Given that artificial intelligence (AI) is significantly transforming businesses, it is crucial to examine how AI will change the future of the hospitality and tourism industry. By integrating multiple data sources (i.e., practitioner literature, research literature, and expert opinions), we suggest three trends constituting opportunities and challenges (AI applications in different business sectors, primary AI functions, emerging AI topics), three possible themes of change (adoption and acceptance, operations management, AI in marketing), as well as four directions for future research (AI interaction, AI and organizational decision making, organizational implications, and managerial issues). Our findings present a detailed picture of AI development and applications along with predictions regarding its place in the industry. Finally, we outline a research agenda that addresses key issues for stakeholders in hospitality and tourism: individuals, including customers and employees; organizations and businesses; and public policymakers and governments.

ChatGPT is expected to have significant implications for trip planning from a traveler’s perspective. ChatGPT has the potential to be a revolutionary search tool, enabling travelers to bypass an often complicated and disturbing process with a simple conversation with ChatGPT. This research aimed to explain the impact of ChatGPT on travelers’ trip planning behavior; specifically, it examined how travelers perceive ChatGPT when they narrow down multiple travel options. Based on the choice overload effect, we conducted five experimental studies to determine the negative effect of reducing options from the initial recommendations using ChatGPT. The results showed the importance of a hybrid decision-making process involving both humans and ChatGPT. Using our empirical results, we provide significant theoretical and practical implications for travelers’ trip planning behavior incorporating ChatGPT.

This paper revisits the publication “Smart Tourism: Foundations and Developments” published in Electronic Markets in 2015, which presented a data-centric definition of smart tourism and a foundational model of smart tourism layers and components. Recognizing the dramatic evolution of smart technologies over the past decade, the extensive digital transformation of tourism accelerated by the global COVID-19 pandemic, the Artificial Intelligence revolution fueled by large language models, and the continuing efforts to advance the Metaverse, the paper is a 10-year retrospective and incorporates recent developments in Artificial Intelligence and Metaverse technologies, resulting in an updated “AI-powered smart tourism 2.0” model. The new framework bridges past insights with future possibilities and reflects on emerging smart tourism experiences, smart tourism industry practices, and governance approaches. It thus offers an updated vision for smart tourism to guide future research, policymaking, and industry innovation in an era of extremely rapid and profound technological changes.

An online review is composed of various information components (e.g., reviewer profile, review rating, and text), which may have impacts on its user simultaneously. However, while there is a growing interest in understanding the information value of online reviews, the potential interaction effects between different review components have rarely been examined. This study aims to explore the interaction effects on individual perception between review rating and review text in the online hotel review context. We conducted an analytical exercise using actual hotel reviews collected from three major review websites to understand the interaction effects that took place in real, potentially complex settings. Findings showed that review rating and review text interact with each other, and individual perception of hotel reviews varies with the interactions. Finally, we discuss the implications for the holistic perception of online reviews and interactive roles of review components as well as limitations and future research directions.