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This study aims to analyze the importance and performance of customer-facing technologies in luxury hotels. The study also assessed differences between and within the four generations in the importance-performance analysis (IPA).

Data were collected using a Qualtrics panel of recent luxury hotel customers in the USA belonging to all four generations. The cross-generational IPA was conducted using t-tests and (ANAOVA).

The IPA matrix concentrated most technology items in either low importance – low performance or high importance – high performance quadrants. One-way ANOVA revealed significant differences between generations on the importance ratings of all technology items except wireless charging power solutions and on the performance ratings of all technology items. Furthermore, post hoc tests indicated that millennials rated luxury technology most favorably among the four cohorts, followed by generations Z, X and Baby Boomers. In addition, significant differences between the importance and performance of many technology items within each generational cohort were observed. Overall, Wi-Fi was unanimously ranked across generations as the most important technology among luxury guests, but it was the only one that scored lower in performance than importance.

The findings of this study contribute to hospitality scholarship in two primary ways: the importance and performance of technology and generational differences. The results advance the understanding of the impact of generational factors on customer-facing technological adoptions in the luxury hotel sector.

Technologies that are pervasive in the home also become vital offerings for hotels. The more pervasive technology, the more a luxury hotel must work to ensure that it performs at optimal levels. Additionally, which technologies are most important to targeted generations are provided so practitioners may budget for their implementation.

This research is a pivotal step forward in unraveling the intricate interplay between generational factors and technological evaluations, providing a foundation for future research and practical applications in a rapidly evolving technological landscape in the hospitality industry.

This study aimed to explore the adaptations and perspectives of hotel managers regarding green and smart hotel technologies within the context of sustainability.

A comprehensive literature review guided the formulation of this study, followed by face-to-face, semi-structured interviews with hotel managers. A total of 17 prepared questions were finalized after examination by two expert academicians. The responses were analyzed using qualitative research methodology and the results were weighted using the step-wise weight assessment ratio analysis (SWARA) method.

Interviews with sustainability and operational managers yielded insights into environmentally friendly practices and strategies such as reducing energy and water consumption, waste and chemical reduction, supporting local entrepreneurs and adopting smart technologies. These factors are crucial in eco-friendly hotels. According to the SWARA analysis, 'reducing energy consumption' is the most effective criterion.

This study offers insights into green and smart hotel management by focusing on the perspectives of hotel managers with a small sample. In future studies, research with larger samples on customer perspectives and the effect of hotel selection is recommended.

This study offers insights to hotel managers on energy conservation and customer satisfaction enhancement through green and technological applications. These technological applications can improve hotel service quality and provide personalized experiences, fostering customer loyalty.

This pioneering study focuses on the intersection of green and smart practices in hospitality. By intertwining the often separately discussed concepts of “green” and “smart,” this study presents a novel approach to the sustainability practices in the hospitality industry, holding a key position, especially in Turkey. Implementing these concepts can yield environmental and economic benefits, offering invaluable insights to hotel managers and policymakers into integrating smart technologies with sustainability.

This research investigates the role of customer involvement (CINV) in customer relationship management (CRM) dimensions and customer retention (CR) in Ghana’s hotel industry.

This quantitative-based explanatory research obtained primary data via structured questionnaires from 277 hotel customers in Ghana, processed it with SmartPLS4.0 software, and analysed it with structural equation modelling.

CRM dimensions (CRM-based technology, managing knowledge and personalisation of services) and CINV positively affect CR. Also, CINV partially mediates the interactions between the CRM dimensions and CR in Ghana’s hotel industry.

The study is geographically limited to hotels in Ghana and conceptually limited to three CRM dimensions, CINV and CR. Methodologically, the study was limited to the quantitative approach. However, our outcomes imply that hotels in Ghana that invest in relevant CRM dimensions would improve CR. CRM-CR association can also be improved through CINV.

The study outcomes imply that when Ghanaian hotels implement the CRM dimensions and foster active CINV, their customers’ retention will improve significantly. Hence, CRM and CINV are prerequisites for enhancing CR in Ghana’s hotel industry.

The study offers valuable contributions to the current literature on CRM, consumer behaviour and hospitality management, especially in a developing economy context. Its novel contribution, the mediating role of CINV, would advance CRM studies in the hospitality sector.

The purpose of this study is to explore how past and future temporal focus of CEOs in the hospitality industry influence their intention to invest in metaverse technology and the underlying mechanism under boundary conditions of perceived competitive pressure.

This multi-informant study collected data over three waves from a sample of 235 CEOs and their subordinates in India’s hospitality industry. A PLS-SEM was applied to the study data. Further, the study also used phenomenological interviews to capture CEOs’ perspectives on the study’s conceptual model.

Findings suggest that the past temporal focus of CEOs decreases technology orientation, and future temporal focus increases the technology orientation of firms, consequently impacting the intention to invest in the metaverse. CEOs’ perceived competitive pressure moderates the mediating relationship, such that the negative impact of past temporal focus on technology orientation is decreased and that of future temporal focus on the CEO is increased.

By exploring the role of a CEO’s past and future temporal focus on influencing technology orientation and, hence, adoption of new technology, the study extends upper-echelon theory to the field of metaverse adoption in the hospitality industry and responds to scholars’ calls to explore the industry’s technology adoption from the lens of the upper echelon.

The study has significant implications for the success of the adoption of metaverse technology in the hospitality industry. Findings imply that the board members should encourage CEOs to have future temporal focus.

The study provides novel insights into the adoption of metaverse technology by the hospitality industry, where CEO attributes such as their temporal focus influence intention to invest in metaverse.

In the tourism sector, fully unmanned and partially unmanned hotel models serving customer segments from different income groups are increasing. Analyzing examples of unmanned hotels worldwide and their practices is crucial for understanding the automation systems used, the smart technologies employed, and the opportunities and challenges these hotels present, as well as for gaining insights into their impacts on the tourism sector.

The data used in this research were obtained from secondary sources. One of the qualitative research methods, document analysis, was used for the analysis of these sources. The content analysis technique was used in the analysis of the data. A seven-stage systematic review process was used in the research. This seven-stage review process consists of the following stages: (1) determining the review objectives and formulating research questions; (2) identifying search terms and selection criteria; (3) conducting a search for unmanned hotel applications before clarifying exclusion and inclusion criteria; (4) evaluating the quality and relevance of unmanned hotel applications; (5) identifying content analysis review variables; (6) conducting content analysis; and (7) analyzing and reporting the findings.

In traditional hotel management, the innovations brought by digitalization and automation are transforming the guest experience and increasing operational efficiency. Unmanned smart hotels are equipped with various technological solutions, such as voice-controlled AI assistants, smart room control systems, AI-based concierge services, and robotic room service. These hotels are redefining roles and expectations within traditional hotel management, while simultaneously reducing costs and enhancing efficiency. Analyses indicate that unmanned smart hotels particularly appeal to specific customer segments, such as business travelers, and are becoming increasingly popular. These hotels offer advantages such as allowing guests to perform self-check-in, control their rooms, and receive necessary services via robots.

The universe of the research consists of all currently operating unmanned hotels worldwide. As a result of the research, 18 examples of unmanned smart hotels were identified. Hotels within the same chain with identical applications and processes were considered as a single example. Therefore, the research sample consists of 18 hotels.

By integrating these technological advancements, the hospitality and tourism industries can mitigate the impact of staff shortages, maintain high service standards, and improve operational efficiency. This approach allows businesses to adapt to changing workforce dynamics while continuing to deliver exceptional guest experiences. In conclusion, the significance and impact of unmanned smart hotels in the travel industry are growing. These hotels have the potential to shape the role of technology in the hospitality sector and influence future trends. Therefore, the adoption and development of unmanned smart hotels are important considerations for hotel operators and industry experts.

This paper addresses a crucial research need by examining the influence of compatibility, a pivotal design element for hotel concierge apps, on the socio-psychological dynamics of digital hotel guests. While prior research has examined the constructs, their application to digital concierge apps introduces a unique context. We posit that compatibility significantly influences central variables rooted in theory of planned behaviors (TPBs) and technology acceptance model (TAM), fostering positive usage intentions.

Analyzing data from 668 four-star hotel guests through PLS-SEM substantiates compatibility’s role, endorsing the theoretical amalgamation of affordance, TPB, and TAM frameworks.

Compatibility positively affected perceived ease of use, perceived usefulness, and attitude toward behavior. Besides, usage intention positively affected willingness to pay a price premium and revisit intention.

This paper adopts compatibility as a unifying force for integrating TPB and TAM; the predictive ability of digital concierges' usage intentions on revisit intentions to upscale hotels. Further, this paper is the first attempt to highlight employing compatibility as a pivotal design factor for digital concierge apps in the hospitality setting.

Drawing on the Service Robot Acceptance Model (sRAM) proposed by Wirtz et al. (2018), this study aims to examine how functional and social-emotional antecedents affect relational elements and the critical functions that trust and rapport play in robot acceptance in hotel services. Additionally, this study incorporates customer characteristics into the modified sRAM.

Consistent partial least squares (PLSc) was used to test the proposed model utilizing data collected from 456 Chinese customers.

The results indicated that effort expectancy and performance expectancy positively affect hotel guests’ trust toward and rapport with service robots. However, the effect of social influence on trust and rapport is insignificant. Additionally, perceived humanness and perceived social interactivity positively influence rapport, and perceived social presence positively affects both trust and rapport. Furthermore, trust and rapport positively influence hotel guests’ acceptance of service robots. The results also revealed the moderating role of age.

This study contributes to service robot literature by providing insights into how functional and social-emotional factors affect relational factors and the key role of relational factors in robot acceptance based on the sRAM. This study also advances this body of knowledge by highlighting the moderating effect of age.

基于Wirtz等人（2018）提出的服务机器人接受模型（sRAM）, 本研究旨在探讨功能性和社会-情感性前因如何影响关系元素, 以及信任和融洽在酒店服务中对机器人接受度的关键作用。此外, 本研究将顾客特征纳入修改后的 sRAM 中。

采用一致性偏最小二乘法（PLSc）对来自456名中国顾客的数据进行分析，以验证所提出的模型。

结果表明, 努力期望和绩效期望积极影响酒店客人对服务机器人的信任和融洽。然而, 社会影响对信任和融洽的影响不显著。此外, 感知人性化和感知社会互动积极影响融洽, 感知社会临场感积极影响信任和融洽。此外, 信任和融洽积极影响酒店客人对服务机器人的接受度。结果还揭示了年龄的调节作用。

本研究通过提供关于功能性和社会-情感性因素如何影响关系因素以及关系因素在机器人接受度中的关键作用的见解, 为服务机器人文献做出了贡献。本研究还通过强调年龄的调节效应, 推进了这一知识体系的发展。

Along with the development of the robotics industry, service robots have been gradually used in the hospitality industry. Nevertheless, service robot categorization and the fulfillment of the cognitive and emotional needs of consumers by hotel service robots have yet to be fully explored. Hence, the purpose of this study are to categorize hotel service robots, to explore consumers’ robot hotel experience, to identify the consumers’ preference of hotel service robot in general, to reveal consumers’ preference for hotel service robots based on their fulfillment of emotional needs and to examine the completion of cognitive–analytical and emotional–social tasks.

Through in-depth interviews with technology managers and questionnaire survey among consumers who have and have not had robot hotel stay experience to achieve the aforementioned research objectives.

Findings of in-depth interviews show that service robots can be categorized as check-in/out robots, artificial intelligence (AI) robots and service delivery robots. Results of questionnaire survey indicate that consumers prefer non-humanoid robots (n = 213, p = 47.87%) among check-in/out robots, the Xiaodu Smart Display (n = 163, p = 36. 63%) among the AI robots and the machine-shaped robot porter (I) (n = 178, p = 40.00%) among the service delivery robots.

This study provides implications, such as the adoption of robot-shaped AI with a screen display, to hotel managers to meet the needs of consumers regarding the completion of cognitive–analytical and emotional–social tasks of robots.

This study extends uncanny valley theory by identifying preference for the shape and functions of different categories of service robots and contributes to the limited literature on hotel robots.

This study aims to examine the variables that may influence the acceptance and adoption of robot-assisted services by various stakeholders in the tourist industry, namely in hotels.

This study utilized a qualitative research approach to investigate what may influence the acceptance and adoption of artificial intelligence (AI)-driven technologies in hotels in North Cyprus. Participants were selected for the study based on certain criteria using a referral sampling method.

The author have identified five core themes. (1) “Insufficient awareness;” (2) “Inadequate knowledge to operate robot-assisted services;” (3) “Limited budget;” (4) “Adherence to traditional management approaches” and (5) “Absence of incentives from tourism authorities.” This study establishes the foundation for future research and strategic initiatives aimed at enhancing the readiness of the hotel industry in North Cyprus to integrate robot-assisted services.

This research has practical consequences for hotel management employees in North Cyprus. The results may serve as guides for hotel stakeholders to enhance their understanding of the importance of innovation and establishing a competitive advantage in the rapidly growing hospitality business by identifying the pros and cons of adopting AI-driven technology.

To the best of the authors' knowledge, there have been few studies examining the viewpoints of managerial employees in North Cyprus hotels on the implementation of robot-assisted services. The authors examined several managerial employees in hotels to determine factors that might affect the adoption of AI-driven technology. The results are valuable for future research in the context of hotels in North Cyprus.

The proliferation of Smart Technologies, Artificial Intelligence, Robotics, and Algorithms (STARA) in the tourism and hospitality (T&H) industry has been shown to trigger negative employee behaviour associated with awareness of these technologies. This study expands the existing literature on technology and organisational behaviour from the perspective of hospitality employees based on a dual appraisal of STARA awareness.

The sample included 324 Turkish hotel employees, and the analysis was conducted through partial least squares structural equation modelling (PLS-SEM).

Results revealed the negative impact of STARA awareness on job outcomes among hotel employees. STARA awareness negatively affected the psychological relationship between individuals and organisations. Despite these findings, when perceived as a companion that could support employees' career development, STARA technologies increased employees’ work engagement.

Organisational support plays a critical role in decreasing employees’ fear of technological unemployment. Hotel managers can increase employees' commitment to the organisation by helping them feel valued and supported. However, the support they give to employees will not always work. While more optimistic employees are warmer toward the organisation, depressed employees may not recognise the value the organisation gives them. Hence, managers should strive to offer personalised assistance that addresses the distinct requirements and worries of individual employees.

The research provides a two-sided assessment, extending the one-sided negative perceptions of employees towards STARA technologies. The research is grounded in the Transactional Stress Theory and provides significant implications for the Job Demands-Resources Theory, Person-Organisation Fit Theory, and Self-Determination Theory.