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The technological and digital revolution has introduced important changes in the tourism industry. However, capturing the extent of the new tourism 4.0 paradigm is still difficult. This study aims to assess the dimensions related to the concepts of industry 4.0 in tourism and hospitality, tourism innovation and tourism ecosystem when considered simultaneously, and their role in promoting a new wave of competitiveness in the tourism industry.

A bibliometric study was conducted based on tourism 4.0, hotel 4.0, tourism innovation and tourism ecosystem using 120 eligible articles published between 2008 and 2021 from the Web of Science database.

This study demonstrated the advances in industry 4.0 in tourism and hospitality publications over 13 years and identified five interconnected dimensions: (1) knowledge transfer in tourism; (2) networking tourism innovation; (3) sources of tourism innovation; (4) smart tourism ecosystem and (5) innovation research in tourism. It was also concluded that tourism development should be a regional competence based on strategic networking and externalisation of regional knowledge flows.

This bibliometric review provides important implications and recommendations for several players of industry 4.0 in tourism and hospitality and policymakers. Not only did it make it possible to create a state of art, but also to categorise the existing interconnections between the dimensions of Tourism 4.0, Hotel 4.0, Tourism innovation and Tourism ecosystem to optimise its implementation and generate greater value. In addition, practical implications were inferred that improve the tourism sector’s competitiveness, helping strategic decision-making at the level of policymakers and actors in this sector.

Apart from state of the art, this bibliometric review made it possible to categorise the existing interconnections between the dimensions of tourism 4.0, hotel 4.0, tourism innovation and tourism ecosystem to optimise its implementation and generate greater value. Practical implications were inferred that improve the tourism sector’s competitiveness, helping strategic decision-making at the level of policymakers and several players in this sector.

This study addresses the existing literature gap in the interconnection of industry 4.0 with tourism and hospitality by describing the most relevant conceptual interconnections and setting practical implications for improving the competitiveness of the tourism industry. Furthermore, it integrates previous studies and outlines future lines of investigation.

This bibliometric study provides an overview of research related to digital transformation (DT) in the tourism industry from 2013 to 2022. The goals of the research are as follows: (1) to identify the development of academic papers related to DT in the tourism industry, (2) to analyze dominant research topics and the development of research interest and research impact over time and (3) to analyze the change in research topics during the pandemic.

In this study, the authors processed 3,683 papers retrieved from the Web of Science and Scopus. The authors performed different types of bibliometric analyses to identify the development of papers related to DT in the tourism industry. To reveal latent topics, the authors implemented topic modeling based on latent Dirichlet allocation with Gibbs sampling.

The authors identified eight topics related to DT in the tourism industry: City and urban planning, Social media, Data analytics, Sustainable and economic development, Technology-based experience and interaction, Cultural heritage, Digital destination marketing and Smart tourism management. The authors also identified seven topics related to DT in the tourism industry during the Covid-19 pandemic; the largest ones are smart analytics, marketing strategies and sustainability.

To identify research topics and their development over time, the authors applied a novel methodological approach – a smart literature review. This machine learning approach is able to analyze a huge amount of documents. At the same time, it can also identify topics that would remain unrevealed by a standard bibliometric analysis.

Artificial intelligence is one of the most significant and active fields of study in the last few years. Artificial intelligence-derived robotic technologies known as chatbots are gaining interest from both academic and industry sectors. By analyzing the development and patterns of research on the chatbot phenomena within the tourism field, this study seeks to develop a theoretical framework for the interaction between chatbots and tourism.

The Web of Science (WoS) database’s 33 articles on chatbots related to travel and hospitality were examined between 2019 and 2024 using VOSviewer software for bibliometric and thematic content analysis.

Research on chatbots for tourism and hospitality appears to be in its early stages. The factors influencing tourists' intentions to use chatbots have been thoroughly researched; the attitudes, perceptions and behavioral intentions of destinations, travel agencies and restaurant patrons regarding chatbots were examined, and it was found that the quantitative research approach was dominant. In addition, the majority of the studies are based on a particular theory or model.

This is one of the first attempts to directly comprehend and depict the interconnected structures of studies on the interaction between chatbots and tourism through the use of network analysis. Furthermore, the study’s findings can offer academics a comprehensive viewpoint and a reference manual for more accurate assessment and oversight of the chatbot-tourism interaction. Regarding the lack of research on the topic and the fragmented structure of the studies that exist, it is imperative to provide both a comprehensive overview and a roadmap for future investigations into the usage of chatbots in the travel and hospitality sector.

This study aims to appraise the historical evolution of tourism research focused on Spain. Firstly, an analysis was conducted to assess the production and impact of research within this domain. Secondly, scientific mapping, specifically through co-word analysis, was used to identify and explore the principal research themes and their evolution in the field.

A historical approach was adopted in this study, using 1,100 bibliographic records obtained from the Scopus database. Science mapping was then conducted through co-word analysis of bibliographic data.

The results of the performance analysis provide insights into the volume, evolution and impact of the scientific documents published within the research area under investigation. Moreover, by adopting a longitudinal approach, science mapping through co-word analysis enables the definition of the intellectual structure within this research domain. In this regard, the main research themes are identified, conceptually assessed, and their evolution is examined across three distinct window periods: an initial research period (1972–2002), a growing research period (2003–2012) and a consolidation period (2013–2022).

The study provides a state-of-the-art position on tourism research related to Spain thus guiding future studies in the area. Furthermore, this study provides a comprehensive “snapshot” of the historical progression of tourism research in Spain, capturing the emblematic aspects that have emerged within the area over the investigated time period.

The purpose of this paper is to test the effect that anthropomorphic framing (i.e. robot vs automatic machine) has on consumers’ responses in case of service failure. Specifically, the authors hypothesize that consumers hold an unconscious association between the word “robot” and agency and that the higher agency attributed to self-service machines framed as robots (vs automatic machines) leads, in turn, to a more positive service evaluation in case of service failure.

The authors have conducted four experimental studies to test the framework presented in this paper. In Studies 1a and 1b, the authors used an Implicit Association Test to test for the unconscious association held by consumers about robots as being intelligent machines (i.e. agency). In Studies 2 and 3, the authors tested the effect that framing technology as robots (vs automatic machines) has on consumers’ responses to service failure using two online experiments across different consumption contexts (hotel, restaurant) and using different dependent variables (service evaluation, satisfaction and word-of-mouth).

The authors show that consumers evaluate more positively a service failure involving a self-service technology framed as a robot rather than one framed as an automatic machine. They provide evidence that this effect is driven by higher perceptions of agency and that the association between technology and agency held by consumers is an unconscious one.

This paper investigates a novel driver of consumers’ perception of agency of technology, namely, how the technology is framed. Moreover, this study sheds light on consumers’ responses to technology’s service failure.

This study aims to offer an overview of hospitality and tourism research on artificial intelligence (AI) and its impact on the industry. More specifically, this study examines hospitality and tourism AI research trends in hospitality and tourism customer service experience creation and delivery, service failure and recovery, human resources and organizational behavior. Based on the review, this study identifies the challenges and opportunities and provides directions for future studies.

A narrative synthesis approach was used to review the hospitality and tourism research on AI and its impact on various aspects of the industry.

AI and AI applications in customer service experience creation and delivery and its possible effects on employees and organizations are viewed as a double-edged sword. Although the use of AI and AI applications offers various benefits, there are also serious concerns over the ethical use of AI, the replacement of human employees by AI-powered devices, discomfort among customers and employees and trust toward AI.

The paper offers an updated holistic overview of AI and its implications in different facets of the hospitality and tourism industry. Challenges and opportunities are discussed to foster future discussions on the use of AI among scholars and industry professionals.