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The purpose of this paper is to identify and map competencies required by frontline employees to enhance guest experience in the hospitality industry, in the context of an emerging experience economy.

Secondary research through extensive review of relevant literature in the area of experience economy and hospitality management.

This study proposes a new construct of “Hospitality Intelligence” (HI) encompassing mainly Emotional Intelligence (comprising Interpersonal Intelligence and Intrapersonal Intelligence), Cultural Intelligence and Hospitality Experiential Intelligence dimensions.

Practitioners and HR professionals in the field of hospitality would find the Hospitality Intelligence construct useful in recruiting and training frontline employees, while educationists could use the findings of this study in designing curricula and pedagogical interventions for developing the right skill set for the hospitality industry.

This study proposes a competencies framework and develops a construct of Hospitality Intelligence required by frontline employees in the hospitality industry to elevate guest experience from a simple interaction to a memorable experience.

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 concept of “regenerative business” is thriving in current business literature. The present study seeks to contribute to the current academic debate by investigating the nature and scope of regenerative hospitality, here seen as a steppingstone of regenerative tourism.

Exploratory in nature and with the goal of understating the nature and scope of regenerative hospitality, nineteen semi-structured interviews with academics, consultants and self-proclaimed regenerative hoteliers were conducted.

Results provide a regenerative hospitality framework to move from the current sustainability paradigm towards local and systemic regenerative approaches in hospitality by applying place and people intelligence.

This research contributes to the current academic debate about the future of travel, particularly focussing on the future of hospitality in relation to the multidisciplinary field of regenerative economy. Particularly, the paper has been designed to contribute to the current discussion in the Journal of Tourism Futures about the transformation and regenerative future of tourism.

This study aims to identify, review and synthesize existing literature on key theories, drivers and barriers affecting consumer adoption or resistance to artificial intelligence (AI) in the hospitality sector.

This study aims to conduct a complete literature review of the accrued knowledge generated so far on AI in the hospitality sector. To attain the overall objectives of this study, we used the systematic literature review (SLR) method. This method systematically handles the diversity of knowledge in a specific topic to answer precise research questions. It also generates new visions through a synthesis of the literature, to identify the knowledge gaps, set the new directions for the future researcher and provide sufficient guidance to inform the policy and practice.

The findings of this study are presented in three sections, as follows: descriptive analysis, content analysis and synthesized framework. The findings highlighted the state-of-the-art mapping of the existing research in terms of publication frequency over time and across publication outlets, key theories, methods and geographies. In addition, literature on consumer adoption (or resistance) of AI in hospitality is content analyzed to highlight key drivers and barriers. Moreover, this review critically evaluates extant literature and sets future agendas by postulating specific research questions for further knowledge development in this field of study.

The SLR focused on consumer adoption or resistance to use AI in hospitality literature. The future researcher may include additional streams to get better results.

The study findings will help multiple stakeholders to understand the underlying causes of customer resistance or barriers to the intention to use/adopt AI services in the hotel sector. Furthermore, study results will allow them to better analyze the relationship between customer barriers, intents or consumer decision behaviors.

First, this study provides a comprehensive synthesis of the literature on the consumer adoption or resistance of AI in hospitality. This study categorizes the existing diversified literature in two main themes – drivers and barriers – to present a simplistic picture of the existing literature. Second, the review highlights the gaps and limitations in existing research and provides guidance for future scholars. Third, the key contribution of this review is the development of a unified framework on the consumer adoption or resistance of AI in the hospitality sector. That is, this study puts forward the behavioral reasoning theory framework and suggests that future research using this lens will immensely contribute to existing literature. Finally, this study facilitates the practitioners to understand the key motivating and hindering factors affecting the adoption and resistance behavior.

This paper aims to explore how artificial intelligence (AI) technologies have redefined the hospitality industry. It develops a theoretical framework to evaluate its impact on employee engagement, retention and productivity levels, stemming from its potential implications for service quality and customer satisfaction.

Based on the exploration of relevant literature, role theory and service-profit chain were used to develop – role-service-profit chain.

Role-service-profit chain is an analytical tool which has strong implications for investment and deployment analysis of the new technologies in hospitality and tourism businesses. It proposes how managers can evaluate how the role expectation of technological innovations relate to service quality and customer satisfaction through its impact on employee-related outcomes (such as employee engagement, retention and productivity), and assess the corresponding impact on profitability and growth, in the context of their own unique internal environment and position in the market.

Although an empirical assessment of the hypothesised relationships in the model is required to evaluate and validate it in the hospitality industry, role-service-profit chain presents promising implications for tourism and hospitality practice and future research.

Role-service-profit chain is an analytical tool from which managers can make improvements on talent and talent management practices and adjust expectations and behaviours in ways that facilitate improvements in service quality and customer satisfaction.

This paper makes an important contribution to hospitality and tourism literature, as it explores how AI technologies implemented to improve on talent and talent management practices impact on service quality and customer satisfaction, and develops analytical tools by which this may be evaluated.

The purpose of this study is to examine the effects of hospitality employees’ emotional intelligence (EI) on their stress-coping styles and job satisfaction.

The sample consisted of 366 food and beverage employees in the Korean hospitality industry. The validity and reliability of the respondents’ replies regarding EI, stress-coping styles and job satisfaction were tested through exploratory factor analysis, reliability analysis and confirmatory factor analysis. Once the measure was validated, a structural equation model was used to test the validity of the proposed model and hypotheses.

The results showed that the elements of EI (i.e. self-emotion appraisal [SEA], use of emotion [UOE], regulation of emotion [ROE] and others’ emotion appraisal [OEA]) had a significant, positive effect on the cognitive-appraisal coping style, whereas only SEA and UOE had a significant, positive effect on the problem-solving coping style. Meanwhile, SEA had a significant, negative effect on the emotion-focused coping style. In addition, employees’ problem-solving and cognitive-appraisal stress-coping styles showed a significant, positive effect on their job satisfaction. Employees’ UOE and ROE demonstrated a significant, positive effect on job satisfaction.

The generalizability and, therefore, implications are limited to the Korean hotels and family restaurants. Future research needs to closely examine models and variables which may become the causes of individual traits, relationship traits and leadership.

Strategies to cope with stress and job satisfaction used by family restaurant employees showed more sensitive effects of control than hotel employees did in the organic causal relationships between EI and strategies to cope with stress/job satisfaction. The results of this study, which indicate that hospitality companies can increase employees’ job satisfaction by enhancing their employees’ EI, suggest detailed and practical alternatives to human resource management, as employees with higher degrees of EI can bring positive outcomes to both organizations and employees. Hospitality employees’ EI is significant in terms of organizational performance.

Building on recent smart hospitality systematic reviews and extensive literature analyses, this paper aims to explore recent developments, themes and issues within smart hospitality. It synthesises existing knowledge, extrapolating forward and contributes to the future development of smart hospitality by serving as a reference to enrich academic/industry discussions and stimulate future research.

The research examined 8 recent review articles on smart hospitality and tourism and extracted 145 articles in peer-reviewed sources from Web of Science focussed on smart hospitality. These publications supported in-depth analysis to explore the body of knowledge and develop foresight for the future of smart hospitality within business ecosystems at tourism destinations. It synthesises knowledge and provides the basis for the development of a comprehensive in-depth research agenda in smart hospitality innovations as well as the formulation of agile hospitality ecosystems.

This paper illustrates that smart hospitality introduces disruptive innovations that affect the entire hospitality ecosystem. Smart hospitality takes advantage of smart cities and smart tourism towards establishing agile business ecosystems in networked destinations. Having reviewed the existing literature, the study developed a conceptual framework and introduced a comprehensive future research agenda. This includes the drivers of smart hospitality, namely, customer-centricity, personalisation, individualisation and contextualisation; marketing-driven hospitality excellence and metaverse; as well as operation agility, asset strategy, talent management and supplier interoperation. It also identified the foundations that provide the infostructure for smart hospitality, including ambient intelligence, big data, processes and sustainability, providing the capability blocks to co-create value for all stakeholders in the hospitality ecosystem.

This study conceptualises smart hospitality as a disruptive and innovative power that will affect the competitiveness of hospitality and tourism organisations as part of a comprehensive ecosystem. It identifies the key stakeholders and explores how they can take advantage of emerging developments. This paper proposes the drivers and foundation for future research on smart hospitality. The research provides a conceptual synthesis of the literature and the concepts that have been elaborated. The foundations are effectively the infostructure that enables the drivers to add value to different stakeholders. Key issues are identified to stimulate further research on the area to support smart hospitality development and adoption.

Voice assistants (VAs) empower human–computer interactions by recognising human speech and implementing commands pronounced by users. This paper aims to investigate VA-enabled interactions between hotels and guests in the hospitality context. The research positions VAs within the artificial intelligence (AI)-enabled Internet of Things (IoT) context, disrupting old practices and processes. Smart hospitality uses VAs to support effortless value cocreation for guests cost-effectively. The research examines consumer perceptions and expectations of hospitality VAs and explores VA capabilities through expert technology providers.

This empirical paper investigates the current use and future implications of VAs for hotel environments. It uses qualitative, semi-structured in-depth interviews with 7 expert hospitality VA technology providers and 21 hotel guests who have VA experience. The research adopts a demand and supply approach, addressing the VAs in hospitality holistically.

The findings illustrate the requirements from both end-users’ sides, hotels and guests, exploring VA advantages and challenges. The analysis demonstrates that VAs increasingly become digital assistants. VA technology helps hotels to improve customer service, expand operational capability and reduce costs. Although in its infancy, VA technology has made progress towards optimising hotel operations and upgrading customer service. The study proposes a speech-enabled interactions model.

This research stimulates the transformation of hospitality services by using VAs and the development of smart hospitality and tourism ecosystems. The study can benefit from further research with hotel managers, to reflect hoteliers’ points of view and investigate their perception of VAs. Further research can also explore different aspects of consumer–VA interaction in different contexts.

The paper makes a significant contribution to hospitality management and human–computer interaction best practices. It supports technology providers to reconsider how to develop suitable technology solutions towards improving their strategic competitiveness. It also explains how to use VAs cost-effectively and profitably while adding value to travellers’ experience.

VA studies are often focussed on the technology in private households, rather than in commercial or hotel spaces. This paper contributes to the emerging literature on AI and IoT in smart hospitality and explores the acceptance and operationalisation of VAs. The research contributes to the conceptualisation of VA-enabled hotel services and explores positive and negative features, as well as future prospects.

语音（数码, 虚拟或者人工智能）(VAs) 助理能够识别真人声音和系统指令声音从而为人机互动提供助力。 本研究基于酒店业已有的案例探索了酒店和客人语言支持的互动的本质。本研究探索了关于客房服务的表现和实用性的顾客认知和顾客期望。

本研究借用了定性半结构化深入访谈来收集一手数据, 调查了酒店环境中的语音助理目前的运用情况和未来影响。本研究访谈了7位酒店科技服务提供者和21位有使用个人智能扬声器经验的酒店客人。本研究以供需模型来全方位解决此项问题。

研究结论强调了从双方使用者（酒店和客人）角度考量, 并且考虑到语音仪器带来的所有的优势和挑战的重要性。基于顾客之前对这些仪器的使用经验, 本论文深入阐述了对公共空间这些语音助理的使用功能。本分析证明了由AI技术支持下, VAs 可以灵活的识别语音。VAs理解词汇内容并且也懂得词汇作为数据助手来支持智能家庭的自动化以及履行商业职责背后的意义来。酒店从业人员可以尝试运用此科技来提高用户体验, 扩展运营空间和减少成本。从访谈的数据可以证明, 尽管还在初级阶段, VAs 科技已经对酒店运营优化和晋级客户服务做出了显著的贡献和成就。本研究提出了一项介于酒店和客人之间的VA 语言支持的互动模型。

之前的研究主要针对私人使用, 而不是商业或者酒店空间。考虑到敌对环境和客人和酒店的文化差异, 旅游和酒店成为了尤其有挑战性的领域。本研究通过语音识别革新了酒店服务。本研究针对VAs接受程度和运用进行详细研究从而为酒店领域的AI和IoT提供了专业文献。本文为酒店服务中的VAs使用做出了开拓性的调查并且探讨了正面以及负面的特征和未来展望。

本研究为酒店和旅游管理补充了文献, 尤其是在酒店业人机互动领域。本研究通过语音识别技术对酒店服务的转型革新做出贡献。此项研究可以受益于以酒店管理者为视角的进一步研究。相比于收集科技设备供应方的见解, 对酒店管理者进行访谈可以提供更直接的信息来了解酒店员工对数码语音助理和对语音科技的总体接受程度。

酒店经常寻求途径来提高和客户的互动。本论文对酒店管理和人机互动领域提供了应用典例。本研究提供了酒店客人针对语音设备功能性的总体评价作为有价值的信息, 进而帮助科技提供者来重新审视针对顾客需要从而量身定制服务的策略和方式。最终, 本研究在提高行业战略竞争力层面分享了关于发展和采用此项强大有力科技的见解。

Grounded on the X Reality framework and human–machine collaboration, this study aims to explore the potential of immersive augmentation through artificial intelligence (AI) service robots for promoting social inclusion in the hospitality industry.

Three experimental studies across diverse hospitality contexts examine the effects of immersive augmentation using inclusive-AI service robots compared to standard-AI robots. The studies also uncover the underlying process of perceived ethicality and the moderating role of customers’ familiarity with AI.

The results indicate that immersive augmentation through inclusive-AI service robots generates higher levels of supportive tipping behavior (Studies 1 and 3), superior buying intentions (Study 2) and an increased likelihood for customers to pay a premium price (Study 2). These effects are mediated by perceived ethicality (Studies 1–3). However, the impact of immersive augmentation for social inclusion is contingent upon customers’ familiarity with AI: customers with high familiarity with AI exhibit lower levels of supportive tipping behavior (Study 3).

The findings emphasize the importance of perceived ethicality and customers’ familiarity with AI in determining the effectiveness of immersive augmentation for social inclusion in hospitality.

This study contributes to the literature by exploring the potential of immersive augmentation using AI service robots for social inclusion in hospitality. It offers novel insights by highlighting the importance of perceived ethicality and customers’ familiarity with AI. The findings provide valuable guidance for hospitality managers seeking to leverage AI technology to foster social inclusion.

Amidst ongoing digital transformation, the current paper provides a 360-degree overview of technology-adoption in Tourism and Hospitality. By combining and consolidating a wide range of sources, mainly in the tourism literature, the analysis depicts how the complex technological ecosystem often enhances or hinders the successful adoption, integration and interoperability of different technologies.

The critical review method was used to assess, analyse and synthesise existing literature in the area of digitisation in tourism and hospitality. The critical review process included a thematic analysis of the literature, where recurring themes, patterns and trends were identified towards addressing the study’s research questions.

The analysis identifies current trends, opportunities, challenges and strategies for technology adoption in tourism and hospitality, the implications for theory, practicable executive directions and avenues for further research.

The paper’s main contribution lies in its comprehensive identification, consideration and incorporation of all primary contemporary technological elements, and the ensuing development of a corresponding conceptual charting framework, which illustrates a multifaceted process with practical implications for various stakeholders, including businesses, authorities, consumers and employees.