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The purpose of this study is to analyze state-of-the-art knowledge of artificial intelligence (AI) research in hospitality.

This study adopts the theory-context-methods framework to systematically review 100 AI-related articles recently published (i.e. from 2021 to April 2023) in three top-tier hospitality journals, namely, the International Journal of Contemporary Hospitality Management, International Journal of Hospitality Management and Journal of Hospitality Marketing and Management.

Findings suggest that studies of AI applications in hospitality are mostly theory-driven, whereas most AI methods research adopts a data-driven approach. State-of-the-art AI applications research exhibits the most interest in service robots. In AI methods research, little attention was paid to the amid-service/experience.

This study reveals inadequacies in theory, context and methods in contemporary AI research. More research from hospitality suppliers’ perspectives and research on generative AI applications are advocated in response to the unveiled research gaps and recent AI developments.

This study classifies the most recent AI research in hospitality into two main streams – AI applications research and AI methods research – and discusses the gaps in each research stream and latest AI developments. The paper then suggests future research directions to guide researchers in advancing AI research in hospitality.

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.

This paper aims to explore the matching effect of hospitality brand image (cool vs non-cool) and service agents (Artificial intelligence [AI] vs human staff) on brand attitude, with a focus on assessing the role of feeling right as a mediator and service failure as a moderator.

This paper tested the hypotheses through three experiments and a Supplementary Material experiment, which collectively involved 835 participants.

The results indicated that the adoption of AI by cool brands can foster the right feeling and enhance consumers’ positive brand attitudes. In contrast, employing human staff did not lead to improved brand attitudes toward non-cool brands. Furthermore, the study found that service failure moderated the matching effect between service agents and cool brand images on brand attitude. The matching effect was observed under successful service conditions, but it disappeared when service failure occurred.

The findings offer practical guidance for hospitality companies in choosing service agents based on brand image. Cool brands can swiftly transition to AI, reinforcing their modern, cutting-edge image. Traditional brands may delay AI adoption or integrate it strategically with human staff.

To the best of the authors’ knowledge, this paper represents one of the first studies to address the issue of selecting the optimal service agent based on hospitality brand image. More importantly, it introduces the concept of a cool hospitality brand image as a boundary condition in the framework of AI research, providing novel insights into consumers’ ambivalent responses to AI observed in previous studies.

This paper aims to bridge the extended reality framework and the luxury hospitality literature by providing insights into how immersive technologies using artificial intelligence (AI) can shape luxury value and consumer differentiation.

The authors conducted three experimental studies comparing immersive AI versus traditional hospitality across luxury contexts (hotels, restaurants and spas). Study 1 investigates the effect of immersive AI (vs traditional hospitality) on customers’ behavioral intentions and the need for differentiation using virtual-assisted reality. Study 2 tests the underlying mechanism of the need for differentiation and luxury value in an augmented reality context. Study 3 provides additional support for the proposed underlying mechanism using virtual-assisted reality in luxury hospitality.

The findings reveal that immersive AI (vs traditional) luxury hospitality reduces customers’ behavioral intentions of using such services and perceived luxury value. Moreover, the findings indicate that the intention to use immersive AI (vs traditional) luxury hospitality services is contingent upon customers’ need for differentiation.

The findings have important theoretical and managerial implications for immersive technologies in luxury hospitality. They shed light on the dynamics between integrating immersive AI into luxury hospitality and its impact on customers’ differentiation motives and perceived luxury value. The findings reveal the detrimental effect of using immersive AI (vs traditional hospitality) within this context.

The study investigates the consumer’s attitude to using artificial intelligence (AI) devices in hospitality service settings considering social influence, hedonic motivation, anthropomorphism, effort expectancy, performance expectancy and emotions.

This study employed a quantitative methodology to collect data from Bangladeshi consumers who utilized AI-enabled technologies in the hospitality sector. A total of 343 data were collected using a purposive sampling method. The SmartPLS 4.0 software was used to determine the constructs' internal consistency, reliability and validity. This study also applied the partial least squares structural equation modeling (PLS-SEM) to test the research model and hypotheses.

The finding shows that consumer attitude toward AI is influenced by social influence, hedonic motivation, anthropomorphism, performance and effort expectancy and emotions. Specifically, hedonic motivation, social influence and anthropomorphism affect performance and effort expectations, affecting consumer emotion. Moreover, emotions ultimately influenced the perceptions of hotel customers' willingness to use AI devices.

This study provides a practical understanding of issues when adopting more stringent AI-enabled devices in the hospitality sector. Managers, practitioners and decision-makers will get helpful information discussed in this article.

This study investigates the perceptions of guests' attitudes toward the use of AI devices in hospitality services. This study emphasizes the cultural context of the hospitality industry in Bangladesh, but its findings may be reflected in other areas and regions.

This study aims to use organizational fashion to underscore a novel phenomenon in which products, services and practices fade in and out of the tourism/hospitality setting within a specific time frame. Drawing from the fashion theoretical strands in organization research, this paper studies how fashion has been conceptualized, operationalized and then diffused among tourism/hospitality enterprises.

A qualitative case design was used. A total of 37 semistructured in-depth interviews with executives of innovative tourism/hospitality companies (e.g. restaurants, hotels, theme parks and travel agencies) were conducted. This paper focuses on the organizational fashion phenomenon in which organizational trendsetters with creative, “hot” products/services have emerged prominently in the marketplace.

This inquiry illustrates a social phenomenon concerning the organizational fashion setting process by integrating existing production practices among different organizational suppliers in the hospitality sector. Different cases in the study show that fashion consists of a series of hybrid, paradoxical processes. These include conceptualization (conventionalization vs novelty, and personalization vs conformity), operationalization (bundling vs unbundling, and learning vs relearning) and diffusion (framing vs co-framing, and adaptation vs alteration).

Throughout the three continuous processes, service design and identity development for consumption, as well as value creation and knowledge transformation for production, are carried out according to the decision of what is “hot” and what is “out” at a particular time. In essence, fashion helps to explain why hospitality institutions imitate specific innovations to take advantage of popular trends in the consumer market, as well as how such trends vanish eventually.

This research contributes the insight that organizations use fashion as a managerial initiative to translate their organizational goals and improvise nascent products and services. The fashion processes can be triggered by microlevel individual organizations and are spread through a series of social interactions to become macrolevel phenomena in a recurring manner.

The purpose of this study is to evaluate service robots as an alternative service provider that can reduce customers’ social discomfort in hospitality service encounters. Specifically, the authors discuss when and in what scenarios service robots can alleviate such social discomfort and explain this effect from the perspective of dehumanization.

Following a social constructivist paradigm, the authors adopt a qualitative research design, gathering data through 21 semistructured interviews to explore why the presence of service employees causes customers’ social discomfort in hospitality service encounters and how service robots alleviate such discomfort.

This study’s results suggest that both the active and passive engagement of service employees are sources of customers’ social discomfort in hospitality service encounters; thus, adopting service robots can help reduce such discomfort in some scenarios. Customers’ differentiating behaviors, a downstream effect of social discomfort, are also addressed.

Service robots can reduce customers’ social discomfort in certain scenarios and influence their consumption behaviors. This finding offers actionable insights regarding the adoption of service robots in hospitality service encounters.

This research enhances the understanding of social discomfort in hospitality service encounters and expands the research on service robots. To the best of the authors’ knowledge, it is the first attempt to reveal the bright side of robots in service encounters from a dehumanization perspective.

Drawing from cognitive dissonance theory (CDT) and attribution ambiguity theory (AAT), this paper aims to examine how employees interact with queer customers within the hospitality service and the ways that queer representations regulate emotions when discriminated against by normative gender roles.

This study used a mixed method. Study 1 used firm-level secondary data to analyze hospitality firms’ efforts in diversity, equity and inclusion (DEI) and the effects on firms’ profit margins and customer satisfaction. In Study 2, an experimental design was used to understand how employees’ assailing behavior toward queer customers interacts with employee feelings of guilt and impacts their sabotage and organizational citizenship behavior via self-serving bias. Study 3 further explored how queer customer victimization interacts with stress to influence their perceptions of organization DEI authenticity and corporate social responsibility (CSR) through resilience.

Hospitality firms’ DEI efforts were associated with varying outcomes, including higher profit margins but lower customer satisfaction, while guilt weakened the impact of employees’ assailing behavior on their outcomes and customer stress amplified the effect of assailing behavior on queer customers’ perceptions of DEI authenticity and CSR through resilience.

Hospitality organizations should take proactive measures to address self-serving bias among employees. Moreover, fostering an inclusive culture is crucial, with managers playing a pivotal role in facilitating discussions and creating an environment that values diversity, inclusivity and respect for all employees.

The study makes a remarkable contribution to hospitality literature by focusing on CDT and AAT in providing valuable implications for DEI advocators to be aware of the tensions between heteronormativity and queer representations in service encounters.

This study examines how leaders’ narcissistic rivalry (LNR) affects the in-role performance (IRP) and proactive customer service performance (PCSP) of employees in the hospitality industry. Specifically, this study investigates the mediating role of psychological distress and the moderating role of locus of control (LOC) in the aforementioned relationships.

This study administered a multi-wave, multi-source questionnaire survey with 323 employees working in 11 full-service hotels in China. Statistical analyses were performed using the PROCESS macro in SPSS 26 software and structural equation modeling using Mplus 8.3 software.

The authors' results suggest that LNR can negatively affect hospitality employees’ IRP and PCSP and that these relationships are mediated by psychological distress. Additionally, the impact of LNR on psychological distress can be lessened by internal LOC.

This study contributes to the literature on leader narcissism by investigating how LNR affects IRP and PCSP among hospitality employees. Drawing on conservation of resources theory, this study also identifies a novel mediating mechanism (psychological distress) connecting LNR to hospitality employees’ service outcomes. Furthermore, this study reveals the moderating role of LOC in the relationship between LNR and psychological distress.

The purpose of this paper is to investigate the opportunities of development of the accommodation establishments by accepting the current shifting in travellers' needs and the possibilities of reducing the impact on nature.

The Drucker's approach is used to investigate the opportunities of development for the accommodation establishments. The case study method is used to confirm the possibility to develop hospitality in a discovered way.

Accommodation establishments located in the natural space can supply the nature-based accommodation services simultaneously providing the eco-friendly activities. On the other side, the accommodation establishment that is not located in the natural space can also accept the provision of nature-based accommodation services as an opportunity for development.

The current shift in the guests' needs prompts accommodation establishments to enlarge supplying of the nature-based services. However, if these services are supplied by hospitality facilities located in natural space, the threats to nature also grow. On the other hand, if the hospitality infrastructure is not located in natural space, hoteliers accept current needs of guests as threats to their business. The paper presents the possibility of solution of this contradiction and shows the opportunities for moving forward in the field of environmental sustainability in the hospitality industry.