This study explores how artificial intelligence (AI) transparency can be designed to enhance trust and guest experience in luxury hospitality. Drawing on 50 semi-structured interviews with hotel guests across Europe, Asia, and North America, and segmented using the CEW Technology Comfort Scale, the research develops the Dynamic Transparency Protocol (DTP) framework. Findings reveal that transparency preferences vary across guest profiles and service stages, shaped by three adaptive mechanisms: user-centric adaptation, situational sensitivity, and emotional matching. Guests with lower digital comfort valued human-mediated, simplified disclosures, while digital elites demanded customizable dashboards and traceability. Across segments, emotional resonance emerged as critical for perceived fairness and trust, reframing transparency as both informational and affective. The study contributes by contextualizing transparency and trust frameworks in a luxury service setting and offers actionable guidance for managers on tiered transparency design, emotionally tuned interfaces, and hybrid human–AI mediation.

Service robots have been adopted in many industries, including hospitality. Yet the conditions under which customers see these robotic assistants as social entities remain unclear. This research investigates how different levels of social influence, including a service robot’s communication skills (i.e., congruent co-verbal gestures), the degree of commensality (i.e., social practice of dining together), and customers’ interactive experiences (i.e., interaction with the robot), shape human–robot interaction and subsequent service robot adoption. Three interconnected studies, including two online experiments and one field study at a restaurant, were conducted based on social impact theory. The results suggest that customers require a certain level of social influence to perceive a service robot’s social presence. This type of presence is the primary factor informing service robot adoption at low to moderate levels of social influence. However, as the level of social influence increases, customers begin to rely more on their interactive experiences (e.g., while dining or interacting with the service robot directly) when making adoption decisions. This research offers several meaningful implications. Theoretically, it is one of the first to experimentally assess the effects of social presence, customers’ dining experiences, and interactivity on service robot adoption under varying levels of social influence. Practically, it provides useful insights for managers by contextualizing customers’ real-world behavior in a restaurant setting.

Given the importance of building a meaningful brand relationship with target customers, this research focuses on how LGBTQ+ customers develop brand equity in the context of LGBTQ+ friendly hotels. An online survey was created, and 316 LGBTQ+ participants were recruited through a consumer research firm. The research model was tested using structural equation modeling. The findings suggest that brand ethicality and brand uniqueness influence brand-self identification, which in turn affects brand affect and brand trust, consequently increasing brand equity. Furthermore, brand uniqueness has a stronger influence on brand identity for highly reputable LGBTQ+ friendly hotels compared with those that are merely advertised. However, contrary to our prediction, brand ethicality shows a weaker influence on brand identity for highly reputable LGBTQ+ friendly hotels than those that are merely advertised. This research offers valuable insights for both researchers and practitioners on how to build and enhance brand equity among LGBTQ+ customers.

AI-powered devices, for example, service robots, are expected to revolutionize hospitality. As a result, research on service robots has surged in the context of hospitality. While prior studies have explored customer and employee attitudes toward using or abandoning robots in different contexts, for example, health care, there is a dearth of research into strategic decision-makers’ views on deciding to continue using or abandoning service robots in hospitality settings after their introduction. To that end, we adopt the Technology-Organization-Environment (TOE) framework through a phenomenon-driven bottom-up approach to explore why strategic decision-makers plan to (dis)continue using service robots in hospitality after their introduction. In practice, semistructured interviews were conducted with robot suppliers ( n = 8) and strategic decision-makers ( n = 10) to explore the planned (dis)continuance of service robot usage. Six key factors related to planned (dis)continuance of service robots in hospitality settings were found, revolving around drivers and barriers of robot adoption (e.g., availability of off-the-shelf robot solutions; operational complexity), the strategic focus of the company (e.g., vision and mission), the user experience (e.g., robots’ persona), technical aspects (e.g., sensors and interoperability), and economic aspects (e.g., managing cashflow). Extending the Technology-Organization-Environment framework, we derive implications for hospitality management theory and practice by developing a novel model for planned (dis)continuance of service robot usage, thus adding to the broader body of work on robot usage continuance in operational settings.

Using a unique switchback field experiment, we investigate the impact of hotel participation in Google Hotel Finder (GHF) and its advertising on consumer purchase behavior, total demand, and booking channel share, and probe the implications for revenue management. A group of 26 hotels was randomly assigned to three treatments, each representing different levels of participation in GHF, with the treatments alternating each week. This design provides causal effect estimates of GHF participation on click behavior and conversion likelihood. We also examine how it influences consumers’ channel choice (direct vs. third-party) and develop revenue-maximizing advertising strategies. Our research makes several key contributions. First, we find that paid advertising in GHF significantly cannibalizes organic (free) bookings. Second, we extend the analysis beyond click-through rates to conversion rates, and explore their impact on bookings, channel mix, and revenue management. Our revenue analysis shows that GHF’s participation generates higher revenue for hotels by increasing demand and shifting bookings to lower-cost channels. Although paid ads introduce additional costs, they still drive sufficient incremental revenue when capacity allows. Specifically, paid ads are optimal for firms with low exposure (lower impressions), but beyond a certain point, additional paid clicks do not result in revenue gains due to capacity constraints. Our findings suggest that paid advertising in GHF can effectively optimize revenue when strategically targeted based on likely search volume and hotel availability.

This paper focuses on the relationship between hotel age and performance, challenging the prevailing theory that hotel performance uniformly declines with age. Using the most extensive dataset available, encompassing over 3,000 U.S. hotels over six recent years, we employ a mixed-methods approach to assess whether a U-shaped performance trend exists. Our analysis reveals a nuanced pattern wherein hotel performance declines during the initial years of operation but improves beyond a critical turning point at approximately 40 years old, particularly for hotels located in large metropolitan areas, and also based on hotel brand-affiliation status and class. The findings suggest that certain older hotels defy conventional depreciation models, experiencing a resurgence in performance. These insights have implications for hospitality researchers, as well as for practitioners, suggesting re-evaluating older hotels’ strategies and informing investment and taxation decisions.

This study investigates how managers’ and targeted Asian employees’ responses to customer-perpetrated racial discrimination affect the observing customers’ perceptions and behavioral intention. Using two experimental designs, Study 1 examines the effect of managers’ responses (i.e., avoidance, employee support, and customer support), and Study 2 tests targeted employees’ responses (avoidance, confrontation, and venting) to racial discrimination on observing customer’s revisit intention. In addition, this study examines the moderating role of the severity of racial discrimination. Across two studies, this research provides evidence that observing customers tend to rate managers as fair when they support the targeted employees. Also, observing customers rate the targeted employees as competent when they professionally confront the customers which led to a higher level of revisit intention. This study expands the hospitality literature by focusing on racial discrimination against Asian American and offers practical guidance on how managers and employees should respond to racial discrimination.

Sexual harassment in the workplace remains one of the most significant issues affecting the hospitality sector today. In particular, scholars need to better understand why some employees choose to remain employed by a company despite experiencing such harassment. Drawing from appraisal theory and social exchange theory, the goal of this study is to investigate the mediating effects of negative emotions (i.e., shame and anger) on the relationship between sexual harassment and turnover intention, and the moderating effect of pay satisfaction on the relationship between such negative emotions and turnover intention. Data were collected from 500 full-time restaurant employees in the United States. Using structural equation modeling (SEM), all direct effects were supported, except for the impact of shame on turnover intention. Moreover, anger mediated the relationship between sexual harassment and turnover intention, and pay satisfaction moderated the relationship between anger and turnover intention. Practical and theoretical implications are discussed in detail.

This article examines the effect of user review ratings and sentiment in review comments on restaurant profitability. In addition, the effects of sentiment in review comments in a local versus a foreign language are compared. User sentiments are mined from 63,904 Dutch and 42,980 English TripAdvisor review comments for restaurants in Flanders (the Dutch-speaking region of Belgium). The article exploits the availability of detailed firm-level financial reports, which are mandatory for all Belgian companies. This facilitates the investigation of bottom-line profitability, which is the ultimate measure of success, and at the same time, the inclusion of firm-specific control variables in the regression analyses. Findings suggest positive sentiment toward restaurants in general and that variations in sentiment impact profitability. Sentiment in review comments is highly significant and has a larger impact than review ratings. In addition, comments in the local language (Dutch) are more impactful than comments in a global language (English). Overall results suggest that, rather than focusing solely on quantitative ratings, restaurateurs should focus on users’ qualitative review comments, actively managing them to help drive restaurant performance. To the authors’ knowledge, this is the first study to empirically assess how review ratings, sentiment in review comments, and language of review comments impact bottom-line restaurant performance, adding to the literature supporting proactive online reputation management.