AI Hospitality Alliance

Academic articles and research signals

The Research Hub curates academic work on AI in hospitality for industry practitioners, operators, and technology leaders. It is designed to help bridge academia and day-to-day business decisions by translating published research into a more usable knowledge base for hotels and hospitality organizations. The collection spans operations, revenue strategy, guest experience, distribution, robotics, and other emerging applications of AI across the sector.

For Professors

Submit an article for consideration

If you have published publicly available research relevant to AI in hospitality, you can submit it for review and possible inclusion in the Alliance Research Hub.

Submit research
Academic ResearchJune 10, 2026International Journal of Hospitality Management

Exploring the impact of human-computer interaction on service robot adoption intention in the service industry

Author links open overlay panel Jingbo Yuan a , Sayed Kifayat Shah b c , Yongquan Wu a , Kayhan Tajeddini d e f , Thilini Chathurika Gamage g , Yongzhong Jiang b c , Wenjing Wang h

This study examines how different human-computer interaction (HCI) styles affect guest adoption of service robots in hospitality settings, depending on the level of guest contact and task complexity. It finds that a master-servant interaction style works best for low-contact, complex tasks by building cognitive trust, while a partner-style interaction fosters emotional trust and adoption in high-contact or simpler tasks. Hotels can use these insights to tailor robot roles and interactions to improve guest acceptance and operational efficiency.

service robotshuman-computer interactionhospitality technologyguest experiencetrust buildingrobot adoptionservice operations
View detailsOpen source
Academic ResearchJune 6, 2026Information Technology & Tourism (Springer)

When Robots Speak: Exploring Conversational Styles, Robot Persona Realism, and Engagement in Hospitality and Tourism Services

Shafaqat Mehmood, Zhimin Zhou, Ifra Noor, Salman Khan

Across one field study and three online experiments in restaurants, hotels, railways, and airports, the authors show that emotional conversational styles in AI service robots drive higher purchase intentions than rational styles, with engagement as the mediating mechanism. Robot persona realism moderates the effect: emotional styles work best with highly humanlike robots, while rational styles outperform with less anthropomorphic ones — a style-persona congruence rule for designing conversational AI in hospitality.

Artificial IntelligenceService RobotsHospitalityTourismGuest ExperiencePersonalizationHospitality Technology
View detailsOpen source
Academic ResearchJune 1, 2026Journal of Hospitality and Tourism Management (ScienceDirect)

Cooperative Interaction: A Taxonomy of Human-GenAI Interaction Patterns in Tourism

Yuexin Zhao, Yingjie Gao, Yahui Wang, Hongyu Zhang, Bowen Zheng

Grounded in cooperation theory, this qualitative study analyzes multi-turn user-GenAI conversations in tourism and derives a taxonomy of four interaction patterns: convergence-guidance, convergence-non-guidance, divergence-guidance, and divergence-non-guidance. The authors identify the challenges each pattern poses for travel decision-making and propose an optimization framework for designing more adaptive, context-aware tourism-specific GenAI.

Generative AITourismGuest ExperienceHospitality TechnologyPersonalization
View detailsOpen source
Academic ResearchMay 31, 2026HOSPITERA: Journal of Hospitality and Tourism Research, Vol. 1 No. 1

The Effect of AI Chatbot Perceived Usefulness and Service Convenience on Customer Loyalty with Mediating Role of Customer Experience in Travel Agency Services

Elkunny Dovir Siratan, Joyce Stefanie Liu

Survey of 200 online travel agency users in Jakarta who interacted with AI chatbots in the past six months, analyzed via PLS-SEM. Perceived usefulness and service convenience both drive customer loyalty in OTA chatbot interactions, with customer experience as a partial mediator that converts functional benefit into emotional commitment. The functional value of a chatbot alone does not create loyalty — it must first translate into a positive, personalized, accessible experience.

Artificial IntelligenceTourismHospitalityGuest ExperienceHospitality TechnologyPersonalizationTechnology Adoption
View detailsOpen source
Academic ResearchMay 7, 2026International Journal of Quality & Reliability Management

Artificial intelligence and service performance: empirical findings from the hospitality sector

Subhodeep Mukherjee , Rashmi Ranjan Panigrahi , Shad Ahmad Khan , Kiran Cotha

This study identifies key factors driving AI adoption in luxury hotels, showing that ease of use, competitive pressure, IT infrastructure, and government support boost AI use and improve service performance. It offers a strategic framework for hotel managers and policymakers to leverage AI for better service, efficiency, and competitive advantage amid rapid digital transformation.

Artificial IntelligenceHospitalityService PerformanceTechnology AdoptionLuxury HotelsDigital TransformationHotel ManagementPolicyOperations
View detailsOpen source
Academic ResearchMay 1, 2026International Journal of Hospitality Management

Designing smart menus: A multi-method exploration of AI integration in hospitality guest experience and operations

Jiahui Wang , Irem Onder , Yifeng Liang , Muzaffer Uysal

This study shows that AI-optimized menus can effectively encourage guests to choose more sustainable and healthy food options without reducing satisfaction. For hospitality operators, especially casual dining venues with broad menus, AI can help design menus that nudge guests toward better choices through clear navigation and visual cues. Single-themed AI menus (either sustainable or healthy) are more effective than mixed themes. Emotional engagement enhances sustainable choices, suggesting that combining menu design with atmosphere can boost impact.

AIMenu DesignSustainabilityHealthy EatingGuest ExperienceHospitality OperationsCasual DiningService Design
View detailsOpen source
Academic ResearchApril 2, 2026arXiv preprint (arXiv:2604.22776)

Epicure: Multidimensional Flavor Structure in Food Ingredient Embeddings — LLM-Augmented Data Curation Reveals Culturally and Perceptually Grounded Dimensions in Food Embeddings

Jakub Radzikowski, Josef Chen

This paper demonstrates that AI-generated food embeddings encode far more culinary knowledge than previously understood — capturing not just taste, but texture, cultural identity, and chemical composition. By using LLMs to clean and consolidate a large ingredient dataset, the researchers recovered fifteen distinct flavor dimensions from vector representations alone, with cultural clustering achieving a 6.2× lift over baseline. For hospitality, the implication is that AI can now support meaningful, culturally grounded food personalization at scale — from menu engineering in hotel restaurants to dietary preference matching across guest profiles.

Guest ExperienceGenerative AIOperationsPersonalization
View detailsOpen source
Academic ResearchApril 2, 2026International Journal of Research and Scientific Innovation (IJRSI)

Smart Hospitality Operations: A Systematic Review of Digital Transformation, Intelligent Systems and Operational Excellence in Contemporary Hospitality

Lynda Dede Graham, Boris Kotey Sasraku-Neequaye

This paper gives hotel operators a practical structure for thinking about smart transformation. Rather than treating AI, IoT, robotics, analytics, and automation as separate projects, it shows how they work together to improve operational efficiency, service consistency, personalization, and sustainability. The most useful takeaway is that smart hospitality is not just about adding technology to existing workflows. It is about redesigning operations so connected systems, better data, and stronger staff readiness all reinforce one another. For managers, the paper points to a phased approach: invest in infrastructure, build employee capability, strengthen governance, and tie each technology decision to measurable business outcomes.

Revenue ManagementOperationsGuest ExperienceRobotics
View detailsOpen source
Academic ResearchApril 1, 2026Frontiers in Robotics and AI

Digital transformation in restaurants: key aspects of service robot deployment from project initiation to evaluation

Anniken Susanne T. Karlsen, Bjørn Andersen, Solvår Elverum Heirsaunet, Elin Indergård, Kristina Nevstad, Wenche Aarseth

One of the clearest lessons from this study is that robot deployment is an architecture decision before it is a technology decision. Restaurants that tried to retrofit robots into existing layouts spent significantly more and got worse results than those that designed the physical environment with robot movement in mind from the start. Beyond the layout question, the research finds that robots consistently reduce physical strain on floor staff, open the door to more inclusive hiring, and generate genuine customer enthusiasm — but only when staff are properly retrained and the team's mindset about what the robot is for has been actively managed.

RoboticsOperationsGuest Experience
View detailsOpen source
Academic ResearchApril 1, 2026International Journal of Hospitality Management

Is human-RAISA collaboration the future of hospitality service? Examining Gen Z's preferences and industry insights from China and Australia

Mengni Fu, Barry Fraser, Charles Arcodia

Both hotel operators and Gen Z guests in China and Australia converge on the same answer: neither full automation nor purely human service is the goal — a collaborative model where robots, AI, and staff each do what they do best is what the next generation of travelers actually wants. The catch is that supply and demand are not yet aligned. Chinese hotels have moved further and faster on RAISA adoption, while Australian hotels remain more anchored to mobile technology. Gen Z preferences, particularly in China, are ahead of what most hotels currently offer, meaning there is a real competitive opportunity for properties willing to close the gap.

RoboticsGuest ExperienceTourismOperations
View detailsOpen source
Academic ResearchMarch 2, 2026Frontiers

Robots, ledgers, and RevPAR: a blockchain-enabled AI–robotics conceptual model for sustainable hotel revenue and asset management

Leonard A. Jackson

This article proposes a conceptual model integrating AI, robotics, and blockchain technologies to enhance hotel revenue management, sustainability, and asset management. It highlights how these technologies can jointly improve financial performance (e.g., RevPAR), operational efficiency, environmental impact, and long-term asset value, while addressing challenges related to governance, ethics, privacy, and organizational readiness.

AIRoboticsBlockchainHotel Revenue ManagementSustainabilityAsset ManagementHospitality TechnologyRevenue StrategyHotel Operations
View detailsOpen source
Academic ResearchFebruary 23, 2026International Journal of Interactive Mobile Technologies (iJIM), Vol. 20 No. 7

AI-Powered Mobile Applications in Hotels: Guest Personalization, Operational Efficiency, and Sustainability

Amila Ishanthi H. M., Neetu Jain, Manpreet Kaur

Qualitative systematic literature review of how AI-powered mobile apps reshape luxury hotels across three outcomes: guest personalization, operational efficiency, and sustainability. Finds that AI-mobile capabilities (pre-arrival personalization, mobile check-in, digital keys, smart-room controls, chatbots, loyalty integration) deliver standardized service, faster response times, lower staffing pressure, and 20–30% energy savings via AI thermostats — but only when paired with employee training, change management, transparent data practices, and a hybrid model that keeps humans on high-touch moments.

Artificial IntelligenceHospitalityHotel OperationsGuest ExperiencePersonalizationOperationsSustainabilityHospitality TechnologyTechnology Adoption
View detailsOpen source
Academic ResearchFebruary 19, 2026Tourism and Hospitality (MDPI), Vol. 7, No. 2, Article 54

AI-Driven Sentiment Analysis: A Unified Framework for Strategic Insights in Tourism

Nikolaos Gkaripis, Georgios Trichopoulos, George Caridakis

This paper presents a dual-model AI framework that combines BERT's supervised classification with Gemini's generative reasoning to extract fine-grained, aspect-level insights from visitor reviews. Rather than returning simple positive/negative scores, the system identifies the specific elements driving dissatisfaction — service, accessibility, cultural experience — and generates actionable recommendations. Validated on TripAdvisor reviews of a UNESCO heritage site, the framework surfaces the kind of nuanced, operational intelligence that traditional review analytics routinely miss. For hotels and tourism operators, it offers a practical path from raw guest feedback to strategic improvement priorities.

Reviews & SentimentGuest ExperienceGenerative AITourism
View detailsOpen source
Academic ResearchFebruary 12, 2026International Journal of Contemporary Hospitality Management

Reviving legends through holographic AI event experiences: Consumer acceptance and value insights

Seden Dogan, AJ Aluri, Muhittin Cavusoglu

This study explores how consumers perceive holographic AI concerts, focusing on factors like ethicality, nostalgia, and uniqueness. It finds that ethical concerns and nostalgic feelings strongly influence emotional and social values, which in turn affect attendance intentions and willingness to pay. The research highlights the importance of transparent ethical practices and nostalgia-driven marketing to enhance engagement and revenue in hospitality events using holographic AI technology.

holographic AIeventsconsumer behaviorethicalitynostalgiahospitality marketingrevenue management
View detailsOpen source
Academic ResearchJanuary 16, 2026Emerald Insight: Tourism Review

Generative AI in hospitality and tourism: a dual-stakeholder perspective on tourist and workforce experience dynamics

Maria Leonor Ferreira

This paper looks at how AI improves short-term rental management using Solarento as an example. AI helps optimize pricing, forecast demand, reduce costs, and improve occupancy and guest experience. However, challenges include reliance on good data, limited transparency, and ethical concerns. The study recommends combining AI with human oversight to ensure balanced, responsible, and effective use in hospitality operations.

Guest ExperienceReviews & SentimentGenerative AITourism
View detailsOpen source
Academic ResearchJanuary 1, 2026F1000Research

Mapping Research Trends in AI-Based Tourism and Hospitality Marketing: A Bibliometric and Thematic Review

Pankaj Kumar Tyagi, Priyanka Aggarwal, Priyanka Tyagi, Asokan Vasudevan, Premendra Kumar Singh

This study systematically reviews 320 peer-reviewed articles from 2003 to 2025 on artificial intelligence (AI) applications in tourism and hospitality marketing. Using bibliometric and thematic analyses, it identifies key publication trends, influential journals and authors, and emerging research themes. The findings reveal a significant growth in AI-related tourism marketing research since 2017, highlighting four main thematic clusters: digital influence and tourist behavior analytics; AI-enabled smart tourism and commerce ecosystems; technology-driven hospitality and experience innovation; and data-driven decision making in predictive tourism modeling. The review underscores AI's transformative role in enhancing personalized marketing, customer engagement, and operational decision-making in the hospitality sector, while also noting challenges related to ethics, data privacy, and maintaining human touch in service.

Artificial IntelligenceTourismHospitalityMarketingBibliometric AnalysisThematic AnalysisCustomer ExperienceData-Driven Decision MakingSmart TourismPersonalization
View detailsOpen source

Research Archive

Browse previous years

2025202420232022