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Explore how the degree of humanization affects user misconduct, and provide effective misconduct prevention measures for the wide application of artificial intelligence in the future.

Based on the “Uncanny Valley theory”, three experiments were conducted to explore the relationship between the degree of humanization of service machines and user misbehavior, and to analyze the mediating role of cognitive resistance and the moderating role of social class.

There is a U-shaped relationship between the degree of humanization of service machines and user misbehavior; Social class not only regulates the main effect of anthropomorphism on misbehavior, but also regulates the intermediary effect of anthropomorphism on cognitive resistance, thus affecting misbehavior.

The design of the service robot can be from the user’s point of view, combined with the user’s social class, match different user types, and provide the same preferences as the user’s humanoid service robot.

This study is an important reference value for enterprises and governments to provide intelligent services in public places. It can prevent the robot from being vandalized and also provide users with a comfortable human-computer interaction experience, expanding the positive effects of providing smart services by government and enterprises.

This study avoids and reduces users' misbehavior towards intelligent service robots, improves users' satisfaction in using service robots, and avoids service robots being damaged, resulting in waste of government, enterprise and social resources.

From the perspective of product factors to identify the inducing factors of improper behavior, from the perspective of social class of users to analyze the moderating effect of humanization degree and user improper behavior.

Within the scope of the research, articles about service robots were examined by the systematic review method.

The research aims to evaluate the articles on service robots, an artificial intelligence (AI) application in restaurant businesses, using a systematic review method. In systematic reviews, the data obtained as a result of scanning databases to find an answer to a research question are synthesized and reported. The criterion sampling technique, one of the purposeful sampling methods, was used for the sample of the research. Inclusion and exclusion criteria were applied within the scope of screening.

The articles on service robots were carried out between 2018 and 2023. In terms of research methods, most of the articles are quantitative, while there are studies on mixed and qualitative methods. In studies, data were generally collected by survey technique. The keywords of the studies on service robots are examined; the most commonly used words were service robot and AI, technology, restaurant, satisfaction, revisit intention, consumer behavior, intention, preference, hospitality and foods. The objectives of the articles pertinent to service robots are mostly to determine people's attitudes and acceptance toward these services focuses.

The studies seem to focus more on customer acceptance, trust, expectations, risks, adaptation, reasons for preference, impact on creative services, emotional and cognitive effects and human–robot interaction. Despite this, it is observed that there are fewer studies on topics such as the development of service robots in restaurant businesses, their reflections on the future, future opportunities and the quality of chef service robots. Based on this, it is recommended to consider studies that will serve as a reference for revealing innovative opportunities that can meet future expectations in order to increase the quality of service robots in restaurant businesses.

This study aims to investigate tourists’ intentions to use hotel service robots with a focus on safety and hygiene. It examines the impact of perceived safety, health awareness and service assurance on consumer engagement and robot usage.

Survey data from 275 participants with experience in robotic service were analyzed using structural equation modeling (SEM). The study used purposive sampling and collected data via the Prolific platform, using SEM and SmartPLS Ver. 3.0 for analysis.

Results indicate customers prioritize safety and hygiene, valuing effective service responses and cleanliness. Perceived robotic safety and service assurance positively influence personal engagement, with a preference for service robots among female guests.

While emphasizing the importance of safety and service assurance in hotel robotics, the study acknowledges limitations in personalization and conclusive use of service robots.

This research contributes to understanding the role of perceived safety in service robot usage, highlighting the significance of user trust and comfort in human–robot interactions. It also explores the novel connection between service assurance and service robots, offering insights into robotic performance reliability in user-centric contexts.

Robots have been adopted in numerous tourism and hospitality sectors, including restaurants. This study aims to investigate fast-food employees' use of service robots (SRs) in Pakistan.

This study used a conceptual model based on innovation resistance theory (IRT). By employing structural equation modeling (SEM) in Smart-PLS 3.2.8, we evaluated data from 247 valid respondents.

The findings demonstrated that drivers of robot adaptation significantly influenced image barriers, risk barriers, traditional barriers, usage barriers and value barriers. The results also revealed that usage, image and traditional barriers significantly affect usage intention.

This study enhances the research on robotics acceptance in tourism and hospitality and subsequently aids in the planning for post-COVID-19 resumption. This study offers several practical and theoretical insights for further investigation.

This study investigates human behavior, specifically attitude and anxiety, toward humanoid service robots in a hotel business environment.

The researcher adopted direct observations and interviews to complete the study. Visitors of Henn-na Hotel were observed and their spatial distance from the robots, along with verbal and non-verbal behavior, was recorded. The researcher then invited the observed hotel guests to participate in a short interview.

Most visitors showed a positive attitude towards the robot. More than half of the visitors offered compliments when they first saw the robot receptionists although they hesitated and maintained a distance from them. Hotel guests were also disappointed with the low human–robot interaction (HRI). As the role of robots in hotels currently remains at the presentation level, a comprehensive assessment of their interactive ability is lacking.

This study contributes to the HRI theory by confirming that people may treat robots as human strangers when they first see them. When a robot's face is more realistic, people expect it to behave like an actual human being. However, as the sample size of this study was small and all visitors were Asian, the researcher cannot generalize the results to the wider population.

Current robot receptionist has limited interaction ability. Hotel practitioners could learn about hotel guests' behavior and expectation towards android robots to enhance satisfaction and reduce disappointment.

Prior robot research has used questionnaires to investigate perceptions and usage intention, but this study collected on-site data and directly observed people's attitude toward robot staff in an actual business environment.

This study aims to focus on publications that jointly address robots in the tourism field and the technology acceptance model (TAM).

This study adopts bibliometric analysis. Publications listed in the Web of Science database constitute the scope of this research. 51 publications were analyzed within the scope of the research.

Between the years 2017 and 2023, an upward trend in the number and citations of publications was identified. It has been observed that article studies are more prevalent compared to other types of publications. When considering the indexes of the publications, a significant majority were found to be in Social Sciences Citation Index (SSCI) and Science Citation Index (SCI)-EXPANDED. The status of the keywords identified within the scope of the research in the abstracts of the publications has been presented. The keyword “robot” was found to be the most frequently occurring in the abstracts. The abstracts were also analyzed, and the publications were accordingly clustered into five distinct themes.

This study offers a comprehensive evaluation of publications concerning the use of robots in the tourism sector, framed within the context of the TAM. Within the scope of the study, the findings were interpreted using bibliometric analysis. The publications have been categorized into themes. The results presented provide insights into the necessity for further publications in this field.

To influence consumer pre-purchase decision-making processes, such as brand selection and perceived brand experience, brands are interested in adopting hyperconnected technological stimuli, such as artificial intelligence, augmented reality (AR), virtual reality, social media and tech devices. However, the understanding of different hyperconnected touchpoints remained shallow and results mixed in previous literature, despite the fact that these touchpoints span different technological interfaces/devices and may influence consumer brand selection. This paper aims to solidify the conceptual underpinnings of the role of online hyperconnected stimuli, which may influence consumer psychological reactions in terms of brand selection and experience.

This paper is conceptual and presents a discussion based on extant literature from various international publishers.

The authors revealed different technological stimuli in the online hyperconnected environment that may influence consumer online hyperconnected brand selection (OHBS), perceived online hyperconnected brand experience (OHBE), perceived well-being and behavioral intention.

The conceptual understanding of OHBS and perceived OHBE was mixed and inconsistent in previous studies. This paper brings together extant literature to establish the conceptual understanding of antecedents and outcomes of OHBS, i.e. perceived OHBE, perceived well-being and behavioral intention, and presents a cohesive conceptual framework.

To date, to the best of the authors’ knowledge, the use of implicit measures in the service research domain is limited. This paper aims to introduce implicit measures and explain why, or for what purpose, they are worthwhile to consider; how these measures can be used; and when and where implicit measures merit the service researcher’s consideration.

To gain an understanding of how implicit measures could benefit service research, three promising implicit measures are discussed, namely, the implicit association test, the affect misattribution procedure and the propositional evaluation paradigm. More specifically, this paper delves into how implicit measures can support service research, focusing on three focal service topics, namely, technology, affective processes including customer experience and service employees.

This paper demonstrates how implicit measures can investigate paramount service-related subjects. Additionally, it provides essential methodological “need-to-knows” for assessing others’ work with implicit measures and/or for starting your own use of them.

This paper introduces when and why to consider integrating implicit measures in service research, along with a roadmap on how to get started.

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.

Financial services industry is increasingly showing interest in automated financial advisors, or robo-advisors, with the aim of democratizing access to financial advice and stimulating investment behavior among populations that were previously less active and less served. However, the extent to which consumers trust this technology influences the adoption of rob-advisors. The resemblance to a human, or anthropomorphism, can provide a sense of social presence and increase trust.

In this paper, we conduct an experiment (N = 223) to test the effect of anthropomorphism (low vs medium vs high) and gender (male vs female) of the robo-advisor on social presence. This perception, in turn, enables consumers to evaluate personality characteristics of the robo-advisor, such as competence, warmth, and persuasiveness, all of which are related to trust in the robo-advisor. We separately conduct an experimental study (N = 206) testing the effect of gender neutrality on consumer responses to robo-advisory anthropomorphism.

Our results show that consumers prefer human-alike robo-advisors over machinelike or humanoid robo-advisors. This preference is only observed for male robo-advisors and is explained by perceived competence and perceived persuasiveness. Furthermore, highlighting gender neutrality undermines the positive effect of robo-advisor anthropomorphism on trust.

We contribute to the body of knowledge on robo-advisor design by showing the effect of robot’s anthropomorphism and gender on consumer perceptions and trust. Consequently, we offer insightful recommendations to promote the adoption of robo-advisory services in the financial sector.