,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5300051/v1/47e425c9-a5c5-484d-8fa2-cb6bf0edecb5.pdf"},{"id":67503945,"identity":"12022a52-d3e5-4924-bc76-8e070dfd2c27","added_by":"auto","created_at":"2024-10-25 17:58:24","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":286596,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-5300051/v1/c22b4d9b2ec4057b0051f11c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Robotics in the Travel, Tourism, and Hospitality Sector: A Bibliometric Analysis of Publications from 2014 to 2023","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWith the advancement of new technologies, the use of service robots to deliver human-centered services is drawing growing interest from companies in the tourism and hospitality sectors.\u003c/p\u003e \u003cp\u003eThanks to robotics and artificial intelligence, tourism benefits from modernization in order to improve the services offered. Thus, language translation, audio tours and online shopping create much more interesting and engaging travel conditions. (Samala et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe integration of robotics and artificial intelligence in the hospitality and tourism industry can lead to improved operational efficiency, cost reductions, enhanced safety measures, and better customer service (N\u0026uacute;\u0026ntilde;ez et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Hotel owners, as well as the related staff, offer modern conditions and services, based on novel technologies, such as: intelligent room technology, artificial intelligence and robotic devices. \u0026ldquo;Robots can help with everyday tasks such as guests greeting, housekeeping, room service and luggage delivery\u0026rdquo; (Lacalle \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, p.1; Callarisa-Fiol et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis bibliometric analysis seeks to offer a quantitative overview of research and publications related to robotics in the tourism and hospitality sector from 2014 to 2023.\u003c/p\u003e \u003cp\u003e\u0026ldquo;A bibliometric analysis is a type of study that uses statistical analysis to evaluate and measure the influence and impact of publications or research within a particular field, and is often considered the most appropriate method for studying the evolution of areas of scientific research (Grabowska et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Rojas-S\u0026aacute;nchez et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). It can be useful to understand research effort, structures, growth and impact (Sandnes, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), such as trends in article and journal performance, collaboration patterns, intellectual structures of a given field (Donthu et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), research priorities and references, research networks and geographical location\u0026rdquo; (Ospina-Mateus et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Postelnicu and Boboc \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, p.2). In this context, the present analysis seeks to offer insights into the current state and future trends of robotics in tourism and hospitality by examining the field's development, identifying key contributors, and assessing their impact.\u003c/p\u003e \u003cp\u003eA bibliometric analysis was conducted to assess the current advancements and identify potential research avenues concerning the use of robotics across various industrial sectors, including healthcare (Liu et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), tourism (Dey et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), apparel (Goel et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), construction (Seyman Guray and Kismet \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), engineering education and training (Lai et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), lean manufacturing (Alsadi et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and the built environment (Zhang et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), among others (N\u0026uacute;\u0026ntilde;ez 2024). However, to the best of our knowledge, there is still no bibliographic study on the application of robotics in tourism, although there are numerous review articles on different topics:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ehistorical context: Reviewing the evolution of robotics technology and its applications within various industries.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ecurrent applications: Examining how robotics is currently being used in tourism, such as in hotel service robots, robotic tour guides, and automated check-in/check-out processes.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eimpact analysis: Evaluating the impact of these technologies on the tourism experience, customer satisfaction, and operational efficiency.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003efuture trends: Investigating emerging trends and future directions for the use of robotics in tourism.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eGathering data from academic journals, industry reports, and conference proceedings could be a starting point for such a study.\u003c/p\u003e \u003cp\u003eTo address the gap in the scientific literature regarding the bibliometric analysis of robotics applications in tourism, this study investigates the following questions:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eWhat are the overall publication trends in the field of tourism utilizing robotics?\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eWho are the most prolific authors, how intense is the cooperation between them, how are the papers assigned with respect to the number of those who authored them? (Gonz\u0026aacute;lez-Alcaide \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eWhich are \u0026ldquo;the most cited publications, the most cited authors and the most cited institutions\u0026rdquo;? (Reis et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eWhich sources \u0026ldquo;have published the highest number of articles on this topic\u0026rdquo;, and what types of publications are most prevalent? (Malik et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAdditionally, what are the primary keywords associated with research on the application of robotic technology in tourism? (Mukunda and Sahoo \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e"},{"header":"1. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.1. Data source and search strategy\u003c/h2\u003e \u003cp\u003eThis research employed the Scopus database to conduct the bibliometric analysis. Scopus is a comprehensive repository of abstracts and citation data, covering a wide range of academic fields such as engineering, medicine, social sciences, and the arts and humanities, including journals, conference proceedings, and books. For bibliometric studies, \u0026ldquo;citation data is primarily sourced from Clarivate Analytics' Web of Science (WoS) and Elsevier's Scopus (Mongeon and Paul-Hus \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u0026rdquo; (Albadayneh et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, p.3; Postelnicu and Boboc \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile \u0026ldquo;WoS was the first database established and is widely recognized\u0026rdquo; (Albadayneh et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, p.3) within academia, Scopus has emerged as a strong alternative (Harzing and Alakangas \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) due to its broader, more inclusive, and comprehensive content coverage, which in some fields surpasses that of WoS (Shome et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Kumpulainen and Sepp\u0026auml;nen 2023, Hashem et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, \u0026ldquo;Scopus offers individual profiles for authors, institutions, and serial sources (Anugerah et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u0026rdquo; (Car\u0026egrave; and Cumming \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kumar et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and \u0026ldquo;features a more recent and extensive selection of journals (Umeokafor et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). To minimize errors arising from the integration of data from various databases with differing formats, this study utilized a single database for data retrieval\u0026rdquo; (Albadayneh, et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, p.3). This approach is consistent with the methodology outlined by M\u0026uuml;hl and de Oliveira (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and Postelnicu and Boboc (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe search conducted in the Scopus database aimed to identify documents related to service robots, social robots, intelligent robots, and mobile robots, specifically in the context of tourism, hospitality, leisure, and travel. The travel and tourism sector encompasses a wide array of products and services, including both leisure and business travel (Sharma et al. 2024). The hospitality sector is a diverse segment of the service industry, encompassing a wide range of services such as lodging, food and beverage provision, event management, theme parks, travel services, tourism, hotels, restaurants, nightclubs, and bars. The author deliberately selected these four terms to comprehensively capture relevant documents from the database, filtering results based solely on the \u0026ldquo;Title, Abstract, and Keywords fields\u0026rdquo;.\u003c/p\u003e \u003cp\u003eThe search was conducted using the following query: \u0026ldquo;TITLE-ABS ( \"service robots\" OR \"social robots\" OR \"intelligent robots\" OR \"mobile robots\" ) AND TITLE-ABS-KEY ( \"tourism\" OR \"hospitality industry\" OR \"leisure\" OR \"travel\") AND PUBYEAR\u0026thinsp;\u0026gt;\u0026thinsp;2013 AND PUBYEAR\u0026thinsp;\u0026lt;\u0026thinsp;2024 AND ( LIMIT-TO (DOCTYPE, \"ar\" ) OR LIMIT-TO ( DOCTYPE, \"cp\" ) )\u0026rdquo;. The subsequent section will outline the abbreviations utilized in this study. This search yielded a total of 620 documents within the specified timeframe, and it was performed on March 28, 2024. \u0026ldquo;The publication records were extracted in CSV format through the advanced search feature provided by Scopus. This file was then imported into MS Excel, and VOSviewer software (version 1.6.20) (2024) was employed for mapping analysis\u0026rdquo; (Postelnicu and Boboc \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, p.3).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e1.2. Inclusion and exclusion criteria\u003c/h3\u003e\n\u003cp\u003eFrom the initial set of 620 documents, the author examined each paper to assess its relevance to both the robotics domain and the tourism sector. All abstracts were reviewed, and the content was analyzed to determine if they met the specified criteria. The study does not include publications that do not meet the previously mentioned criteria, nor those that represent reviews (surveys) or presentations of the current state of research. Only research papers with contributions to the tourism and robotic fields were considered, and finally, a total of 110 documents were selected based on the established criteria (Valeri and Albattat \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The criteria for inclusion required that the articles focus on tourism research involving robotic technology, covering publications from January 1, 2014, to December 31, 2023. Excluded from this review were conference reviews (\"cr\"), literature reviews (\"re\"), book chapters (\"ch\"), entire books (\"bk\"), notes (\"no\"), retracted papers (\"tb\"), and any articles that did not fit the designated keywords. The analysis was limited to journal articles (\"ar\") and conference proceedings (\"cp\"). An initial search, conducted without these restrictions, resulted in 679 documents. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e depicts \u0026ldquo;the process for identifying and selecting the relevant studies\u0026rdquo; (Heirene et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, p. 13). The retrieval of articles followed \u0026ldquo;the PRISMA (\u003cb\u003eP\u003c/b\u003e\u003cem\u003ereferred\u003c/em\u003e \u003cb\u003eR\u003c/b\u003e\u003cem\u003eeporting\u003c/em\u003e \u003cb\u003eI\u003c/b\u003e\u003cem\u003etems for\u003c/em\u003e \u003cb\u003eS\u003c/b\u003e\u003cem\u003eystematic Reviews and\u003c/em\u003e \u003cb\u003eM\u003c/b\u003e\u003cem\u003eeta-\u003c/em\u003e\u003cb\u003eA\u003c/b\u003e\u003cem\u003enalyses\u003c/em\u003e) guidelines\u0026rdquo; (Page et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Postelnicu and Boboc \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, p.3).\u003c/p\u003e \u003cp\u003eThis approach facilitated the identification of key articles relevant to the study topic, organized systematically as a bibliometric analysis rather than a bibliographic presentation. Bibliometric analysis involves measuring, tracking, and analyzing scholarly literature using quantitative methods (Rojas-S\u0026aacute;nchez et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Postelnicu and Boboc \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). It offers a comprehensive understanding of \u0026ldquo;the bibliometric and intellectual landscape of a field by analyzing the social and structural connections between key research components, such as authors, countries, institutions, and topics\u0026rdquo; (Donthu et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Hern\u0026aacute;ndez-Perlines et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, p.4; Postelnicu and Boboc \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e1.3. Data analysis\u003c/h2\u003e \u003cp\u003eEligible articles according to the established criteria were studied using a dedicated program. The analysis yielded several bibliometric indicators, including document type, language, publication year, document and author counts, publication numbers by country and international collaboration, affiliation-based publication counts, authorship metrics, citation counts, publication sources, co-citation analysis, and keyword co-occurrence.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSource: Adapted from Postelnicu and Boboc (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe bibliometric analysis followed these steps:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eDatabase selection: Scopus\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSearch fields: Article Title, Abstract, and Keywords\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTimeframe: January 1, 2014, to December 31, 2023\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eData collection: Data was extracted as a CSV file from Scopus\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAnalysis tools: VOSviewer and Microsoft Excel were used for data analysis\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eResults presentation: The findings were displayed in tables, graphs, and diagrams (Postelnicu, et al. 2024).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"2. Results and discussion","content":"\u003cp\u003eThis section outlines the research results and provides a discussion of the bibliometric analysis, offering a detailed overview of the quantitative scientific output in the field of robotics as it pertains to the tourism and hospitality sectors (Jain et al. 2024).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.1.\u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003cem\u003eOverview of bibliometric information\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe bibliometric analysis identified 110 articles sourced from Scopus, authored by 347 different individuals and published across 67 journals. The majority of these publications are classified as \u0026ldquo;journal articles\u0026rdquo; (79.09%), with \u0026ldquo;conference papers\u0026rdquo; comprising the remaining 20.91% (Fig. 2a). Most articles were written in English (108 records, 98.18%), while 2 were published in Japanese (1.82%). The types of papers that were excluded are depicted in Fig. 2b.\u003c/p\u003e\n\u003cp\u003eThe findings indicate a substantial increase in robotics research within the tourism sector over the past decade. Approximately 59.83% of the total articles were published in the last three years, with yearly publications exceeding 20 (Fig. 3a). The peak publication year was 2023, accounting for 37% of the total. A similar upward trend is seen in the \u0026ldquo;number of authors\u0026rdquo; indicator (Fig. 3b), with the highest number of authors recorded in 2023 (16.36%).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.2. \u0026nbsp;\u003c/em\u003e\u003cem\u003eGeographic distribution of publications\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe research on robotics applications in the tourism and hospitality industry (Mukherjee et al. 2023; Ivanov et al. 2019) originated from 40 countries. These included 18 from Asia, 15 from Europe, 3 from Africa, 2 from North America, 1 from South America, and 1 from Oceania. Fig. 4 illustrates the global distribution of the articles analyzed in this study. Asia emerges as the leading continent, contributing 45.00% of the total publications, followed by Europe (37.50%), Africa (7.50%), North America (5.00%), South America (2.50%), and Oceania (2.50%). Out of the countries studied, 33 (82.50%) produced between 1 and 5 publications, while 6 countries (15.00%) published between 6 and 20 articles, and only 1 country (2.50%) generated more than 20 publications. Notably, China contributed approximately 32.73% (n=36) of the included studies, followed by the United Kingdom at 14.55% (n=16) and the United States at 13.64% (n=15). Among those countries with 6 to 20 publications, the United Kingdom (16 publications) and the United States (15 publications) were the most prolific.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003eTop 12 contributing countries that published more than 3 papers.\u003c/p\u003e\n\u003cp\u003eThe analysis reveals that China makes the most significant contributions to the field. Table 1 lists the top 12 countries based on their contributions, detailing both the number of publications and citations. It is important to note that the total citation counts reflect data retrieved from the Scopus database on March 28, 2024. To provide a clearer picture of the most active countries, Fig. 5 illustrates the \u0026quot;cooperation network\u0026quot; indicator.\u003c/p\u003e\n\u003cp\u003eThis analysis was conducted using VOSviewer software, with a minimum publication threshold of 4 documents per country, resulting in 12 countries that met this criterion. In Fig. 5, the size of the circles represents the volume of publications for each country, while the connecting lines indicate collaborative efforts with other nations. The analysis identifies five main clusters: the first includes China and Australia (blue), the second comprises the United Kingdom, Spain, and Italy (green), the third encompasses the United States and Turkey (purple), the fourth features India, France, and Malaysia (red), and the fifth cluster includes Hong Kong and South Korea (yellow).\u003c/p\u003e\n\u003cp\u003eChina, United Kingdom and United States are the most influential countries with a total link strength (TLS) of 9 for each country, followed by India and Australia. As predicted, the Fig. exemplifies an evolution towards an increased number of papers written with the contribution of several authors.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.3.\u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003cem\u003eAffiliation-based distribution of publications\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis identified a total of 196 research institutions associated with the publications. Among these, 154 institutions (78.57%) contributed only one article, while 39 institutions (19.90%) published two or three studies, and 3 institutions (1.53%) published more than three papers.\u003c/p\u003e\n\u003cp\u003eThe University of Surrey in Guildford emerged as the most prolific academic institution, with six publications. It was followed by Sun Yat-Sen University in Guangzhou, which produced five publications, and Sakarya Universitesi in Sakarya, with four publications. Collectively, the top 12 institutions (Table 2) contributed 42 papers, representing 38.18% of the total articles published.\u003c/p\u003e\n\u003cp\u003eAlthough most institutions involved in research on robotic technologies applied to tourism are universities, the landscape also includes private and governmental organizations, research centers, and various institutes (Ospina-Mateus et al. 2019).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003eTop 12 most productive institutes according to the number of publications and number of citations\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.4. \u0026nbsp;\u003c/em\u003e\u003cem\u003eAuthors and their cooperation\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAs previously noted, the 110 publications involved a total of 347 authors. The number of authors per study varied from 1 to 8, with an average of 3.15 authors per article. Table 3 provides a summary of the publications categorized by the number of authors and the citations each group received. Most articles were authored by 2, 3, or 4 individuals, with the highest citation counts associated with works authored by 3 and 4 authors. Notably, 94.24% (n=327) of the authors published only a single article, while 4.32% (n=15) authored 2 articles, and 1.44% (n=5) published 3 studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003eDistribution of publications based on the number of authors\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 4\u0026nbsp;\u003c/strong\u003eMost-productive authors according to the number of citations\u003c/p\u003e\n\u003cp\u003eTable 4 shows the first 10 of the most prolific authors, considering the number of citations.\u0026nbsp;This table provides information on the selected papers, including author affiliations, countries, the number of publications, citations, and the Scopus h-index. Within this context, Dogan Gursoy (n=394), Daniel Belanche (n=160), and Stanislav Ivanov (n=118) are the top three authors. Based on their Scopus h-index, Dogan Gursoy, with 2 publications, leads the ranking with an h-index of 67. His most cited paper is (Lu et al. 2019), which has received 390 citations. Following him, Daniel Belanche, also with 2 articles, has his most cited work (Belanche et al. 2021) attracting 119 citations. Stanislav Ivanov ranks third, with 2 publications as well, the most cited being (Ivanov et al. 2020a), which has garnered 102 citations in Scopus.\u003c/p\u003e\n\u003cp\u003eFig. 6 details the model relative to the cooperation of the authors. The co-authorship analysis conducted using VOSviewer reveals a network of the 10 authors who have published at least one paper. This analysis identifies three distinct clusters, each represented in different colors. Huang Dan emerges as the most prominent author, with a Total Link Strength (TLS) of 3. It can be mentioned that there is collaboration between authors from the same institution or organization belonging to China.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.5. \u0026nbsp;\u003c/em\u003e\u003cem\u003eDocument citation\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 5 presents data for the most cited articles, including their titles, publication sources, total citations as of 2023, and \u0026quot;Field-Weighted Citation Impact (FWCI)\u0026quot; (Cant\u0026uacute;-Ortiz 2017). The FWCI is a metric that reflects the average citation impact of a document, indicating how often it is cited in comparison to similar works (Purkayastha, et al. 2019). It is calculated using the following formula:\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"531\" height=\"32\"\u003e\u003c/p\u003e\n\u003cp\u003ewhere \u003cem\u003ec\u003csub\u003ei\u0026nbsp;\u003c/sub\u003e\u003c/em\u003erepresents \u0026ldquo;the number of citations received by publication\u003cem\u003e\u0026nbsp;i\u003c/em\u003e and \u003cem\u003ee\u003csub\u003ei\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003edenotes the expected number of citations per publication received by similar publications\u0026rdquo; (Postelnicu and Boboc 2024, p.7).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u0026nbsp;\u003c/strong\u003eTop 10 highly cited papers\u003c/p\u003e\n\u003cp\u003eAmong the ten highest-impact articles, three were published in \u0026quot;Tourism Management\u0026quot; while one article each appeared in the following journals: \u0026quot;International Journal of Hospitality Management\u0026quot;, \u0026quot;Tourism Geographies, Computers in Human Behavior\u0026quot;, \u0026quot;International Journal of Contemporary Hospitality Management\u0026quot;, \u0026quot;Annals of Tourism Research\u0026quot;, \u0026quot;Electronic Markets, and Information Technology and Tourism\u0026quot;.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe article \u0026ldquo;by Lu et al. (2019) received\u0026rdquo; (Husain et al. 2023) the highest total citation count, with 390 citations, and also ranks first in terms of average citations per year, averaging 78 citations. The publications listed in the table were released between 2017 and 2021.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6\u0026nbsp;\u003c/strong\u003eTop 10 most active publications (journals and conference proceedings).\u003c/p\u003e\n\u003cp\u003e\u0026ldquo;A ranking of the top 10 most cited publications, encompassing both journals and conference proceedings, has been compiled (Table 6) to illustrate the influence of these works due to their significant scientific impact. This table includes details such as the source name, ISSN, publisher, number of articles related to the selected topic, percentage of the total articles, total citations received by those articles, journal impact factor, quartile ranking, and CiteScore according to Scimago Journal Ranking\u0026rdquo; (JCR 2022) (Postelnicu and Boboc 2024, p.10).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe \u0026quot;International Journal of Hospitality Management\u0026quot; led with the highest number of publications in the designated timeframe, contributing 9 articles (8.18%). Following it, the \u0026quot;International Journal of Contemporary Hospitality Management\u0026quot; ranked second with 7 publications (6.36%), trailed closely by \u0026quot;Tourism Management\u0026quot; (\u0026quot;International Journal of Tourism Management\u0026quot;) in terms of the number of papers.\u003c/p\u003e\n\u003cp\u003eIn total, 110 articles were published across 67 sources. Among these, 10 sources (14.93%) published more than 2 papers, while 57 sources (85.07%) contributed 1 or 2 articles. Fig. 7 illustrates the annual publication count for the ten most active sources, including both journals and conference proceedings.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.6. \u0026nbsp;\u003c/em\u003e\u003cem\u003eSubject area publications\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe 10 most significant subject areas from the Scopus database, according to their distribution by domains, are presented in Table 8. The analysis revealed that \u0026quot;the \u003cem\u003eBusiness Management Accounting\u003c/em\u003e field made the largest contribution to research\u0026quot; (Olowoselu and ElSayary 2024) on robotics in tourism and hospitality, followed by \u003cem\u003eComputer Science\u003c/em\u003e and \u003cem\u003eSocial Sciences\u003c/em\u003e. It is important to note that some publications span multiple subject areas, resulting in a total publication count that exceeds the 110 selected documents.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable \u0026nbsp;8\u0026nbsp;\u003c/strong\u003eThe top 10 subject areas\u003c/p\u003e\n\u003cp\u003eFig. 8 illustrates the keywords co-occurrence network, generated through the full counting method. Among the 361 keywords analyzed, 10 met the criteria of appearing at least twice, resulting in a keyword network categorized into 6 distinct clusters. These clusters highlight themes with numerous interconnected elements. \u0026ldquo;The size of each circle corresponds to the frequency of the keywords used: the more frequently a keyword appears, the larger the circle\u0026rdquo; (Agyei et al. 2024, p.10). Additionally, \u0026ldquo;a smaller distance between keywords indicates a stronger relationship\u0026rdquo;, based on how often the terms co-occur (Lehner et al. 2023). The diagram reveals that \u0026quot;service robots,\u0026quot; \u0026quot;artificial intelligence,\u0026quot; and \u0026quot;human-robot interaction\u0026quot; are among the most frequently used terms. Specifically, \u0026quot;service robots\u0026quot; appears 47 times with a Total Link Strength (TLS) of 59; \u0026quot;artificial intelligence\u0026quot; occurs 22 times, resulting in a TLS of 50; and \u0026quot;human-robot interaction\u0026quot; has 15 occurrences with a TLS of 29. Other notable terms include \u0026quot;COVID-19\u0026quot; and \u0026quot;robot,\u0026quot; both with 9 occurrences (TLS of 20 and 12, respectively), as well as \u0026quot;robotics,\u0026quot; which appears 7 times and has a TLS of 17. The yellow cluster is associated with service robots and anthropomorphism, encompassing themes like technology acceptance and social presence. The green cluster focuses on artificial intelligence, robots, and service automation. Terms related to human-robot interaction, social robots, and trust are found in the red cluster. The turquoise cluster addresses aspects related to COVID-19 and safety, while the purple cluster includes topics related to robotics, automation, and big data. Lastly, the orange cluster pertains to hospitality and tourism, and the blue cluster features terms linked to hotel service automation and autonomous robots.\u003c/p\u003e\n\u003cp\u003eFig. 9 shows trends of the top 12 keywords from January 1, 2014, to December 31, 2023. In addition to the established term (\u0026quot;service robots\u0026quot;), there are growing trends for topics related to \u0026quot;human-robot interaction\u0026quot; with the most occurrences. It can also be seen that keywords such as \u0026quot;artificial intelligence\u0026quot;, \u0026quot;COVID-19\u0026quot; and \u0026quot;robotics\u0026quot; start to be used later (from 2020) in tourism research, which experiences a staggering collapse in 2020.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter clustering the author\u0026apos;s keywords, it is possible to highlight the most prominent research areas currently using robotic technologies in tourism and hospitality. These emerging technologies are used in many areas of tourism: airports, travel agencies, flight booking, hotel booking, airport security, hotel robots, robot porters, cleaning, food preparation and guests greeting are all areas where robots can be used. Robots are very efficient because they reduce working time and ensure that the work is done correctly. Robots reduce the workload as less manpower is required to do the work.\u003c/p\u003e\n\u003cp\u003eThe bibliometric analysis revealed a significant gap in systematic reviews within the scientific literature regarding the use of robotics in tourism and hospitality (Mukherjee et al. 2023). As such, this paper may serve as a valuable foundation for conducting a systematic literature review.\u003c/p\u003e\n\u003cp\u003eLooking forward,\u0026nbsp;it is clear that the incorporation of robotics into the tourism and hospitality (Ndhlovu et al. 2024) industry holds considerable promise, albeit accompanied by certain challenges. To lay the groundwork for future research, a detailed investigation plan will be developed, concentrating on key issues identified through a thorough keyword analysis. Below is a brief overview of the research agenda, designed to aid both scholars and practitioners in comprehending the evolving \u0026quot;relationship between robotics and the tourism and hospitality sector\u0026quot;, which is increasingly influenced by technological advancements (Jerez-Jerez and Foroudi 2024). Robotics is affecting this industry in various ways:\u003c/p\u003e\n\u003cp\u003e1.\u0026nbsp; \u0026nbsp;Enhanced guest experience:\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;Robotic concierge: Robots can act as concierge assistants in hotels, providing guests with information about the hotel, local attractions, and even making reservations. These robots can make personalised recommendations based on guest preferences.\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;Room service robots: Robots can deliver room service items like food, beverages, and amenities directly to guests\u0026apos; rooms, ensuring a fast and efficient service experience.\u003c/p\u003e\n\u003cp\u003e2.\u0026nbsp; \u0026nbsp;Operational efficiency:\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;Automated check-in/check-out: Self-service kiosks and robotic systems can streamline check-in and check-out processes, decreasing wait times and allowing\u0026nbsp;\u0026quot;staff to concentrate on providing more personalized guest interactions\u0026quot; (Saranya\u0026nbsp;et al. 2025).\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;Cleaning robots: Hotels are increasingly using robotic vacuums and floor cleaners to maintain cleanliness and hygiene efficiently, especially in high-traffic areas.\u003c/p\u003e\n\u003cp\u003e3.\u0026nbsp; \u0026nbsp;Cost reduction:\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;Labour cost savings: Although the initial investment in robotics may be substantial, these technologies can lead to significant long-term savings on labor by automating repetitive and time-consuming tasks. This shift enables human employees to focus on roles that require personal engagement.\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;Inventory management: Robots can help manage inventory and supplies, ensuring that stock levels are maintained efficiently and reducing waste.\u003c/p\u003e\n\u003cp\u003e4.\u0026nbsp; \u0026nbsp;Personalised services:\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;Data collection and analysis: AI-powered robots can analyse guest data to provide tailored recommendations and services. For example, a robot could suggest local dining options based on previous guest reviews and preferences.\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;Language translation: Robots can offer real-time language translation, facilitating communication for international guests and improving their overall experience within the hotel or tourism environment.\u003c/p\u003e\n\u003cp\u003e5.\u0026nbsp; \u0026nbsp;Attraction and entertainment:\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;Interactive exhibits: In tourist attractions and museums, robots can serve as interactive guides, providing educational and engaging experiences. They can provide information, answer questions, and even entertain guests.\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;Themed experiences: Robots can be integrated into themed entertainment experiences, such as robot-themed shows or events, adding a futuristic element to attractions.\u003c/p\u003e\n\u003cp\u003e6.\u0026nbsp; \u0026nbsp;Safety and hygiene:\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;Sanitation robots: Particularly relevant to health and safety, robots can be used to disinfect and sanitise public spaces, helping to ensure a clean and safe environment for guests.\u003c/p\u003e\n\u003cp\u003e7.\u0026nbsp; \u0026nbsp;Accessibility:\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;Assistive robots: Robots can help guests with disabilities by assisting with navigation, carrying luggage, or providing information, thus improving the accessibility of tourism and hospitality services (Sharma, 2024).\u003c/p\u003e\n\u003cp\u003eOverall, robotics has the potential to transform the tourism and hospitality sectors by enhancing operational efficiency, improving guest experiences, and introducing innovative services. Nevertheless, it is vital for businesses to strike a balance between automation and personal interaction, as these human connections remain essential to the guest experience.\u003c/p\u003e\n\u003cp\u003eInterdisciplinary collaboration among computer scientists, psychologists, ethicists, and engineers will be crucial for advancing these research initiatives. Additionally, establishing \u0026ldquo;a robust ethical framework throughout the research and development processes will be essential to ensure the responsible application of robotic technologies within the travel, tourism, and hospitality industries\u0026rdquo; (Ivanov et al. 2020a; Herawan et al, 2023).\u003c/p\u003e"},{"header":" 3. Limitations","content":"\u003cp\u003eThe research conducted for selecting representative articles was confined to the Scopus database. While this database encompasses a broad spectrum of publications across various disciplines, future studies \u0026ldquo;should consider including additional databases to achieve a more comprehensive\u0026rdquo; (Prasad and Subramanian 2024, p. 23) overview while ensuring the quality of the sources. Furthermore, this study provided a quantitative analysis without delving into the content of the articles, which is a notable limitation of bibliometric analyses. Lastly, the extensive number of publications reviewed raises \u0026ldquo;the possibility of including articles that may not align perfectly with the topic\u0026rdquo; (Postelnicu and Boboc 2024, p.13), despite the authors\u0026apos; efforts to adhere to the defined selection criteria Nevertheless, the authors believe that the analysis presented is sufficiently conclusive.\u003c/p\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eRobotics, a key technology associated with Industry 4.0 (Dammacco et al. 2020), has demonstrated its capacity to deliver numerous advantages to \u0026ldquo;the tourism and hospitality sectors, including hotels (e.g., front desk agents, concierges, delivery robots, porters, and housekeepers), restaurants (e.g., chefs, hosts, waitstaff, food runners, bartenders, and food delivery robots), events (e.g., guest entertainment and physical presence for virtual attendees), attractions (e.g., museums), and travel (e.g., airports and autonomous vehicles)\u0026rdquo; (Ivanov et al. 2020b).\u003c/p\u003e\n\u003cp\u003e\u0026ldquo;This study offers a comprehensive overview of research concerning the applications of robotics in tourism and hospitality over the past decade\u0026rdquo; (G\u0026ouml;k\u0026ccedil;e, et al. 2024). The bibliometric analysis reveals a notable surge in research and development efforts in this domain. Findings indicate an increasing interest in robotic technologies and a significant level of international collaboration among authors and organizations. Additionally, there is a rise in interdisciplinary research, bringing together specialists from various fields.\u003c/p\u003e\n\u003cp\u003eOverall, this study provides valuable insights into the current role of robotics in tourism and hospitality. The key findings include:\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;The majority of the analyzed documents are published in English.\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;The number of publications has accelerated significantly in the last five years.\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;Authors from Asia and Europe (notably China and the United Kingdom) lead in publication volume, with a strong collaborative relationship between them.\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;China ranks as the top country in terms of the number of organizations affiliated with authors who have published research.\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;Most articles have three authors, with a nearly equal number of four-author papers, and these tend to have the highest citation counts.\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;The most frequently cited documents are published in academic journals.\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;Elsevier dominates in terms of both the number of papers published and total citations (Hanganu-Bresch et al, 2022; Hern\u0026aacute;ndez-Perlines et al. 2023; Siriwardhana and Moehler 2024).\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u0026nbsp; \u0026nbsp;Among journals, the \u0026ldquo;International Journal of Hospitality Management\u0026rdquo; has the highest publication count.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eCorina Monica Pop is the single author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAgyei, V., Adom-Asamoah, G., \u0026amp; Poku-Boansi, M. 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Transforming Hospitality, Personalized Medicine, and Adaptive Learning: Robotic Innovations. In A. Shaik (Ed.), \u003cem\u003eAI-Powered Advances in Pharmacology\u003c/em\u003e (pp. 373-406). IGI Global. https://doi.org/10.4018/979-8-3693-3212-2.ch014\u003c/li\u003e\n\u003cli\u003eSeyman Guray, T., \u0026amp; Kismet, B. (2023). VR and AR in construction management research: bibliometric and descriptive analyses. \u003cem\u003eSmart and Sustainable Built Environment\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(3), 635-659. https://doi.org/10.1108/SASBE-01-2022-0015\u003c/li\u003e\n\u003cli\u003eSharma, A., (Ed.) (2024). \u003cem\u003eInternational Handbook of Skill, Education, Learning, and Research Development in Tourism and Hospitality.\u003c/em\u003e Springer Singapore. https://doi.org/10.1007/978-981-99-3895-7\u003c/li\u003e\n\u003cli\u003eShome, S. Hassan, M.K. Verma, S., Panigrahi, T.R. (2023) Impact investment for sustainable development: a bibliometric analysis, \u003cem\u003eInt. Rev. Econ. Finance 84,\u003c/em\u003e 770\u0026ndash;800. https://doi.org/10.1016/j.iref.2022.12.001\u003c/li\u003e\n\u003cli\u003eSiriwardhana, S. and Moehler, R.(2024), \u0026quot;Mastering the skills of Construction 4.0: a review of the literature using science mapping\u0026quot;, \u003cem\u003eSmart and Sustainable Built Environment\u003c/em\u003e, 13(4), 989-1014. https://doi.org/10.1108/SASBE-03-2023-0045\u003c/li\u003e\n\u003cli\u003eUmeokafor, N., Umar, T., \u0026amp; Evangelinos, K. (2022). Bibliometric and scientometric analysis-based review of construction safety and health research in developing countries from 1990 to 2021. \u003cem\u003eSafety science\u003c/em\u003e, \u003cem\u003e156\u003c/em\u003e, 105897. https://doi.org/10.1016/j.ssci.2022.105897\u003c/li\u003e\n\u003cli\u003eValeri, M., \u0026amp; Albattat, A. (Eds.). (2024). \u003cem\u003eMetaverse and Tourism: Rethinking Implications on Virtual Reality\u003c/em\u003e. Taylor \u0026amp; Francis.\u003c/li\u003e\n\u003cli\u003eVirkus, S., Leoste, J., Marmor, K., Kasuk, T., \u0026amp; Talisainen, A. (2023). Telepresence robots from the perspective of psychology and educational sciences. \u003cem\u003eInformation and Learning Sciences\u003c/em\u003e, \u003cem\u003e124\u003c/em\u003e(1/2), 48-69. https://doi.org/10.1108/ILS-09-2022-0106\u003c/li\u003e\n\u003cli\u003eVisualising Scientific Landscapes (version 1.6.18). (2024) http://vosviewer.com.\u003c/li\u003e\n\u003cli\u003eYoganathan, V., Osburg, V. S., Kunz, W. H., \u0026amp; Toporowski, W. (2021). Check-in at the Robodesk: Effects of automated social presence on social cognition and service implications. \u003cem\u003eTourism Management\u003c/em\u003e, \u003cem\u003e85\u003c/em\u003e, 104309. https://doi.org/10.1016/j.tourman.2021.104309\u003c/li\u003e\n\u003cli\u003eZeng, Z., Chen, P. J., \u0026amp; Lew, A. A. (2020). From high-touch to high-tech: COVID-19 drives robotics adoption. \u003cem\u003eTourism Geographies\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(3), 724-734. https://doi.org/10.1080/14616688.2020.1762118\u003c/li\u003e\n\u003cli\u003eZhang, Y., Liu, H., Kang, S. C., \u0026amp; Al-Hussein, M. (2020). Virtual reality applications for the built environment: Research trends and opportunities. \u003cem\u003eAutomation in Construction\u003c/em\u003e, \u003cem\u003e118\u003c/em\u003e, 103311. https://doi.org/10.1016/j.autcon.2020.103311\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 8 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"tourism, hospitality, robotics, service robots, bibliometric analysis","lastPublishedDoi":"10.21203/rs.3.rs-5300051/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5300051/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e This study aims to conduct a bibliometric analysis of research publications (Virkus et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) on the application of robotics in the hospitality and tourism industry (Sharma \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Robotics is transforming various industries, including tourism, where technologies such as service robots, social robots, intelligent robots, and mobile robots are increasingly adopted (Ladeira 2023). Publications from 2014 to 2023 were collected from the Scopus database and analyzed (Car\u0026egrave; and Cumming \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) based on several criteria, including document type, language, publication year, country of origin, authorship, affiliations, sources, citations, keywords, and research areas. VOSviewer was used to visualize research trends related to the application of robots in hospitality and tourism. An analysis of 110 documents revealed a consistent increase in publications over the past decade, with China leading in publication output, followed by the United Kingdom and the United States. The International Journal of Hospitality Management emerged as the most prolific journal in this field, and the University of Surrey, Guildford, was identified as the leading institution in terms of publication volume. Keyword analysis underscored the primary research areas associated with service robots in tourism. This bibliometric study highlights the expanding literature on robotics applications within the tourism sector and serves as a valuable resource for researchers and industry stakeholders seeking to understand the current state and trends in the field (Valeri and Albattat \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e","manuscriptTitle":"Robotics in the Travel, Tourism, and Hospitality Sector: A Bibliometric Analysis of Publications from 2014 to 2023","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-25 17:58:19","doi":"10.21203/rs.3.rs-5300051/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f9196c08-3d00-4511-995f-ba92604dbe1d","owner":[],"postedDate":"October 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-11-23T14:08:44+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-25 17:58:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5300051","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5300051","identity":"rs-5300051","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}