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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.

This paper aims to understand the process of guest-robot value co-creation in the restaurant context. It empirically examines the guest perception of value facilitation by service robots and its impact on guest value co-creation and advocacy intentions. It also investigates the moderating role of interaction comfort in the relationship between service robot value facilitation and guest value co-creation.

A mixed-methods approach was adopted. Ten customers who had dined at a service robot restaurant in China were interviewed in the qualitative study, followed by a quantitative study with 252 restaurant patrons to test the relationships between service robot value facilitation, guest value co-creation, interaction comfort and advocacy intentions.

Guest perceptions of six robot attributes, including role significance, competence, social presence, warmth, autonomy and adaptability, determine service robot value facilitation. Interaction comfort moderates the influence of service robot value facilitation on guest value co-creation. Additionally, guest value co-creation mediates the effect of service robot value facilitation on advocacy intentions.

This study offers an understanding of six robot attributes that can improve service robot value facilitation. Nevertheless, the authors collected data from guests who had experience at service robot restaurants. The authors encourage future research to use random sampling methods to ensure study representativeness.

This study offers strategic guidance for managers to deploy service robots in frontline roles in restaurants and provides important implications for service robot design to improve their facilitating role in the guest value co-creation process.

This study responds to a recent call for research on the role of service robots in the guest value co-creation experience. Unlike prior studies that focused on the adoption or acceptance of service robots, it examines the role of service robots in the value co-creation process (post-adoption stage). Furthermore, it is one of the early studies to identify and empirically examine the service robot attributes that enable value facilitation and foster value co-creation in guest-robot service encounters.

The purpose of this study is to explore the impact of the robot restaurant servicescape and robot service competence (RSC) on customers’ behavioral intentions and to analyze the mediating role of hedonic value (HV) and utilitarian value (UV) in these relationships and the moderating role of individual characteristics.

This research involves seven constructs to be measured, namely, servicescape, RSC, negative attitude toward robots (NAR), openness to change (OC), HV, UV and behavioral intention. This research selects Foodom robot restaurants, located in Shunde and Guangzhou of China, as the research site, and the research objects are customers having dinner in the restaurant. A total of 485 valid data was collected. Structural equation modeling was used to analyze the data, verify the proposed research model, and test the research hypotheses.

The study finds that servicescape and RSC improve customer behavioral intention. Additionally, HV and UV mediate the influence of servicescape and RSC on customer behavioral intention. Moreover, OC negatively moderates the influence of servicescape on UV and that a NAR negatively moderates the influence of RSC on HV.

Through carefully design of servicescape and the improvement in service capabilities of robots, the original service delivery dominated by frontline service personnel can be transformed into service delivery dominated by service robots, which is conductive to providing a pleasant and unforgettable experience for customers.

Anthropomorphism in Artificial Intelligence (AI)-powered devices is being used increasingly frequently in consumer-facing situations (e.g., AI Assistants such as Alexa, virtual agents in websites, call/chat bots, etc.), and therefore, it is essential to understand anthropomorphism in AI both to understand consequences for consumers and to optimize firms' product development and marketing. Extant literature is fragmented across several domains and is limited in the marketing domain. In this review, we aim to bring together the insights from different fields and develop a parsimonious conceptual framework to guide future research in fields of marketing and consumer behavior.

We conduct a review of empirical articles published until November 2021 in Financial Times Top 50 (FT50) journals as well as in 41 additional journals selected across several disciplinary domains: computer science, robotics, psychology, marketing, and consumer behavior.

Based on literature review and synthesis, we propose a three-step guiding framework for future research and practice on AI anthropomorphism.

Our proposed conceptual framework informs marketing and consumer behavior domains with findings accumulated in other research domains, offers important directions for future research, and provides a parsimonious guide for marketing managers to optimally utilize anthropomorphism in AI to the benefit of both firms and consumers.

We contribute to the emerging literature on anthropomorphism in AI in three ways. First, we expedite the information flow between disciplines by integrating insights from different fields of inquiry. Second, based on our synthesis of literature, we offer a conceptual framework to organize the outcomes of AI anthropomorphism in a tidy and concise manner. Third, based on our review and conceptual framework, we offer key directions to guide future research endeavors.

Drawing on the cognitive–affective–conative framework, this study aims to develop a model of service robot acceptance in the hospitality sector by incorporating both cognitive evaluations and affective responses.

A mixed-method approach combining qualitative and quantitative methods was used to develop measurement and test research hypotheses.

The results show that five cognitive evaluations (i.e. cuteness, coolness, courtesy, utility and autonomy) significantly influence consumers’ positive affect, leading to customer acceptance intention. Four cognitive evaluations (cuteness, interactivity, courtesy and utility) significantly influence consumers’ negative affect, which in turn positively affects consumer acceptance intention.

This study provides significant implications for the design and implementation of service robots in the hospitality and tourism sector.

Different from traditional technology acceptance models, this study proposed a model based on the hierarchical relationships of cognition, affect and conation to enhance knowledge about human–robot interactions.

This study aims to apply the service robot acceptance model (sRAM) to examine how attitude toward human–robot interaction (HRI) and engagement influence consumer acceptance of service robots in a frontline setting.

Data was collected from 255 visitors who interacted with a robotic tour guide at a city museum. The data was analyzed using smart PLS 4.0.

The findings show the positive effects of subjective norms, appearance, perceived trust and positive emotion on both attitude toward HRI and engagement. In addition, social capability impacted attitude toward HRI, whereas perceived usefulness affected engagement.

To deliver engaging museum experiences that bring about positive word-of-mouth and intention to visit, managers need to incorporate the sRAM dimensions in the design and deployment of service robots.

This research uses field data to empirically validate the sRAM in the context of service robot acceptance. It introduces engagement as a novel mediating variable, enriching current understanding of human-like qualities in HRIs.

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 simultaneously examine the influence of demographic, psychographic and situational factors on consumers’ willingness to pay a price premium (WTPp) for robotic restaurants and to profile market segments based on consumers’ WTPp levels (positive, neutral and negative).

Using an online survey, the data were gathered from a sample of 897 Thai consumers who had dined at a robotic restaurant in the past 12 months. Structural equation modeling, chi-square tests and the one-way analysis of variance were used for data analysis.

Demographic (gender, age, income and marital status), psychographic (perceived advantages/disadvantages, personal innovativeness and personality traits) and situational factors (perceived health risk and self-protection behavior) significantly influence consumers’ WTPp for robotic restaurants. The positive price premium group differs significantly from the neutral and negative price premium groups in terms of demographic, psychographic and situational profiles.

The findings of this study help restaurateurs target the correct customers and set up appropriate price fences to safeguard profits and maximize return on investment.

This study contributes to the literature on technology-based services and hospitality by heeding the calls made by Ivanov and Webster (2021) and providing much-needed empirical evidence of possible changes in consumers’ WTPp for robot-delivered services in restaurants due to COVID-19.

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.