Wolfgang Wörndl Chulmo Koo Jason L. Stienmetz Editors Information and Communication Technologies in Tourism 2021 Proceedings of the ENTER 2021 eTourism Conference, January 19–22, 2021 Information and Communication Technologies in Tourism 2021 Wolfgang W ö rndl • Chulmo Koo • Jason L. Stienmetz Editors Information and Communication Technologies in Tourism 2021 Proceedings of the ENTER 2021 eTourism Conference, January 19 – 22, 2021 123 Editors Wolfgang W ö rndl Department for Informatics Technical University of Munich Garching bei M ü nchen, Bayern, Germany Jason L. Stienmetz Department of Tourism and Service Management MODUL University Vienna Vienna, Wien, Austria Chulmo Koo Smart Tourism Education Platform (STEP) College of Hotel and Tourism Management Kyung Hee University Seoul, Korea (Republic of) ISBN 978-3-030-65784-0 ISBN 978-3-030-65785-7 (eBook) https://doi.org/10.1007/978-3-030-65785-7 © The Editor(s) (if applicable) and The Author(s) 2021. 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This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Preface The 28th Annual International eTourism Conference ENTER21@yourplace features new research, innovative systems, and industry case studies on the appli- cation of Information and Communication Technologies (ICT) in travel and tour- ism. Organized by the International Federation for IT and Travel & Tourism (IFITT), ENTER21@yourplace takes place online, January 19 – 22, 2021, with the theme “ eTourism: Development Opportunities and Challenges in an Unpredictable World. ” The research track of ENTER21@yourplace received a total of 88 full and short paper submissions, covering a diverse variety of fi elds within the area of ICT and tourism. Each research paper submission went through a rigorous double-blind review process. As a result, 32 full papers and 23 short papers were accepted for presentation at the conference and are included in these proceedings. While still maintaining a broad topic, the papers presented in this volume advance the current knowledge base of ICT and tourism in the following areas: social media and sharing economy, technology including AI-driven technologies, research related to destination management and innovations, COVID-19 reper- cussions, and others. We hope these proceedings will serve as a valuable source of information on the state of the art in ICT and tourism research. We greatly appreciate the considerable time and effort put in by all members of the ENTER21@yourplace Scienti fi c Committee who helped us to ensure that the content of the research papers is of high quality. We also would like to thank the panel of experts who helped with additional reviews in order to select candidates for the best paper award. Furthermore, we are thankful to the ENTER21@yourplace conference chair Claudia Br ö zel and the rest of the conference organization team, the IFITT President Zheng Xiang, and the IFITT Board for their support while managing the research track. Finally, we would also like to thank all the authors for their v willingness to disseminate their latest research at ENTER21@yourplace. This conference would not be possible without their efforts. Wolfgang W ö rndl Chulmo Koo Jason Stienmetz vi Preface Organization ENTER21 Scienti fi c Committee Marina Abad University of Deusto, Spain Alisha Ali Shef fi eld Hallam University, UK Aurkene Alzua-Sorzabal Deusto University, Spain Norman Au The Hong Kong Polytechnic University, Hong Kong Rodolfo Baggio Bocconi University, Italy Catalin-Mihai Barbu University of Duisburg-Essen, Germany Matthias Braunhofer Microsoft, Germany Claudia Br ö zel University of Applied Science for Sustainable Development, Germany Dimitrios Buhalis Bournemouth University, UK Jacques Bulchand-Gidumal University of Las Palmas de Gran Canaria, Spain Lorenzo Cantoni USI — Universit à della Svizzera italiana, Switzerland Federica Cena University of Torino, Italy Yeongbae Choe University of Macau, China Namho Chung Kyung Hee University, Korea Ludovik Coba Free University of Bozen-Bolzano, Italy Cihan Cobanoglu University of South Florida, USA Cynthia Corr ê a University of S ã o Paulo, Brasil Giacomo Del Chiappa University of Sassari, Italy Amra Deli ć TU Wien, Austria Linus W. Dietz Technical University of Munich, Germany Anneli Douglas University of Pretoria, South Africa Marine-Roig Estela University of Lleida, Spain Anna Fensel University of Innsbruck, Austria Matthias Fuchs Mid Sweden University, Sweden vii Robert Goecke Munich University of Applied Sciences, Germany Maria Rosario Gonz á lez-Rodr í guez University of Seville, Spain Ulrike Gretzel University of Southern California, USA Vincent Gr è zes University of Applied Sciences Western Switzerland, Switzerland Juyeon Ham Kyung Hee University, Korea Noor Hazarina Hashim Universiti Teknologi Malaysia, Malaysia Jesus Herrero Tecnalia, Spain Sunyoung Hlee Kyung Hee University, Korea Wolfram H ö pken University of Applied Sciences Ravensburg-Weingarten, Germany Athina Ioannou University of Surrey, UK Dietmar Jannach University of Klagenfurt, Austria Jin Young Kim Kyung Hee University, Korea Taekyung Kim Kwangwoon University, Korea Yoo Ri Kim University of Surrey, UK Stefan Klein University of Muenster, Germany Peter Knees Vienna University of Technology, Austria Jan Krasnodebski Expedia, Switzerland Rob Law The Hong Kong Polytechnic University, Hong Kong Pam Lee Kyung Hee University, Korea Seul Ki Lee Sejong University, Korea Daniel Leung The Hong Kong Polytechnic University, Hong Kong Rosanna Leung I-Shou University, Taiwan Maria Lexhagen Mid Sweden University, Sweden Gang Li Deakin University, Australia Andreas Liebrich Hochschule Luzern — Wirtschaft, Switzerland Anyu Liu University of Surrey, UK Bernd Ludwig University of Regensburg, Germany Kimberley Marr Modul University, Austria David Massimo Free University of Bozen-Bolzano, Italy Hisashi Masuda Kyoto University, Japan Christian Maurer IMC University of Applied Sciences Krems, Austria Luiz Mendes-Filho Federal University of Rio Grande do Norte, Brasil Elina Michopoulou University of Derby, UK Valeria Minghetti CISET — Ca ’ Foscari University, Italy Jean-Claude Morand CYBERSTRAT, France Antonio Moreno Universitat Rovira I Virgili, Spain Jamie Murphy University of Eastern Finland, Finland viii Organization Julia Neidhardt Vienna University of Technology, Austria Barbara Neuhofer Salzburg University of Applied Sciences, Austria Lyndon Nixon Modul University Vienna, Austria Elena Not Fondazione Bruno Kessler, Italy Peter O ’ Connor ESSEC Business School, France Sangwon Park The Hong Kong Polytechnic University, Hong Kong Kwangsoo Park North Dakota State University, USA Juho Pesonen University of Eastern Finland, Finland Ilona Pezenka FH Wien der WKW University of Applied Sciences for Management & Communication, Austria Birgit Proell Johannes Kepler University Linz, Austria Mattia Rainoldi Salzburg University of Applied Sciences, Austria Francesco Ricci Free University of Bozen-Bolzano, Italy Jia Rong Victoria University, Australia Laurens Rook Delft University of Technology, Netherlands Roland Schegg HES-SO Valais, Switzerland Mete Sertkan TU Wien, Austria Marianna Sigala University of South Australia, Australia Brigitte Stangl University of Surrey, UK Dandison Ukpabi University of Jyvaskyla, Finland Vania Vigolo University of Verona, Italy Katerina Volchek Deggendorf Institute of Technology, Germany Christian Weismayer Modul University, Austria Kyung-Hyan Yoo William Paterson University, USA Chung-En (Joanne) Yu Salzburg University of Applied Sciences, Austria Markus Zanker Free University of Bozen-Bolzano, Italy Organization ix Contents Part I: Technology Full Papers The Evolution of Chatbots in Tourism: A Systematic Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Davide Calvaresi, Ahmed Ibrahim, Jean-Paul Calbimonte, Roland Schegg, Emmanuel Fragniere, and Michael Schumacher Blockchain Technology ’ s Potential for Sustainable Tourism . . . . . . . . . 17 Inessa Tyan, Mariemma I. Yag ü e, and Antonio Guevara-Plaza In-room Voice-Based AI Digital Assistants Transforming On-Site Hotel Services and Guests ’ Experiences . . . . . . . . . . . . . . . . . . . . . . . . . 30 Dimitrios Buhalis and Iuliia Moldavska Next-POI Recommendations Matching User ’ s Visit Behaviour . . . . . . . 45 David Massimo and Francesco Ricci Assessing Online Sustainability Communication of Italian Cultural Destinations – A Web Content Mining Approach . . . . . . . . . . . . . . . . . 58 Valentina Marchi, Valentina Apicerni, and Alessandra Marasco Technostress Among Hotel Employees - a Longitudinal Study of Social Media as Digital Service Encounters . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 Karin H ö gberg How Arti fi cial Intelligence Will Change the Future of Tourism Industry: The Practice in China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Yanzheng Tuo, Lanyu Ning, and Aiyuan Zhu Co-creating Personalised Experiences in the Context of the Personalisation-Privacy Paradox . . . . . . . . . . . . . . . . . . . . . . . . . 95 Katerina Volchek, Joanne Yu, Barbara Neuhofer, Roman Egger, and Mattia Rainoldi xi A Platform for Dif fi culty Assessment and Recommendation of Hiking Trails . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Jean-Paul Calbimonte, Simon Martin, Davide Calvaresi, and Alexandre Cotting Short Papers A Study on the Factors Affect the Technology Satisfaction on AI Based Self-service Technology Service Failure in Hotel . . . . . . . . . . . . . . . . . . 123 Lu QianTing, Hee Chung Chung, and Namho Chung The Role of Perceived Technology and Consumers ’ Personality Traits for Trust Transfer in Airbnb . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 Cirenzhuoga, Juyeon Ham, and Namho Chung Part II: Innovation Full Papers Finding Meaning Through Travel Journaling: A Strength-Based Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 C. K. Bruce Wan, Cees J. P. M. de Bont, Paul Hekkert, and Kenny K. N. Chow Loyalty Programs and Direct Website Performance: An Empirical Analysis of Global Hotel Brands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 Peter O ’ Connor Effect of Personal Innovativeness on Technology Adoption in Hospitality and Tourism: Meta-analysis . . . . . . . . . . . . . . . . . . . . . . . 162 Olena Ciftci, Katerina Berezina, and Minsoo Kang A Netnographic Study of Consumer Value in Slow Travel . . . . . . . . . . 175 Veera Riikonen, Juho Pesonen, and Johanna Heinonen Gen Z and Esports: Digitizing the Live Event Brand . . . . . . . . . . . . . . . 188 Rebecca de Freitas Short Papers Coworking and Coliving: The Attraction for Digital Nomad Tourists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202 Ekaterina Chevtaeva Mobile Payments, Chinese Tourists, and Host Residents: Are Destination Stakeholders Prepared to Facilitate Mobile Payments? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210 Tania Maria Tangit and Rob Law xii Contents Airbnb Host ’ s Perceptions on Airbnb Customer Social Responsibility and Organizational Justice in Airbnb 2.0 . . . . . . . . . . . . . . . . . . . . . . . . 216 Xiao Rui Tie, Hyunae Lee, and Namho Chung Robo-Tipping: Are Customers Game? . . . . . . . . . . . . . . . . . . . . . . . . . . 222 Lisa Cain and Katerina Berezina Part III: Social Media and User Generated Content Full Papers Tourist Experiences at Overcrowded Attractions: A Text Analytics Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231 Joanne Yu and Roman Egger The Implicit and Explicit Motivations of Tourist Behaviour in Sharing Travel Photographs on Instagram: A Path and Cluster Analysis . . . . . . 244 Jennifer Daxb ö ck, Maria Laura Dulbecco, Sintija Kursite, Tommy Kristoffer Nilsen, Andrada Diana Rus, Joanne Yu, and Roman Egger Dreaming About Travel: A Pinterest Netnography . . . . . . . . . . . . . . . . 256 Ulrike Gretzel Cultural Traits in the Consumption of Luxury Hotel Services . . . . . . . . 269 David D ’ Acunto and Serena Volo Short Papers Exploring the Impact of Heuristic Attributes of Electronic Word of Mouth on Accommodation Sharing Platforms . . . . . . . . . . . . . . . . . . 280 Yuwan Wang, Lin Li, and Sung-Byung Yang How Reliable Is Social Media Data? Validation of TripAdvisor Tourism Visitations Using Independent Data Sources . . . . . . . . . . . . . . 286 Shihan Ma and Andrei Kirilenko Do Tourists from Different Countries Interpret Travel Experience with the Same Feeling? Sentiment Analysis of TripAdvisor Reviews . . . 294 Luyu Wang and Andrei P. Kirilenko The Impact of Crisis Characteristics and Media Coverage on the Public ’ s Attitude Toward Tourism Organization Expressed on Sina Weibo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302 Lijuan Su and Svetlana Stepchenkova HOTFRED: A Flexible Hotel Fake Review Detection System . . . . . . . . 308 Michael M ö hring, Barbara Keller, Rainer Schmidt, Matthias Gutmann, and Scott Dacko Contents xiii Contextual Effects of Online Review Recency: Three Research Propositions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315 Seunghun Shin and Zheng Xiang Information Characteristics on Instagram and Viewer Behavior . . . . . . 322 Eunmi Kim, Jae Eun (Francesca) Park, Jin-Young Kim, and Chulmo Koo Meme Tourism: A Conceptual Framework . . . . . . . . . . . . . . . . . . . . . . 328 Yerin Yhee, Jahyun Goo, and Chulmo Koo Part IV: Destinations Full Papers Approach to Evaluating the Effect of an Inter-organizational Information System on Performance: The Case of a Destination Management Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337 Marie Claire Louillet, Fran ç ois B é dard, and Bertrand Dongmo Temgoua The Digitized Ecosystem of Tourism in Europe: Current Trends and Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352 Norman Schaffer, Martin Engert, Guido Sommer, Jasmin Shokoui, and Helmut Krcmar Measuring the Value of Social Media Marketing from a Destination Marketing Organization Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . 365 Jonna Kumpu, Juho Pesonen, and Johanna Heinonen Destination Imagery Diagnosis Model: The Case of Switzerland . . . . . . 378 Meng-Mei Chen, Laura Zizka, Ef fi e Ruiheng Zhang, and Justine Gentinetta Tourism Management in Japan and Switzerland: Is Japan Leapfrogging Traditional DMO ’ s Models? A Research Agenda . . . . . . . 389 Miriam Scaglione, Yasuo Ohe, and Colin Johnson Touristic Consumption as “ Sitesharing ” : Unpacking the Smart Tourism Paradigm from an Internet Studies Perspective . . . . . . . . . . . . 403 Michelangelo Magasic Short Papers The Pathway from Smartness to Sustainability: Exploring the Transmission Mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 413 Jos é F. Perles-Ribes and Josep A. Ivars-Baidal Discovering Cultural Differences Through Information Flow of National DMOs Websites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419 Hyejin Park and Svetlana Stepchenkova xiv Contents A Conceptual Framework of Destination Sustainability in Sharing Economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 426 Huiying Zhang, Xi Yu Leung, and Billy Bai Smart Tourism Cities ’ Competitiveness Index: A Conceptual Model . . . 433 Namho Chung, Hyunae Lee, Juyeon Ham, and Chulmo Koo Part V: COVID-19 Full Papers Hear No Virus, See No Virus, Speak No Virus: Swiss Hotels ’ Online Communication Regarding Coronavirus . . . . . . . . . . . . . . . . . . . . . . . . 441 Laura Zizka, Meng-Mei Chen, Ef fi e Zhang, and Amandine Favre Virtual Reality as a Travel Substitution Tool During COVID-19 . . . . . . 452 Daniel Sarkady, Larissa Neuburger, and Roman Egger Covid-19 and Instagram: Digital Service Innovation in Top Restaurants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 464 Aarni Tuomi, Iis Tussyadiah, and Mark Ashton The Sustainability of Using Domestic Tourism as a Post-COVID-19 Recovery Strategy in a Distressed Destination . . . . . . . . . . . . . . . . . . . . 476 Erisher Woyo “ Nothing Can Stop Me! ” Perceived Risk and Travel Intention Amid the COVID-19 Pandemic: A Comparative Study of Wuhan and Sapporo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 490 Si Ru Li and Naoya Ito Factors In fl uencing Tourists ’ Intention to Use COVID-19 Contact Tracing App . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 504 Dandison Ukpabi, Sunday Olaleye, and Heikki Karjaluoto Destination Management in Times of Crisis - Potentials of Open Innovation Approach in the Context of COVID-19? . . . . . . . . . . . . . . . 517 Markus Pillmayer, Nicolai Scherle, and Katerina Volchek “ Old ” and “ New ” Media Discourses on Chinese Outbound Tourism to Switzerland Before and During the Covid-19 Outbreak. An Exploratory Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530 Lea Hasenzahl and Lorenzo Cantoni Short Papers A Model to Predict Users ’ Intentions to Adopt Contact-Tracing Apps for Prevention from COVID-19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 543 Imane Ezzaouia and Jacques Bulchand-Gidumal Contents xv A Comparison of Hotel Guest Experience Before and During Pandemic: Evidence from Online Reviews . . . . . . . . . . . . . . . . . . . . . . . 549 Irene Cheng Chu Chan, Jing Ma, Huiyue Ye, and Rob Law How COVID-19 Impacts Chinese Travelers ’ Mobility Decision-Making Processes: A Bayesian Network Model . . . . . . . . . . . . 557 Junyi Wang, Xueting Zhai, and Qiuju Luo Examining Post COVID-19 Tourist Concerns Using Sentiment Analysis and Topic Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 564 Sreejith Balasubramanian, Supriya Kaitheri, Krishnadas Nanath, Sony Sreejith, and Cody Morris Paris Enhancing the Visitor Experience in the Time of COVID 19: The Use of AI Robotics in Pembrokeshire Coastal Pathway . . . . . . . . . 570 Katarzyna Minor, Emmet McLoughlin, and Vicky Richards Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 579 xvi Contents Part I: Technology The Evolution of Chatbots in Tourism: A Systematic Literature Review Davide Calvaresi ( B ) , Ahmed Ibrahim, Jean-Paul Calbimonte, Roland Schegg, Emmanuel Fragniere, and Michael Schumacher Institute of Information Systems, University of Applied Sciences and Arts Western Switzerland (HES-SO), Sierre, Switzerland { Davide.Calvaresi,Ahmed.Ibrahim,Jean-Paul.Calbimonte,Roland.Schegg, Emmanuel.Fragniere,Michael.Schumacher } @hevs.ch Abstract. In the last decade, Information and Communication Tech- nologies have revolutionized the tourism and hospitality sector. One of the latest innovations shaping new dynamics and fostering a remark- able behavioral change in the interaction between the service provider and the tourist is the employment of increasingly sophisticated chat- bots. This work analyzes the most recent systems presented in the lit- erature (since 2016) investigated via 12 research questions. The often appreciated quick evolution of such solutions is the primary outcome. However, such technological and financial fast-pace requires continuous investments, upskilling, and system innovation to tackle the eTourism challenges, which are shifting towards new dimensions. Keywords: Chatbots · Tourism · Virtual assistants · Virtual agents · Hospitality · eTourism 1 Introduction The fast-paced evolution of Information and Communication Technologies (ICTs) has radically transformed the dynamics and business models of the tourism and hospitality industry [32]. This leads to new levels/forms of com- petitiveness among service providers and transforms the customer experience through new services. Creating unique experiences and providing convenient services to customers leads to satisfaction and, eventually, customer loyalty to the service provider or brand (i.e., hotels) [4]. In particular, the most recent tech- nological boost received by the tourism sector is represented by mobile appli- cations [16]. Indeed, empowering tourists with mobile access to services such as hotel reservations, airline ticketing, and recommendations for local attractions generates fervent interest and considerable revenues [8,37]. On the one hand, immediate access, automation, and ease of use have made these applications an irreplaceable part of many tourists’ daily lives. On the other hand, beyond automation-related features, there is a need for personaliza- tion. To do so, several Artificial Intelligence (AI)-based solutions (e.g., chatbots) c © The Author(s) 2021 W. W ̈ orndl et al. (Eds.): Information and Communication Technologies in Tourism 2021 , pp. 3–16, 2021. https://doi.org/10.1007/978-3-030-65785-7 _ 1 4 D. Calvaresi et al. are getting space in the market [2]. A chatbot is a computer program able to entertain a natural language-based conversation with a human. The ancestor of modern chatbots dates back to the 60s when Joseph Weizenbaum developed ELIZA [38]. Its goal was to simulate a psychotherapist with a bounded knowl- edge and several workarounds to avoid dead-ends in the conversation. Although more than 50 years have passed since that revolutionary idea, chatbot technolo- gies (CBTs) have only recently reached sufficient maturity to be widely deployed and used in diverse real-life scenarios. Today, chatbots are intended to be pro- grams understanding one or more human languages by using Natural Language Processing (NLP) or AI Markup Languages leveraging on a knowledge-base con- sisting of a collection of dialogue management rules that use different techniques for processing the user’s input [37]. In the last five years, early prototypes were mainly based on simple state machines, offering simple interactions simulating conversations with humans [2,7]. In the tourism sector, the first interactions delegated to a chatbot were used to support the search for tips and information (e.g., opening hours) of local restaurants [17] and customer-care basic support (i.e., 85% of customer care in tourism are today handled by chatbots/AI-based systems [37]). Besides the main characteristic of CBT (i.e., anytime-anywhere availability) and the main objective (i.e., providing information) chatbots have also been used for data col- lection. In the era of data-driven AI, this capability is priceless, enabling the provision of tailored recommendations and dialogues, which were/are expected to boost the user experience. For example, in the hospitality sector, Mercure, the AccorHotels brand, has chosen Facebook Messenger to host its virtual assistant. Guests can discover anecdotes about the surrounding area and secret addresses thanks to geolocation. Booking.com’s new service and support chatbot is now widely available to English-language bookings, handling 30% of those customer questions automatically in less than five minutes. In the context of the tourism industry, to provide a reconciling view on the most advanced solutions presented in the literature, we aim at analyzing how far have the current solutions and research gone? and what is targeted or envisioned by the tourism sector and the related research? This study aims at fostering the understanding of what stands behind those interactive dialogues between chatbot technologies and customers, beyond the well-known buying tickets online or book hotels support in the tourism industry. To do so, we have conducted a Systematic Literature Review, following a well- defined methodology. The methodology identifies a series of research questions against which existing works are analyzed. The remainder of the paper is organized as follows. Section 2 presents the review methodology employed in this study. Section 3 reports the results and evidence. Section 4 discusses the aggregated and generated knowledge produced by this study. Finally, Sect. 5 concludes the paper. The Evolution of Chatbots in Tourism: A Systematic Literature Review 5 2 Review Methodology This paper adheres to the original procedure for literature review presented in [24] and further adopted and adapted by [5] and [6] (see Fig. 1). This method- ology applied to conduct the Systematic Literature Review (SLR) is meant to be rigorous and reproducible (i.e., replicate the retrieval, selection, and analysis processes). Planning the Review (a) Dissemination (c) free form and structured research questions Develop the review protocol (research strategy) Validate the review protocol Data Analysis Final report composition Summarizing evidence Performing Review (b) Disagreement resolution Article Elaboration [Features collection] Article Selection [Inclusion criteria application] Systematic search Fig. 1. Review methodology adapted from [5]. Following the Goal-Question-Metric (GQM) [25], the generic free-form ques- tion “How is the evolution of chatbots in Tourism characterized?” is broken down into the following structured research questions (SRQs): – SRQ1: Demographics . How time- and geographic- wise are the research efforts distributed? i.e., when (year) and where (the geographical indication of the scientific institute). – SRQ2: Abstraction . What is the abstraction level of the elaborated scien- tific contributions? e.g., at which level the contribution is: conceptual (C), prototype (P), or tested (T). – SRQ2: Application scenarios . Which applications/areas of the tourism domain have employed CBT-solutions? (e.g., hospitality, travel agency, and transportation). – SRQ3: Recipients . Who are the users of CBT-solutions? – SQR4: Desiderata Which are the requirements standing behind the employment of CBT? – SQR5: Goals . Which are the objectives set for CBT-solutions? – SQR6: Services realized . Which CBT functionalities have been realized ? – SQR7: Services envisioned . Which CBT functionalities are desired and envisioned ? 6 D. Calvaresi et al. – SQR8: Technology . Which underlying technologies have been employed to realize the CBTs? – SQR9: Benefits . Which advantages do CBTs provide? (from both user and provider sanding points). – SQR10: Drawbacks . Which limitations have CBTs shown? – SQR11: Open challenges . Which open challenges concern the next genera- tion of CBTs? To increase the accuracy of the semi-automatic research, some keywords have been contextualized (i.e., some contextual words have been associated with queried keywords). In particular, the queries have been realized by combining the two sets listed below: – Contextual keywords: tourism + hospitality + traveling; – Targeted keywords: chatbot + virtual assistant + online assistant + auto- mated assistance + conversational agent. The research of the articles has been conducted using the following sources: IEEExplore, Science Direct, ACM Library, and Google Scholar. Ninety-three relevant papers have been initially collected. Performing a coarse-grained and successively fine-grained examination, the primary studies to be elaborated have been reduced to 27. Such filtering has been performed by briefly parsing the title, abstract, and the core contribution of the paper, which had to comply with the following criteria: a) Recency (post-2016): The aim is to identify the current trends and under- stand recent works addressing CBT in tourism. Given the recent technolog- ical advancement and the tangible contribution of chatbots to the tourism industry, we set 2016 as the starting year of the collection. b) Relevance: The paper must confer relevant information and contribution to the tourism sector (solely scholarly papers without a link to the tourism domain have been excluded). c) Accessibility: To be included, the content of the article should be accessible via one of the portals mentioned above. d) Singularity/Originality: Duplicate papers or papers having an extended follow-up version are not included. Only the complete version is included. 3 Results Presentation SRQ1 and SRQ2: Demographics and Abstraction The paper selection and elaboration have been conducted in late July 2020. That justifies the only 11 papers collected in that year. However, the projection sug- gests the exponential trend, manifesting a significant interest from the scientific community. Figure 2(b) shows the papers distribution per country. The abstraction level of the elaborated studies is quite significant. Indeed, most of them propose prac- tical and tested solutions (16 studies), only five studies present systems at a prototype level, and six solely conceptual contributions.