review · Tourism and Hospitality Research
Generative artificial intelligence is increasingly investigated for tourism and hospitality applications, particularly to enhance user experience and operational efficiency. A review of academic literature between 2019 and 2023 highlights key themes such as automated chatbots, sentiment analysis, deep learning, and managerial decision-making. Research output is predominantly concentrated in the United States, China, India, and Saudi Arabia, frequently drawing upon established frameworks such as human-computer interaction, the Technology Acceptance Model, and the Stimulus-Organism-Response model. While the technology offers clear potential for service operations, significant gaps persist regarding ethical considerations, technical performance limits, research scope, and effective collaboration between human workers and artificial intelligence systems. Addressing these challenges is essential for guiding the responsible integration of generative models into service environments and operational workflows.
Generative artificial intelligence has substantial potential to transform tourism by automating customer service and streamlining business operations. Understanding where the technology stands helps hospitality businesses and policymakers address vital questions around system ethics, reliability, and workforce interaction, ensuring that new digital tools deliver reliable benefits without compromising service standards or human oversight.
The findings point to direct commercial uses in customer-facing chatbots, sentiment analysis, and operational decision support tools for hospitality businesses and travel operators. Because this review synthesises early academic literature spanning 2019 to 2023, practical implementations remain largely in early to mid-stage development, requiring further resolution of technical performance, ethics, and human-machine collaboration before achieving mature, enterprise-wide integration.
AI-generated from the published abstract. Always read the original work before citing.
This study used bibliometric analysis and a systematic literature review (SLR) to examine how the tourism and hospitality industries use generative artificial intelligence (GAI), identifying developed patterns, theoretical frameworks, strengths and limitations, and future research challenges. We conducted a systematic review using the Scopus database, adhering to PRISMA principles. We analyzed a sample of 25 articles published between 2019 and 2023 through narrative synthesis and bibliometric analysis using the VOSviewer software, a tool for visualizing network analysis. The USA, China, India, and Saudi Arabia are the major countries engaged in GAI research in tourism and hospitality. Significant research topics emphasize decision-making, chatbots, deep learning, and sentiment analysis, mainly through the Technology Acceptance Model (TAM), Stimulus-Organism-Response (S-O-R), and Human-Computer Interaction (HCI) frameworks. GAI applications demonstrate strength in improving user experience and operational efficiency, though gaps exist in scope, ethics, technology performance, and collaboration between humans and AI. This study, therefore, provides a fundamental foundation for understanding the current status of GAI research in tourism and hospitality by pointing out some trends and areas that require further investigation to ensure the responsible and effective integration of AI within the industry.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1177/14673584241293125
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
