Progess on robotics in hospitality and tourism a review of the literature

Progress on robotics in hospitality and tourism: a review of the literature Stanislav Ivanov Varna University of Management, 13A Oborishte Str., 9000 Varna, Bulgaria, e-mail: stanislav.ivanov@vumk.eu Ulrike Gretzel USC Center for Public Relations, Annenberg School of Communication & Journalism, University of Southern California, 3502 Watt Way, Los Angeles, CA 90089, USA, e-mail: gretzel@usc.edu Katerina Berezina College of Hospitality and Tourism Leadership, University of South Florida Sarasota-Manatee, FL, USA, e-mail: katerina@katerinaberezina.com Marianna Sigala School of Management, University of South Australia Business School, Australia, e-mail: marianna.sigala@unisa.edu.au Craig Webster Department of Management, Miller College of Business, Ball State University, Muncie, Indiana, USA, e-mail: cwebster3@bsu.edu Abstract Purpose Provides a comprehensive review of research on robotics in travel, tourism and hospitality Identifies research gaps and directions for future research Design/methodology/approach Analyzes 131 publications published during 1993-2019 identified via Scopus, Web of Science, ResearchGate, Academia.edu and Google Scholar This includes quantitative analysis of frequencies and cross-tables, and qualitative thematic analysis of the publications within each of seven identified domains Findings Identifies ‘Robot’, ‘Human’, ‘Robot manufacturer’, ‘Travel / tourism / hospitality company’, ‘Servicescape’, ‘External environment’, and ‘Education, training and research’ as research domains Most research is dedicated to robots in restaurants, airports, hotels and bars Papers tend to apply engineering methods, but experiments and surveys grow in popularity Asia-Pacific countries account for much of the empirical research Research limitations/implications Electronic copy available at: https://ssrn.com/abstract=3335817 The analysis was limited to publications indexed in databases and search engine Only publications in English were considered Growing opportunities for those who are anxious to publish in the field are identified Importantly, emerging research is branching out from the engineering of robots to the possibilities for human/robot interactions and their use for service providers, opening up new avenues of research for tourism and hospitality scholars Practical implications The paper identified a myriad of application areas for robots across various tourism and hospitality sectors Service providers must critically think about how robots affect the servicescape and how it needs to be adjusted or re-imagined to ensure that robots and employees can augment the service experiences (co-)created within it Originality/value First study to systematically analyze research publications on robotics in travel, tourism and hospitality Keywords: robotics; robonomics; robot design; robot adoption; servicescape; rService; human-robot interaction; research agenda Article classification: Literature Review Citation: Ivanov, S., Gretzel, U., Berezina, K., Sigala, M., & Webster, C (2019) Progress on robotics in hospitality and tourism: a review of the literature Journal of Hospitality and Tourism Technology (forthcoming) Electronic copy available at: https://ssrn.com/abstract=3335817 Introduction 1.1 Rationale and research background Travel, tourism and hospitality have served as application areas for robotics for quite some time The first publication dealing with the topic was published in 1993 by Schraft and Wanner and presented an aircraft cleaning robot Much of the research at the beginning was performed by engineers and only recently tourism/hospitality researchers actually entered the field and added a tourism/hospitality social science flavour to robotics research (e.g Berezina, 2018; Collins et al., 2017; Ivanov et al., 2017, 2018; Kuo et al., 2017; Murphy et al., 2017a, b; Tung & Law, 2017; Tung & Au, 2018; Tussyadiah et al., 2017; Tussyadiah & Park, 2018) The growing interest in robotics in travel, tourism and hospitality raises the need for a systematic review of research on the topic and an identification of future research avenues in the field Such a meta-analysis is currently missing from the literature Therefore, this review paper looks into the academic literature on robots and its relevance to the travel, tourism and hospitality industries The concept of the robot is not particularly old, only being coined in 1920 by Karel Čapek in his play R.U.R— Rossum’s Universal Robots (NPR, 2011), and it took several decades before the concept was incorporated fully into popular culture By the 1950s, Hollywood and popular culture had broadly disseminated the concept of the robot and inspired robot development By 1956, the first company to produce a robot, Unimation, was founded (International Federation of Robotics, 2012) Today, industrial robots are widely used in agriculture (Driessen & Heutinck, 2015), manufacturing (Pires, 2007), warehousing and logistics (Min, 2010), transportation (Maurer et al., 2016), and medicine (Schommer et al., 2017) Service and social robots (Agah et al., 2016; Ferreira, 2017; Wirtz et al., 2018) are commonly used in education (Timms, 2016) and elder care (Glende et al., 2015) While there may be colloquial understandings of what a robot is, there is also a more technical and industry-accepted definition A robot is defined as an “actuated mechanism programmable in two or more axes with a degree of autonomy, moving within its environment, to perform intended tasks” (International Organization for Standardization, 2012: n.p.) The paper adopts this definition to guide the review The incorporation of robotics came relatively late to the industries involved in travel, tourism and hospitality, probably since many of the services provided require sophisticated reactions to the needs of the customer While some automobile factories were largely staffed by robots by the mid-1990s, it was only in 2015 that a hotel predominantly staffed by robots opened (the Henn-na Hotel in Japan, http://www.h-n-h.jp/en/) While most hotels and hospitality operations are not as automated as the Henn-na Hotel in Japan, there are increasing concerns regarding the way in which such robotic and artificial intelligence technologies will be incorporated into travel, tourism and hospitality (Ivanov et al., 2017; Murphy et al., 2017b) At present, robots are used in hotels for such tasks as checking guests in, vacuuming floors, delivering things to guests, concierge services, and other common chores Robots are also involved in many other services in tourism and related industries, such as preparing drinks, entertaining guests, guiding guests and offering information to guests (Ivanov et al., 2017) As application areas expand, more (and more diverse) research will be needed to inform development and implementation efforts A meta-analysis of relevant existing literature can provide important guidance in this respect (Gretzel & Kennedy-Eden, 2012) Electronic copy available at: https://ssrn.com/abstract=3335817 This paper examines how the academic literature has evolved with regards to robotics and the travel, tourism and hospitality industries The value of the paper lies in its summary of relevant academic literature, its depiction of the state of the art of research in this context, and its identification of research gaps that can inform future research efforts Since robotics will be increasingly used in these industries, such a comprehensive review of the literature can also provide important practical insights for robot design and implementation 1.2 Purpose The purpose of this study is two-fold First, this paper aims to provide a comprehensive review of research on robotics in travel, tourism and hospitality Second, based on the analysis of available literature, this paper will identify research gaps and directions for future research Methodology 2.1 Data collection The intention was to gather as comprehensive as possible a picture of English-language academic research linking the study of robots to travel, tourism and hospitality Data were collected during July-August 2018 The world’s two largest databases with scientific publications (Elsevier’s Scopus and Clarivate’s Web of Science) served as the main source of data The authors implemented extensive searches in the two databases by using a combination of two search words in the title, abstract and key words of the publications: Search word 1: robot Search word 2: travel, tourism, hospitality, leisure, recreation, hotel, hostel, lodging, accommodation establishment, restaurant, bar, travel agency, tour operator, travel agent, airport, airline, port, ship, bus station, bus, train station, train, event, car, rent-a-car, car rental, museum, casino, theme park, amusement park The authors read the title and the abstract of every publication displayed in the search results If the paper was considered relevant for the research, the full text was obtained In total, 92 relevant publications were identified in Scopus and 80 in Web of Science – 72 of them appeared in both databases, 20 were included only in Scopus, while appeared only in Web of Science As Scopus and Web of Science, although extensive databases, are far from comprehensive, the authors enriched the publications list by looking for relevant publications with the same search word combinations in the two largest archive websites with academic publications (Academia.edu and Researchgate.net) and the most popular free academic search engine – Google Scholar In this way 55 additional publications were identified In total 154 relevant publications were found through all five sources (Scopus, Web of Science, Academia.edu, Researchgate.net and Google Scholar) After deleting all duplicates the final dataset included 131 publications (see Appendix 1) 2.2 Data analysis For each publication in the dataset the following characteristics were obtained: type of publication (journal article, conference paper or book chapter), year of publication and full reference The full text of each publication was read and the paper was classified according to the following criteria: Electronic copy available at: https://ssrn.com/abstract=3335817  Research focus – whether the paper adopted a supply-side perspective regarding the discussion of the topic (i.e the view point of the company), a demand-side perspective (i.e the view point of the customer) or both perspectives, although one of them might be prevailing  Tourism sector focus of the paper – the individual travel/tourism/hospitality sectors like hotels, restaurants, bars, airports, museums, etc., or all sectors in general  Research methodology, research approach applied in the paper – engineering, experiment (field, laboratory), survey (questionnaire, interview), content analysis of customer reviews, observation, biometrics (eye-tracking, skin response, etc.), mathematical modelling / optimization, or the paper was conceptual / descriptive The ‘engineering’ group consisted of all technical methods that dealt with the actual design, programming and manufacturing of a robot  Country of focus, country in which data was collected, if empirical research was implemented  Research domains – seven broad research domains were identified based on the focal actor/action domain: 1) Robot – design, mobility, navigation, information processing, communication, functionality, appearance, autonomy, etc.; 2) Human (customer and employee) – perceptions and attitudes/acceptance, adoption of robots, use behavior, robot mediated interaction, robot personalization, etc.; 3) Tourist company – the impact of robots on its operations, human resources, marketing, finances, etc.; 4) Robot manufacturers – robot development agenda, pricing of robots, resources used, partnerships with other companies, etc.; 5) Servicescape – changes in servicescape due to the use of robots, active adjustments to servicescape/workflow, robot friendliness of tourism/hospitality facilities, etc.; 6) External environment – legal and ethical issues arising from the use of robots, impact of robots on labor market, etc.; and, 7) Education, training and research in robotics in travel, tourism and hospitality It should be noted that a paper could deal with more than one tourism sector, methodology, country of focus and/or research domain Hence, the grouping of papers according to these criteria is not mutually exclusive The paper applies both quantitative and qualitative analysis of research publications on robotics in travel, tourism and hospitality The quantitative analysis is based on frequencies, cross-tables and respective test statistics (Chi-square test) Due to the small number of publications per year, the 27-year period between the first publication in the dataset (Schraft & Wanner, 1993) and the latest one (Claveau & Force, 2019) was divided into five 5-year blocks (the first one with 7-years due to the small number of publications) in order to facilitate the quantitative analysis The qualitative analysis involves thematic analysis of the publications within each of the identified domains Findings 3.1 General overview Tables 1, and elaborate the quantitative results The findings reveal several key trends: First, after a modest start with only publications in total in 1993-1999 and in 2000-2004, the number of publications jumped to 13 in 2005-2009, 33 in 2010-2014 and reached 75 in 2015-2019 It is important to note that at the time the research was conducted, the most recent 5-year interval was not over yet; consequently, the Electronic copy available at: https://ssrn.com/abstract=3335817 study included several publications from 2019 that appeared online through early publication services, but did not include all research that would eventually be published in 2019 Nevertheless, this time period has already proved to be the most productive in terms of the number of publications The research on robots in travel, tourism and hospitality is gaining strong momentum and one may expect it to significantly increase in the future, in line with the actual adoption of robots by tourist companies Second, the majority of publications (78 or 59.54%) are conference papers, while 47 (or 35.88%) are journal articles This result is logical, considering the fact that the field of robotics is rapidly developing and conference proceedings provide faster and more flexible (in terms of topics and methodologies) publication opportunities compared to journals, which usually employ a prolonged review process and are more selective Conference papers are also seen as more prestigious in most engineering and computer science fields The lack of books on the topic is notable as it suggests that robotics in tourism is currently not taught as a stand-alone subject and that the topic has not reached the maturity level at which researchers are able to publish comprehensive works or publishers become interested in supplying handbooks Third, more than half (70 or 53.44%) of publications adopt a supply-side perspective (i.e the robot-related issues are discussed from the perspective of the company), 28 (21.37%) refer to the demand-side (the robot-related issues are discussed from the perspective of the user/customer), while 33 (25.19%) adopt both perspectives, although for many publications of the latter group, the supply-side perspective is much stronger than the demand-side As a matter of fact, the overwhelming majority of publications that adopt a supply-side perspective only (63 out of 70 or 90%) are either engineering papers (e.g explaining the design of a robot with tourism application) or conceptual (e.g discussing how tourist companies can use robots) However, results in Table indicate that the number of publications that adopt a demand-side focus or present both perspectives is increasing since 2010 – papers deal not only with the design of the robot, its autonomy, navigation, etc., but also the human-robot interaction, user perceptions and acceptance of robots as service providers Further, the most popular tourism sectors are restaurants (42 or 32.06% of analyzed papers), followed by hotels (25 papers or 19.08%), airports (23 papers or 17.56%), and bars (11 papers of 8.40%), i.e the sectors where robots can mitigate labor shortages (e.g restaurants, bars, hotels), where spacious premises facilitate a robot’s navigation and make cleaning robots very attractive (e.g restaurants, hotels, airports), where tasks require low level skills and can be easily divided, or where there is considerable traffic flow that robots can help manage through the provision of information (e.g airports) It is interesting to note that museums were initially quite popular among researchers (they were the focus of out of papers published before 2004) but later lost their allure A possible explanation might be the limited opportunities for commercialization of museum robots Museums provide large spaces (hence facilitating robot navigation), a well-structured environment (premises not change), and the information robots need to provide to visitors does not change often; hence, museums are excellent grounds for testing robot prototypes in controlled environments However, the sheer number of hotels, restaurants, bars and airports globally and the number of robots they could employ, make them much more attractive from a commercial point of view, which may explain the shift in the tourism sector focus observed in research publications after 2005 Electronic copy available at: https://ssrn.com/abstract=3335817 As far as the research methodology is concerned, more than half of the publications (74 or 56.49%) employ engineering methods related to robot design, navigation, face / object / speech recognition, autonomy, etc., while 58 (44.27%) involve some form of a field or laboratory experiment (e.g testing a robot’s capabilities in different restaurant settings) Surveys and interviews (27 publications or 20.61%) have experienced growing popularity during the last 10 years, mostly due to the increasing number of publications with a focus on users/customers and generally more interest in the topic by social scientists Observation (e.g direct observation or reviewing surveillance camera recordings of robot behavior or human-robot interactions) has received considerable application as well (23 publications or 17.56%), while innovative methods like biometric methods are just entering the field (they were used in only papers) Conceptual papers increased significantly after 2015 when tourism / hospitality researchers (not only engineers) entered more bravely into robotics and started publishing papers on various aspects of the application of robots in tourism / hospitality settings Japan leads by country of focus for empirical papers (24 or 18.32% of all publications), followed by Germany, USA and China – see Table Asia-Pacific countries (Japan, Republic of Korea, Macao, Taiwan, Thailand) are the empirical setting of nearly a third of all publications (39 or 29.77%) Considering that Asia-Pacific countries have the highest concentration of robots in the world (IFR, 2018), such a result is not surprising It is noteworthy that countries with demographic decline seem most interested in robotic labor Regarding the research domains, the findings reveal that most papers (104 or 79.39%) concentrate on the robot itself, 81 (61.83%) focus on the human, while 66 (50.38%) discuss the impact of robotics on companies Research in the servicescape domain has been initially quite modest, probably due to the very small number of service robots in business, but since 2015 it has increasingly attracted the attention of tourism / hospitality researchers The other three domains (robot manufacturers, external environment and education/training/research) are discussed in less than 10% of the papers However, research in two of these domains (external environment and education/training/research) seems quite recent, with all of the papers published in the last years This suggests growing concerns with the legal and ethical implications of the use of robots in service domains as well as emerging educational opportunities and needs Table shows the cross-tabulation between the research domain (columns) and tourism sector focus and research methodology (rows) Results indicate that the papers are very concentrated in specific sectors, domains and methodologies For example, most papers on airport robots fall within two domains – ‘Robot’ and ‘Tourist company’, papers on restaurant and hotel robots – within ‘Robot’, ‘Human’ and ‘Tourist company’, while all papers on robots for bars discuss robot design Papers within the ‘Servicescape’ domain deal with restaurant and hotel robots or with all tourism sectors It is interesting to note that half of the papers within the ‘External environment’ and ‘Education, training, research’ domains not have a particular tourism sector focus, but deal with all of them simultaneously, probably due to the more general nature of the topics discussed in these two domains (e.g ethics, training, education) Electronic copy available at: https://ssrn.com/abstract=3335817 Examining research domain and methodology, most papers in the ‘Robot’ domain employ engineering methods (71 publications in the domain or 68.27%) or involve a field or laboratory experiment (49 papers or 47.12%) The same methods are most popular for publications in the ‘Human’ domain, while papers within the ‘Tourist company’ and ‘Education, training, research’ are predominantly and papers within the ‘External environment’ are exclusively conceptual The findings are logical because the topics discussed in each domain determine, at least to some extent, the method Obviously, research on robot design, navigation, autonomy, etc., would require the application of engineering methods, while the more theoretical domain of ‘External environment’ would call for conceptual papers INSERT TABLES 1, AND AROUND HERE We now turn our attention to the qualitative analysis of research publications within the framework of the seven domains 3.2 Research domains The research domains reflect the human and non-human actors and action domains that the existing literature on robotics in tourism and hospitality addresses Figure graphically portrays these seven domains as well as their interactions The robot domain describes various aspects that pertain to the robots themselves These include all areas of their design, such as functionality, mobility and autonomy, with appearance being highlighted because of its prominence in the literature The human domain includes both consumers and employees who are exposed to these robots The third domain refers to robot manufacturers, meaning companies that provide the hardware and/or software as well as services, such as customization or maintenance, needed for implementing robots in tourism and hospitality contexts The tourist company domain encompasses all functions within tourism and hospitality providers, ranging from operations to human resources to marketing and finances The servicescape domain describes the space in which robotic services are (co-)created by robots, tourist companies, employees and consumers, and which can be described in terms of its robot-friendliness The external environment domain includes the legal, ethical, social and economic frames and conditions that shape, and are in turn shaped by, the introduction of robots into the tourism and hospitality context Last, education, training and research institutions are treated separately from this external domain because of their particular role in influencing and understanding the other domains The diagram emphasizes the many ways in which these domains interact or overlap While there are publications that are purely focused on robots, others acknowledge the influence of existing research/algorithms, company requirements, servicescape parameters, and current manufacturing on their design Many studies deal with the influence of robots on human perceptions and behaviors and some on the way humans influence robots The way in which humans and robots interact or should interact with each other is also a popular topic, while possible robot-mediated interactions between customers and employees have not been studied as much Robots impact the operations and general functioning of tourism and hospitality companies, and these companies, in turn, design servicescapes that influence what robots can and cannot and what human actors experience The literature further acknowledges that companies and manufacturers both use and facilitate research This research influences robot design as well as the training of engineers and hospitality employees The literature also points Electronic copy available at: https://ssrn.com/abstract=3335817 out that manufacturers now sell directly to consumers, enabling customers to bring their own robots into the servicescape Robot adoption is also an important area of research and is influenced by the features of the robots, the availability, pricing and sales conditions set forth by the manufacturers, the customer and employee attitudes and skills shaped by educational and training institutions, and the needs and innovativeness of companies All these interactions happen within a particular external environment that either facilitates or hinders them The following sections describe the specific themes that emerged within the seven domains in greater detail INSERT FIGURE AROUND HERE 3.3 The robot The design of the robot itself was identified as the most prominent theme in all studies collected for the purpose of this research Table shows that robot design for the travel, tourism and hospitality industry was discussed in 104 (79.39%) out of 131 publications used in the current study The earliest publication on this topic was written by Schraft & Wanner in 1993 Since then, the topic was steadily gaining attention, and peaked in 2015-2019 with 53 relevant publications Robot design for the hospitality and tourism industry was most frequently investigated in the context of the restaurant subsector (32 publications, 30.77%), followed by airports (22 publications, 21.15%), and hotels (17 publications, 16.35%) A few articles on robot design were written in relation to bars, museums, train stations, guides, casinos, and theme parks Methodologically, these papers mainly relied on engineering (71 publications, 68.27%) and experimental methods (49 publications, 47.12%), or were conceptual in nature (39 publications, 37.5%) (Table 3) Robot design research is essential for laying the foundation for robot applications in our field, both conceptually and technically It ensures effective design and deployment of robots in the hospitality and tourism industry, as well as efficient execution of intended tasks More specifically, the topics covered in these studies included robot appearance; mapping, path planning and navigation; collision/obstacle avoidance; vision calibration and image recognition (including object and facial recognition); object manipulation (e.g., dishes at a restaurant, luggage at the airport); socially interactive behaviors and levels of interactivity; and, robot persuasiveness Studies on robot design may be further classified based on three main categories of robot use in the hospitality and tourism industry: autonomously functioning robots, robots interacting with other robots, and robots interacting with humans Autonomously functioning robots perform independent tasks on their own For example, such robots may include airport surveillance robots (Acaccia et al., 2006; Capezio et al., 2007; Donadio et al., 2018), robots cleaning tables at a restaurant (Acosta et al., 2006), or robots screening luggage at airports (DeDonato et al., 2014) Instead of dealing with the interaction of robots and humans, this stream of research focuses on precision and accuracy in robot design, navigation, and vision Once robots engage in interactions with either other robots or humans, the research topics that are associated with these types of robots represent an additional layer of complexity, which is needed to ensure smooth operations in the interactive environments Robot-to-robot interactions can result in the creation of multi-robot systems (MRS) that may offer enhanced performance to the hospitality and tourism organizations For example, Electronic copy available at: https://ssrn.com/abstract=3335817 such MRSs have been considered for preparing airplanes for departure (El-Ansary et al., 2016), debris cleaning on airport runways (Öztürk & Kuzucuoğlu, 2016), and creating smart restaurants (Huang & Lu, 2017) The papers written in this domain concentrate on the design of the entire system, and optimization algorithms that would enable smooth robot interactions and cooperation Human-robot interaction in the hospitality and tourism industry may be observed through interaction with customers, for example, in the case of a robot waiter (Cheong et al., 2016; Lehmann et al., 2014), bartender (Foster et al., 2012; Keizer et al., 2014), or robot-guide (Joosse & Evers, 2017), and in the case of interaction with staff members, such as for airplane maintenance (Donadio et al., 2018) Once robots start interacting with humans, new research topics emerge that cover such behavior For example, research studies related to the design of robots that will be interacting with humans evaluated levels of interactivity and ability to influence crowd flow (Caraian et al., 2015), socially interactive behaviors (Chung et al., 2016), and robot persuasiveness (Herse et al., 2018) A more detailed review of the studies on human-robot interaction is provided in Section 3.4 3.4 The human Issues related to robot use by consumers and employees are heavily researched within the tourism domain However, studies mainly relate to interaction and adoption topics and they not equally cover (or not cover at all) the four dimensions relating to human-robot interaction, namely usability, social acceptance, user experience and societal impact (Weiss et al., 2009) Moreover, the majority of the studies is found in hotels, restaurants, and bars and much less in other tourism sectors such as airports, trains, events, and theme parks (Table 3) Most studies adopt an engineering and experimental approach, followed by survey and observation research (Table 3) Earlier studies have focused on examining the technical dimensions of robot interaction (primarily with customers and less with employees), which are heavily influenced by functional dimensions – engineering capabilities and features of robots For example, research has examined issues of localization, mapping, avoiding collision with or serving, guiding / following humans in various tourism contexts such as: public spaces (Burgard et al, 199), restaurants (Tzou & Su, 2009; Yu et al., 2012), entertainment parks (Kober et al., 2012), museums (Thrun et al., 1999), and train stations (Shiomi et al., 2011) The aim of this stream of research was to perfect the functional capabilities of robots so that they can easily physically interact and behaviorally navigate with and around humans In this vein, research focused on evaluating robot-consumer interaction using performance metrics such as response time of robots, accuracy of response to customers, and robots’ understanding of people’s presence (e.g Pinillos et al., 2016) As the technical capabilities of the robots advanced and socio-emotional and intelligent capabilities that enable robots to carry out meaningful interactions with humans emerged (e.g Neumann et al., 2016; Lehmann et al., 2016; Mokhtari et al., 2016), the focus of the research turned towards understanding the socio-psychological implications and dimensions of robot-human interactions To that end, more studies started adopting a survey and observational approach for examining and understanding human reactions to robots However, the majority of these studies focuses on the customer’s rather than the employee’s perspective Electronic copy available at: https://ssrn.com/abstract=3335817 Ivanov, S., & Webster, C (2018) Adoption of robots, artificial intelligence and service automation by travel, tourism and hospitality companies – a cost-benefit analysis In Marinov, V., Vodenska, M., Assenova, M & Dogramadjieva E (Eds) Traditions and Innovations in Contemporary Tourism Cambridge 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Year of publication 2000- 2005- 20102004 2009 2014 13 33 10 20 13 12 29 10 26 10 15 2 11 10 2 1 1 1 12 29 21 12 11 27 17 - 20152019 75 43 26 44 35 28 20 39 16 19 24 13 1 13 53 48 44 29 8 27 29 17 Total 131 78 47 92 80 32 28 70 33 25 42 11 23 1 1 15 104 81 66 11 42 8 74 58 27 Share of total publications 100.00% 59.54% 35.88% 4.58% 70.23% 61.07% 24.43% 21.37% 53.44% 25.19% 19.08% 32.06% 8.40% 3.05% 3.82% 0.76% 17.56% 3.82% 0.76% 0.76% 0.76% 0.76% 2.29% 11.45% 79.39% 61.83% 50.38% 8.40% 32.06% 6.11% 6.11% 56.49% 44.27% 20.61% 0.76% - 12 23 23 17.56% 3.05% 17.56% 1 11 36 51 38.93% Notes: ‘Other’ includes publications in Academia.edu, ResearchGate and papers indexed by Google Scholar, but not included in Scopus or Web of Science Some papers are indexed both in Scopus and Web of Science; One paper can focus on more than one tourism sector; One paper can be classified in more than one research domain; More than one research methods can be applied in a paper Electronic copy available at: https://ssrn.com/abstract=3335817 Table Number of publications by year of publication and country of focus 19941999 - Year of publication 2000- 2005- 20102004 2009 2014 13 33 1 1 13 Total 20152019 75 2 13 1 2 1 38 Share of total publications 100.00% 0.76% 1.53% 0.76% 4.58% 9.16% 0.76% 18.32% 0.76% 1.53% 1.53% 0.76% 1.53% 0.76% 3.05% 3.05% 1.53% 0.76% 1.53% 7.63% 42.75% 131 Total number of publications Argentina Country of focus (in Australia alphabetical Bangladesh order) China, PR Germany 12 India Japan 24 Korea, Republic of Macao, SAR, China Netherlands Pakistan Portugal Russia Spain Taiwan Thailand Turkey UK USA 10 Not applicable or not 56 specified Note: Not applicable (if conceptual paper) or not specified (if empirical paper but the country is not mentioned) Electronic copy available at: https://ssrn.com/abstract=3335817 Table Number of publications by research domain, tourism sector focus and research methodology Total number of publications in the research domain Hotels Tourism sector focus Restaurants Bars Events Museums Guides Airports Train stations Casinos Taxis Theme parks Sex tourism Hospitality (in general) All tourism sectors Engineering Research methodology Experiment (field, laboratory) Survey (questionnaire, interview) Content analysis of customer reviews Observation Biometric Mathematical modelling / Optimization Conceptual / Descriptive Research domains Robot Servicescape manufacturer Robot Human Tourist company 104 81 66 11 42 17 32 11 22 1 71 49 18 20 20 19 25 10 5 1 10 38 44 24 20 10 17 19 12 27 26 14 14 1 10 4 39 33 42 Electronic copy available at: https://ssrn.com/abstract=3335817 Total External environment Education, training, research 131 12 2 3 21 18 10 11 2 - 1 2 - 24 42 11 22 1 1 15 74 58 27 23 23 23 50 Chisquare χ2=83.690 (N=338, df=78, p=0.309) χ2=70.859 (N=660, df=42, p=0.004) Figure Research domains identified in the robots and tourism/hospitality literature Development of robots Robot Impacts on skills and well-being Human Design Human-robot interaction Customer Robot-mediated or enhanced interaction Appearance Employee Servicescape Education Training Research Robotfriendliness of the environment Servicescape design Adoption of robots Education institutions Robots manufacturers Tourist company Impacts Operations Finances Human resources Marketing Education / Training / Research External environment Electronic copy available at: https://ssrn.com/abstract=3335817 Appendix List of publications on robots in travel, tourism and hospitality included in the analysis (in alphabetical order) 10 11 12 13 14 15 16 17 18 19 20 Abad, P., Franco, M., Castillón, R., Alonso, I., Cambra, A., Sierra, J., & Murillo, A C (2017, November) Integrating an Autonomous Robot on a Dance and New Technologies Festival In Iberian Robotics conference (pp 75-87) Springer, Cham Acaccia, G M., Bruzzone, L E., & Razzoli, R P (2006, January) Mobile Robots for Airports Surveillance: A Modular Solution In ASME 8th Biennial Conference on Engineering Systems Design and Analysis (pp 705-711) American Society of Mechanical Engineers Acosta, L., González, E., Rodríguez, J N., & Hamilton, A F (2006) Design and implementation of a service robot for a restaurant International Journal of Robotics & Automation, 21(4), 273-280 Aoki, H., Fujimoto, Y., Suzuki, S., Sato-Shimokawara, E., & Yamaguchi, T (2011) Difference in physiological responses by different cultural greetings using a robot In International Workshop on Advanced Computational Intelligence and Intelligent Informatics (Suzhou, China), 2011 Asif, M., Sabeel, M., & Mujeeb-ur-Rahman, K Z (2015, November) Waiter robot–solution to restaurant automation In Proceedings of the 1st student multi disciplinary research conference (MDSRC), At Wah, Pakistan (pp 14-15) Böhlen, M., & Mateas, M (2002) Machines with a different calling In IROS 2002: international conference on intelligent robots and systems (pp 1172-1177) Burgard, W., Cremers, A B., Fox, D., Hähnel, D., Lakemeyer, G., Schulz, D., & Thrun, S (1999) Experiences with an interactive museum tour-guide robot Artificial intelligence, 114(1-2), 3-55 Capezio, F., Mastrogiovanni, F., Sgorbissa, A., & Zaccaria, R (2007, October) The ANSER project: Airport nonstop surveillance expert robot In Intelligent Robots and Systems, 2007 IROS 2007 IEEE/RSJ International Conference on (pp 991-996) IEEE Caraian, S., Kirchner, N., & Colborne-Veel, P (2015, March) Moderating a Robot's Ability to Influence People Through its Level of Sociocontextual Interactivity In Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction (pp 149-156) ACM Chen, C., Gao, Q., Song, Z., Liping, O., & Wu, X (2010, July) Catering service robot In Proceeding of the 8th World Congress on Intelligent Control and Automation (WCICA), 2010 (pp 599-604) IEEE Cheong, A., Lau, M W S., Foo, E., Hedley, J., & Bo, J W (2016) Development of a robotic waiter system IFAC-PapersOnLine, 49(21), 681-686 Cheung, C W., Tsang, T I., & Wong, K H (2017) Robot Avatar: A Virtual Tourism Robot for People with Disabilities International Journal of Computer Theory and Engineering, 9(3), 229 Chung, M J Y., Huang, J., Takayama, L., Lau, T., & Cakmak, M (2016, November) Iterative Design of a System for Programming Socially Interactive Service Robots In International Conference on Social Robotics (pp 919-929) Springer, Cham Claveau D., Force S (2019) A Mobile Social Bar Table Based on a Retired Security Robot In: Kim JH et al (eds) Robot Intelligence Technology and Applications RiTA 2017 Advances in Intelligent Systems and Computing, vol 751 Springer, Cham Collins, G R., Cobanoglu, C., Bilgihan, A., & Berezina, K (2017) Hospitality information technology: Learning how to use it (8th ed.) 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Total number of publications Argentina Country of focus (in Australia alphabetical Bangladesh order) China, PR Germany 12 India Japan 24 Korea, Republic of Macao, SAR, China Netherlands Pakistan