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Drawing on person–environment fit theory, this study aims to investigate how the relationships between service task types (i.e. utilitarian and hedonic service tasks) and perceived authenticity (i.e. service and brand authenticity) differ under different conditions of service providers (human employee vs service robot). This study further examines whether customers’ stereotypes toward service robots (competence vs warmth) moderate the relationship between service types and perceived authenticity.

Using a 2 × 2 between-subjects experimental design, Study 1 examines a casual restaurant, whereas Study 2 assesses a theme park restaurant. Analysis of covariance and PROCESS are used to analyze the data.

Both studies reveal that human service providers in hedonic services positively affect service and brand authenticity more than robotic employees. Additionally, the robot competence stereotype moderates the relationship between hedonic services, service and brand authenticity, whereas the robot warmth stereotype moderates the relationship between hedonic services and brand authenticity in Study 2.

Restaurant managers need to understand which functions and types of service outlets are best suited for service robots in different service contexts. Robot–environment fit should be considered when developers design and managers select robots for their restaurants.

This study blazes a new theoretical trail of service robot research to systematically propose customer experiences with different service types by drawing upon person–environment fit theory and examining the moderating role of customers’ stereotypes toward service robots.

The purpose of this paper is to propose a new service framework for managing nature and physical resources that balances the needs of people and planet.

The process used in this paper was a rapid literature review and content analysis of 202 articles in service journals and learned that there are limited papers on Sustainable Development Goal (SDG) #6 (clean water and sanitation) or SDG #7 (affordable and clean energy) and very few articles on SDG #12 (responsible production and consumption) that focused on environmental components of services. This highlighted the need to conceptualise a service framework for managing these resources sustainably.

The proposed regenerative service economy framework for managing natural and physical resources for all humans (without harming the planet) reflects insights from analysing the available service articles. The framework draws on the circular economy, an Indigenous wholistic framework and service thinking to conceptualise how service research can manage natural and physical resources in ways that serve both people and the planet.

This paper introduces the regenerative service economy framework to the service literature as an approach for guiding service researchers and managers in sustainably managing natural and physical resources in a sustainable way.

This paper aims to provide researchers and practitioners with a consumer-focused alternative for considering the integration of artificial intelligence (AI) into services.

The paper reviews and critiques the most popular frameworks for addressing AI in service. It offers an alternative approach, one grounded in social psychology and leveraging influential concepts from management and human–computer interaction.

The frameworks that dominate discourse on this topic (e.g. Huang and Rust, 2018) are fixated on assessing technology-determined feasibility rather than consumer-granted permissibility (CGP). Proposed is an alternative framework consisting of three barriers to CGP (experiential, motivational and definitional) and three responses (communicate, motivate and recreate).

The implication of this research is that consistent with most modern marketing thought, researchers and practitioners should approach service design from the perspective of customer experience, and that the exercise of classifying service occupation tasks in terms of questionably conceived AI intelligences should be avoided.

Indicative of originality, this paper offers an approach to considering AI in services that is nearly the polar opposite of that widely advocated by e.g., Huang et al., (2019); Huang and Rust (2018, 2021a, 2021b, 2022b). Indicative of value is that their highly cited paradigm is optimized for predicting the rate at which AI will take over service tasks/occupations, a niche topic compared to the mainstream challenge of integrating AI into service offerings.

This article overviews some key contributions to service research from the organizational behavior/human resource management (OB/HRM) discipline with its strong focus on the role of employees. This focus complements the Marketing discipline’s heavy emphasis on customers, largely true of service research, overall.

Ten OB/HRM frameworks/perspectives are applied to analyzing the roles of people (with a focus on employees and modest consideration of customers as “partial” employees who co-create value) in a service organization context. Also, commentary is offered on how the frameworks relate to six key themes in contemporary service research and/or practice. The article concludes with five reflections on the role and status of employees in service research—past, present and future.

Employee roles in evolving service contexts; participation role readiness of both employees and customers; role stress in participating customers; an employee “empowered state of mind”; an emphasis on internal service quality; “strong” HRM systems link individual HRM practices to firm performance; service-profit chain with links to well-being of employees and customers; a sociotechnical system theory lens on organizational frontlines (OF); service climate as an exemplar of interdisciplinary research; emotional labor in both employees and customers; the Human Experience (HX); specification of employee experience (EX).

Service remains very much about people who still guide organizational design, develop service strategy, place new service technologies and even still serve customers. Also, a people and organization-based competitive advantage is tough to copy, thus possessing sustainability, unlike with imitable technology.

Humanity and all life depend on the natural environment of Planet Earth, and that environment is in acute crisis across land, sea and air. One of a set of commentaries on how service can address the UN’s sustainable development goals (SDGs), the authors focus on environmental goals SDG 13 (climate action), SDG 14 (life below water) and SDG 15 (life on land). This paper aims to propose a conceptual framework that incorporates the natural environment into transformative services.

The authors trace the evolution of service thinking about the natural environment, from a stewardship perspective of the environment as a set of resources to be managed, through an acknowledgement of nonhuman organisms as actors that can participate in service exchange, towards an emergent concept of ecosystems as integrating human social actors and other biological actors who engage fully in value co-creation.

The authors derive a framework integrating human and other life forms as co-creating actors, drawing on shared natural resources to achieve mutualism, where each actor can have a net benefit from the relationship. Future research questions are posited that may help services research address SDGs 13–15.

The framework integrates ideas from environmental ecosystem literature to inform the nature of ecosystems. By integrating environmental actors and ecological insights into the understanding of service ecosystems, service scholars are well placed to make unique contributions to the global challenge of creating a sustainable future.

The purpose of this study is to provide insights and guidance for practitioners in terms of ensuring rigorous ethical and moral conduct in artificial intelligence (AI) hiring and implementation.

The research employed two experimental designs and one pilot study to investigate the ethical and moral implications of different levels of AI implementation in the hospitality industry, the intersection of self-congruency and ethical considerations when AI replaces human service providers and the impact of psychological distance associated with AI on individuals' ethical and moral considerations. These research methods included surveys and experimental manipulations to gather and analyze relevant data.

Findings provide valuable insights into the ethical and moral dimensions of AI implementation, the influence of self-congruency on ethical considerations and the role of psychological distance in individuals’ ethical evaluations. They contribute to the development of guidelines and practices for the responsible and ethical implementation of AI in various industries, including the hospitality sector.

The study highlights the importance of exercising rigorous ethical-moral AI hiring and implementation practices to ensure AI principles and enforcement operations in the restaurant industry. It provides practitioners with useful insights into how AI-robotization can improve ethical and moral standards.

The study contributes to the literature by providing insights into the ethical and moral implications of AI service robots in the hospitality industry. Additionally, the study explores the relationship between psychological distance and acceptance of AI-intervened service, which has not been extensively studied in the literature.

This study aims to examine the impact of AI service robots on restaurant customers' engagement and acceptance and the moderating role of robot anthropomorphism on the relationship between AI robot service quality and customer engagement.

Using a three-wave time-lagged design, 416 customers of service robots-enabled restaurants participated in the study. Mplus was used to examine the hypotheses.

The results confirmed that customers' perception regarding automation, personalization, efficiency and precision of robot service quality determine customer engagement, which further influences customer acceptance of AI service robots. Additionally, robot anthropomorphism moderates the relationships between AI robot service quality in terms of automation, personalization, efficiency and precision and customer engagement. This study confirms that AI service robots-customer engagement contributes to better acceptance of AI service robots.

The proposed framework can be used as a diagnostic tool to enhance customer acceptance of AI service robots in restaurant settings. This research provides guidelines to restaurant owners to employ AI service robots in front-line services that provide better quality, ultimately enhancing customer engagement and acceptance.

This study fills the gap in the literature by investigating the influence of AI robot service quality on customer engagement and customer acceptance with the moderating effect of robot anthropomorphism in an emerging market context.

In the tourism industry, immersive technologies become increasingly vital, amplifying traveler experiences and industry growth. By studying “e-booking” applications prevalent in hotels, this study aims to analyze the impact of integrating an anthropomorphic virtual agent (AVA) on user perceptions of humanness and service usage intent.

Two experiments were conducted to examine the effects of using an AVA and explain the psychological mechanism of how AVA’s attributes increase intention to use “e-booking” application.

The results highlight the positive influence of AVA on the intention to use. They illustrate the psychological mechanism of how AVA’s attributes (agency and emotionality) influence perceived humanness and intention to use. More specifically, the results indicate that perceived humanness mediated the effect of an AVA on intention to use.

Further research should delve into additional capabilities related to humanness.

This study provides useful insights for hotels’ managers about incorporating AVAs in digital services to enhance the perceived humanness of AVAs. The findings suggest that such efforts could yield benefits, especially when they involve conveying that AVAs possess agency and emotionality.

To the best of the author’s knowledge, this study is the first to investigate how AVA impacts hotel human–computer interaction. It examines agency and emotionality features on humanness perception and behavioral intent. It also guides successful digitalized hotel service development and design, expanding existing research on human–virtual agent digital services, which mainly focuses on superficial traits like face and gender.

The purpose of this study is to explore the mechanism of digitalized transformation in organizations’ human resource management (HRM). This study summarizes three basic factors driving the digital transformation process in China: level of perception, level of application and speed of transformation.

This study analyzes the strategic transformation process of HRM in Haier, Hisense and Chambroad to explore the human resource digital transformation mechanism in Chinese enterprises.

The results of this study show that three HR value chain models can be constructed based on how well HRM deals with business: the efficiency-oriented HRM value chain, quasi-business-oriented HRM value chain and business-oriented HRM value chain. The basic factors – level of perception, level of application and speed of transformation – are observed in the entire HRM digital transformation process.

This study provides theoretical and empirical insights for enterprises to explore the value of digital technology in HRM and facilitate the digital transformation of HRM.