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Taking a mixed-method approach, this research developed and validated a novel, value-centric experience framework delineating robotic involvement in the service encounter and its subsequent impact on customers' experiences.

Focused on robotic restaurant businesses where robots are mainly involved in food production processes, this research utilized online customer review data and a multistage, mixed-method design for empirical examination. Automated thematic analysis was first adopted to facilitate a comprehensive understanding of the empirical reality as reflected in online customer reviews. Following an analytic induction process, a theoretical framework was developed integrating prior literature with the empirical reality to uncover the relationships across robotic involvement, experiential values and evaluative outcomes. A theory-driven, dictionary-based content analysis together with path analysis further enabled empirical validation of the developed theoretical framework.

The current research developed and validated a value-centric experience framework to theorize robotic involvement in the service encounter and its downstream impact on customers' experiences. Specifically, this framework conceptualizes robotic involvement as a five-dimensional composition of robotic visibility, competency, performanism, co-creativity and prominence. In addition, the framework specifies seven dimensions of experiential values revolving around high-tech–high-touch robotic service encounters, namely sensorial, utilitarian, hedonic, social, agentic, epistemic and aesthetic values. Following empirical validation, this framework sheds light on robotic involvement and experience design for high-tech–high-touch service businesses aiming to incorporate robots in their service encounters.

Drawing on classic service role theory and consumption value theory, this research developed and validated a novel theoretical model connecting robotic involvement dimensions with experiential consumption values and downstream customer evaluative outcomes. This research and theoretical framework open an exciting avenue for future research in robotic services and customer experiences.

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.

The purpose of this study is to investigate the robotic restaurant experience of travellers around the world and understand the components of robotic restaurant experience.

Travellers who had experienced a robotic restaurant were purposefully selected as a sample group for the study. As the robotic restaurants are limited around the world, multiple case study method has been chosen to gather richer data. A user-generated content technique which is a form of qualitative case study method has been benefited to gather data from travellers’ reviews.

The results reveal a model of components of robotic restaurant experience that include six main themes: attraction for kids, robotic system, memorable experience, ambience related attributes, food related attributes (economic value and gastronomic aspects) and deficiencies (in robotic system, in ambience related attributes and in food related attributes).

This paper is one of the first to investigate the robotic restaurant experience of travellers around the world. Moreover, it contributes to the research on restaurant experience and offers a model of components of the robotic restaurant experience.

The purpose of this paper is to investigate the influencing factors of generation Z (Gen Z) consumers’ revisit intentions to robotic restaurants in the post-pandemic times.

Using a sample of Gen Z consumers with dining experiences in an Indian restaurant using service robots, the study empirically tests a research framework based on stimulus–organism–response theory.

The study explains how Gen Z consumer’s perceptions of functional attributes (i.e. perceived usefulness and perceived ease of use), socio-emotional attribute (i.e. perceived safety) and relational attribute (i.e. trust) shape their attitude, which in turn leads to their evaluations of performance outcomes and intention to revisit the robotic restaurants. The findings also indicate that perceived risk reduction of viral infection moderates the impact of performance outcomes on revisit intention.

Due to the outbreak of COVID-19 pandemic, the changing preferences of consumers have resulted in an increase in demand for restaurants offering robotic services. To support the long-term viability of service robots in restaurant services, the current study investigates what elements of service robots can determine consumers’ intentions to revisit the robotic restaurants during post-pandemic times.

Using cognitive appraisal theory, this study aims to propose and test an integrated framework – comprising robotic service quality, robotic service authenticity, customer existential authenticity and customer revisit intention – on diners with experience using robotic technology in restaurants. The moderating role of robotic appearance is in the hypothesised relationship.

Data was gathered through a Web-based survey delivered to 428 diners who had experience using robotic services in restaurants in China. The hypotheses were analysed using a structural equation model and multi-group analysis was used to analyse the moderating effect.

The findings indicate that functional service quality positively influences robotic service authenticity and existential authenticity. However, technical service quality only affects existential authenticity, which leads to revisit intention. Robotic appearance moderated the relationship between functional service quality and service authenticity.

Restaurateurs should enhance robotic service authenticity, existential authenticity and revisit intention by improving robotic technical service collaborating with robot manufacturers and operators.

Focusing on cognitive appraisal theory, the findings serve as a starting point for investigating robotic service quality and authenticity in robotic service settings theoretically and empirically.

Purpose: The purpose of this chapter is to review and critically evaluate robots, artificial intelligence and service automation (RAISA) applications in the restaurant industry to educate professors, graduate students, and industry professionals.

Design/methodology/approach: This chapter is a survey of applications of RAISA in restaurants. The chapter is based on the review of professional and peer-reviewed academic literature, and the industry insight section was prepared based on a 50-minute interview with Mr. Juan Higueros, Chief Operations Officer of Bear Robotics.

Findings: Various case studies presented in this chapter illustrate numerous possibilities for automation: from automating a specific function to complete automation of the front of the house (e.g., Eatsa) or back of the house (e.g., Spyce robotic kitchen). The restaurant industry has already adopted chatbots; voice-activated and biometric technologies; robots as hosts, food runners, chefs, and bartenders; tableside ordering; conveyors; and robotic food delivery.

Practical implications: The chapter presents professors and students with a detailed overview of RAISA in the restaurant industry that will be useful for educational and research purposes. Restaurant owners and managers may also benefit from reading this chapter as they will learn about the current state of technology and opportunities for RAISA implementation.

Originality/value: To the best of the authors’ knowledge, this chapter presents the first systematic and in-depth review of RAISA technologies in the restaurant industry.

This study aims to investigate Generation Z’s perception of and experience with restaurant service robots.

Established on the servicescape theoretical framework and following Zaltman Metaphoric Elicitation Technique, 34 in-depth interviews were conducted with Generation Z consumers.

The results showed that Generation Z consumers had a generally positive attitude toward the usage of service robots in restaurants. Research participants also indicated aspects that can be improved: the service robot’s appearance design and functionality, and the human service facilitating the robotic service process.

This paper provides a holistic understanding of the Generation Z’s mind maps about robot service restaurants presenting practical suggestions for restaurants.

This research offers an in-depth understanding of how the young consumption power perceives and expects the innovative service robots employed in restaurants. The research findings provide industry practitioners with timely guidelines to improve the usage of robotic services in restaurants to satisfy the emerging consumer group of Generation Z.

The current research contributes to the servicescape literature by extending this long-standing theory to the emerging robotic service contexts for updating discoveries. Particularly, the study focuses on the young consumers of Generation Z, shedding lights on the generational cohort research.

本研究调查了 Z 世代对餐厅服务机器人的看法和体验。

建立在服务场景理论框架之上, 并遵循 Zaltman 隐喻启发技术, 对 Z 世代消费者进行了 34 次深入访谈。

结果表明, Z 世代消费者对在餐厅使用服务机器人持普遍积极态度。 研究参与者还指出了可以改进的方面：服务机器人的外观设计和功能, 以及促进机器人服务过程的人工服务。

这项研究深入了解了年轻的消费力量如何看待和期望在餐厅使用的创新服务机器人。 研究结果为行业从业者提供了及时的指导方针, 以改善机器人服务在餐厅的使用, 以满足 Z 世代的新兴消费群体。

当前的研究通过将这一长期存在的理论扩展到新兴的机器人服务环境以更新发现, 从而为服务景观文献做出贡献。 特别是, 该研究侧重于 Z 世代的年轻消费者, 阐明了世代队列研究。

Robotic chefs are starting to replace human chefs in restaurant industry. Whether customers have a good food quality prediction may have an important effect on their patronage decision. Based on the stereotype content model, the purpose of this paper is to investigate the impact of robotic chef anthropomorphism on food quality prediction through warmth and competence.

An empirical analysis was done to test the theoretical model by using the SmartPLS software. A nonhuman-like robotic chef and a robotic chef with humanoid hands were used as background materials in the questionnaire. The effective sample was 221.

Robotic chef anthropomorphism affects food quality prediction through the sequential mediators of warmth and competence. Age is a significant control variable.

Robotic chef anthropomorphism positively affects food quality prediction. The halo effect of warmth perception on competence perception should be considered in the context of robot anthropomorphism.

Restaurants which feature robotic chefs should use robotic chefs with anthropomorphic designs and promote the anthropomorphic elements of robotic chefs in advertisements.

The anthropomorphic design of robot chefs will facilitate the development of artificial intelligence in restaurants in the future.

To the best of the authors’ knowledge, this paper is one of the first to focus on how robotic chef anthropomorphism affects food quality prediction and reveals the roles of warmth and competence in the influence of robotic chef anthropomorphism on food quality prediction.

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 study examined the effect of brand modernity on brand love. In addition, this study investigated how brand love affects behavioral intentions including intentions to use, word-of-mouth and willingness to pay more. Lastly, this study explored the differences between robot servers and human servers in the five concepts mentioned above.

Data were collected from 300 people who experienced robot servers and from 318 people who experienced human servers.

The results of data analysis revealed that brand modernity has a positive influence on brand love, which in turn positively affects intentions to use, word-of-mouth and willingness to pay more. Additionally, it was found that there were statistical differences with the mean value of the five concepts based on the type of employee, such as robot servers and human servers.

Unlike prior research, the difference between robot servers and human servers was investigated by focusing more on the brand in this study, and such findings can be considered as important theoretical implications of this study.