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This study aims to investigate the effects of hotel customers’ perceived utilitarian and hedonic values on their intention to use service robots. In addition, the influences of innovativeness, ease of use and compatibility on hotel customers’ perceived utilitarian and hedonic values were examined.

The data of the current study was collected from 11 countries including the USA, UK, Turkey, Spain, Romania, Japan, Israel, India, Greece, Canada and Brazil. A structural equation modeling was used to test the study hypotheses.

The results indicated that hotel customers’ intention to use service robots was positively influenced by their utilitarian and hedonic value perceptions. In addition, customers’ perceptions of robots’ ease of use and compatibility had a positive impact on their perceived utilitarian and hedonic values.

The findings of the current study provide unique contributions in the context of hospitality robotics technology adoption literature. In addition, this study provides valuable insights and novel opportunities for hospitality decision-makers to capitalize on, as they strive to strategize the integration of robot-based services into their operations.

本研究调查了酒店顾客感知功能性价值和享乐性价值对服务机器人使用意向的影响。此外, 本研究考察了创新性、易用性和兼容性对酒店顾客感知功能性价值和享乐性价值的影响。

本研究的数据来自美国、英国、土耳其、西班牙、罗马尼亚、日本、以色列、印度、希腊、加拿大和巴西等十一个国家, 采用结构方程模型（SEM）对研究假设进行测试。

结果表明, 酒店顾客使用服务机器人的意向受到他们对功能性价值和享乐性价值的感知的积极影响。此外, 机器人易用性和兼容性对功能性价值和享乐性价值有积极影响。

本研究的发现对酒店行业机器人技术应用文献提供了独特的贡献。此外, 本研究为酒店业的决策者提供了宝贵的见解和新机遇, 使他们能够在将机器人服务的优势整合到酒店运营中。

The purpose of this study is to identify the factors that influence the development of service robots, and to apply a service innovation strategic mindset to the hotel industry in Taiwan.

A mixed-methods approach, combining an expert panel and semi-structured interviews using a SMART SWOT ranking survey, was applied to understand the perspectives of hotel owners and robotics experts.

Fifty-three items were collected regarding the demand side of the hospitality market, showing that the Taiwan hospitality industry has good potential to implement service robots. Sixty-one items on the supply side of business were collected, showing that this robotics service can help hotels handle seasonal employment and labor utilization. The SWOT analysis identifies “The fun and curiosity aroused in consumers can enhance the promotion of service robots”, “Lack of talent in system integration”, “Taiwan’s aging society can increase the demand for service robots” and “China and South-east countries have aggressively poached talent in the global robotics market” as key issues.

Few studies have investigated robotics service for hotels using the six-dimensional service innovation model. This model helps identify six factors and implies that this new service concept can position hotels to better compete by using IT and relationship marketing strategies.

This paper aims to analyze if and to what extent mechanical artificial intelligence (AI)-embedded in hotel service robots-influences customers’ evaluation of AI-enabled hotel service interactions. This study deploys online reviews (ORs) analytics to understand if the presence of mechanical AI-related text in ORs influences customers’ OR valence across 19 leading international hotels that have integrated mechanical AI – in the guise of service robots – into their operations.

First, the authors identified the 19 leading hotels across three continents that have pioneered the adoption of service robots. Second, by deploying big data techniques, the authors gathered the entire population of ORs hosted on TripAdvisor (almost 50,000 ORs) and generated OR analytics. Subsequently, the authors used ordered logistic regressions analyses to understand if and to what extent AI-enabled hospitality service interactions are evaluated by service customers.

The presence of mechanical AI-related text (text related to service robots) in ORs influences positively electronic word-of-mouth (e-WOM) valence. Hotel guests writing ORs explicitly mentioning their interactions with the service robots are more prone to associate high online ratings to their ORs. The presence of the robot’s proper name (e.g., Alina, Wally) in the OR moderates positively the positive effect of mechanical AI-related text on ORs ratings.

Hospitality practitioners should evaluate the possibility to introduce service robots into their operations and develop tailored strategies to name their robots (such as using human-like and short names). Moreover, hotel managers should communicate more explicitly their initiatives and investments in AI, monitor AI-related e-WOM and invest in educating their non-tech-savvy customers to understand and appreciate AI technology. Platform developers might create a robotic tag to be attached to ORs mentioning service robots to signal the presence of this specific element and might design and develop an additional service attribute that might be tentatively named “service robots.”

The current study represents the first attempt to understand if and to what extent mechanical AI in the guise of hotel service robots influences customers’ evaluation of AI-enabled hospitality service interactions.

Using the Delphi technique, this paper aims to investigate how human resource experts perceive service robots will impact leadership and human resource management in the hospitality industry.

A three-stage Delphi study with hotel industry human resource experts was conducted to identify the key trends and major challenges that will emerge in the next ten years and how leaders should deal with the challenges brought about by service robot technologies.

The results show that while service robots are anticipated to increase efficiency and productivity of hotel activities, they may also pose challenges such as high costs, skill deficits and significant changes to the organizational structure and culture of hotels. Therefore, the anticipated applications and integration of robotic technology will require leaders of the future to carefully consider the balance between the roles of service robots and human employees in the guest experience and to nurture a work environment that embraces open-mindedness and change.

This is the first type of study to examine hospitality leadership and human resource management in the context of robotized hotels. This study has taken an important step to understand the leadership role in robotized hotels from a human resource perspective and brings clarity as to how robotic technology can influence leadership in the future workplace.

The main purpose of this study is to investigate the impact of service robots on hotel visitors' behaviour and to verify the role of anthropomorphism(human likeness) in customer satisfaction with robots.

An online survey of 381 respondents was conducted, divided into three types of robots according to the level of anthropomorphism. The research model was thoroughly tested using the PLS-SEM method. Research model was tested thoroughly using the PLS-SEM method.

This study found that user satisfaction with service robots in a hotel had a positive impact on user satisfaction, attitude towards the hotel and room purchase intention. Moreover, our results showed that users were most likely to accept medium-human likeness robots and least likely to accept high–human likeness robots.

This study proposes influencing factors to be considered when researching hotel service robots, as well as practical suggestions for any hotel intending to use or currently using a service robot.

This paper aims to propose an operation policy of multi-capacity room service robots traveling within a hotel. As multi-capacity robots can serve many requests in a single trip, improved operation policy can reduce the investment cost of robots.

Using a mathematical model-based optimization technique, an optimal set of robots with minimum installation cost is derived while serving the entire room service demands. Through testing a variety of scenarios by changing the price and function of robots to be installed, insights that consider the various situations are offered.

Though the increase in capacity saves much time for room service at a lower capacity level, the amount of time saved gradually decreases as the capacity increases. Besides, the installation strategy is divided into two cases depending on the purchase cost of robots.

Currently, the studies focusing on the adoption of service robots from an operations view are rarely be found. To reduce the burden of investment cost, this study takes the unique approach to improve the operation policy of service robots by using the multi-capacity robots.

This study guides the hotel to install an adequate set of robots. The result confirms that the optimal installation set of robots is affected by various factors, such as the room service information, the hotel structure and the unit execution cycle.

After the outbreak of COVID-19, people avoid face-to-face contact and interest in non-contact service is growing. This paper deals with the efficient way to implement non-contact delivery through logistic robots, a timely and important topic.

Robots, as the crystallization of new artificial intelligence, are being applied in various fields, especially the hotel industry. They are seizing the opportunities, using technology to improve the overall quality and comprehensive competitiveness. However, they also cause many problems due to practical limitations. The purpose of this paper is to study customers' recognition and acceptance of hotel service robots to guide the successful promotion of this technology.

This paper proposed a comprehensive model based on the theory of planned behavior, the technology acceptance model and then the perceived value-based acceptance model. Exploratory factor analysis, confirmatory factor analysis, grouped regression analysis and path analysis was adopted to validate the impacts of each variable to obtain the final reliable model using data collected from hotel guests using a self-designed questionnaire.

The empirical research based on the theoretical model shows that the constructed conceptual model can thoroughly explain the influencing factors of hotel robot acceptance, enrich the acceptance theory and provide academic support for the use and popularization of hotel service robots. Among all variables, attitude, usefulness and perceived value are the factors that have the greatest impact on acceptance. They have significant differences in the effects of adjustment variables such as gender, educational level, whether hotel robots have been used, and whether other robot services have been experienced on different paths in the model.

This paper explored the customer acceptance of service robots in hotels, helped to understand the process of decision-making on service robot selection and contributed to the theoretical extension of the hospitality industry. The work guides hotel management to promote better-personalized products and services of robot technology in the hospitality industries.

The acceptance study on hotel service robots provides insight into the hotel industry to understand customers' attitudes and acceptance of emerging technology.

The hospitality industry has witnessed numerous changes to enhance the stay experience of guests. To offer a memorable stay experience, the industry has started deploying intelligent robots. Therefore, this case study aims to examine and explore artificial intelligence (AI) enabled robots in hospitality industry in order to enhance guest experience in a smart city.

Semistructured interviews have been conducted at Novotel Ambassador Seoul Dongdaemun Hotels and Residences, Seoul, South Korea, to understand the stay experience of guests regarding services offered by AI enabled robots. The authors have selected employees for interviews since employees listen and witness the guest experience directly. Out of 214 employees in the hotel with varied experience and background, 26 interviews are conducted.

Through a systematic approach of coding, the authors have identified that deploying AI enabled robots facilitates the automation, information gathering, personalization and seamless service in the hospitality industry of a smart city. Further, with a back-and-forth mapping mechanism based on epistemological principles, the authors made four propositions that lead to the development of a research framework.

The practicing managers of hospitality industry can employ AI enabled robots within the scope of improving and automating the processes that can also offer increased personalization to enhance the stay experience, which is expected in a smart city.

The study offers a unique contribution to literature, since it is a live case study, and the information is from the practicing employees of a well-known organization in a hospitality sector from a smart city (Novotel Ambassador Seoul Dongdaemun Hotels and Residences, Seoul, South Korea).

The hotel industry has witnessed an increasing number of service automation through service robots such as robot concierges. However, few studies have documented how to identify how hotel guests perceive a robot concierge for their service encounter. Therefore, the purpose of this study is to examine the effects of robot concierges on hotel guests’ attitudes and adoption intentions of robot concierges.

This study investigated the effects of robot concierges’ morphology and their level of interactivity with guests at different levels of hotel service on guests’ attitudes and their intentions to adopt robot concierges. To achieve the study’s objectives, this study conducted a 3 × 2 × 3 between-subjects factorial design experiment. Moreover, the survey asked questions about subjects’ preferences of their service encounters (e.g. human employees, robot concierges and/or no preference) and reasons for their selected preference.

The results demonstrated that the robot’s morphology significantly influenced guests’ attitudes toward robot concierges. In particular, the caricatured robot was the most preferred morphology of robot concierges. The findings showed that even if guests had favorable attitudes toward robot concierges, they preferred human employees to robot concierges because of humans’ sincere and genuine interactions.

This study contributes to the literature by investigating the causal impacts of the morphology of robot concierges, level of interactivity and level of hotel service on guests’ attitudes toward robot concierges. The thematic analysis of service encounter preference provides an overview of the factors that guests expect for their service encounters in a hotel setting.

The purpose of this paper is to consider three factors, namely, intra-week demand fluctuations, interrelationship between the number of robots and order scheduling and conflicting objectives (i.e. cost minimization and customer satisfaction maximization), to optimize the robot logistics system.

The number of robots and the sequence of delivery orders are first optimized using the heuristic algorithm NSGACoDEM, which is designed using genetic algorithm and composite difference evolution. The superiority of this method is then confirmed by a case study of a four-star grade hotel in South Korea and several comparative experiments.

Two performance metrics reveal the superior performance of the proposed approach compared to other baseline approaches. Results of comparative experiments found that the consideration of three influencing factors in the operation design of a robot logistic system can effectively balance cost and customer satisfaction over the course of a week in hotel operation and optimize robot scheduling flexibility.

The results of this study reveal that numerous factors (e.g. intra-week demand fluctuations) can optimize the performance efficiency of robots. The proposed algorithm can be used by hotels to overcome the influence of intra-week demand fluctuations on robot scheduling flexibility effectively and thereby enhance work efficiency.

The design of a novel algorithm in this study entails enhancing the current robot logistics system. This algorithm can successfully manage cost and customer satisfaction during off-seasons and peak seasons in the hotel industry while offering diversified schemes to various types of hotels.