• No results found

This study provides valuable managerial implications for the hospitality industry. Due to the efficiency and profitability in many service sectors, managers in the hospitality industry are beginning to consider introducing service robots into their operations. Robots are increasingly capable of performing both more demanding physical and cognitive tasks (Lu et al., 2020). Therefore, the hospitality industry has great interest in experimentation with service robots and already applied social robots to assist hotel guests and shape their experiences.

Nevertheless, to ensure the success of service robots in the short and long run, customers’

support and acceptance are crucial for this type of innovation.

Results of this study suggest that the use of service robots in hotels will increase customers’ overall experience, which complements prior research that pointed out that especially digitized customers seek novel experiences, and demand the adoption of new technologies (Ivanov & Webster, 2019). Therefore it is useful to implement and promote robots as part of an interactive and fun experience, which could increase customer experience and customer referrals.

Nevertheless, managers need to be aware of guests’ discomfort with service robots.

Results of this study show that particularly older individuals are less likely to accept service robots and tend to have less customer experience when a service is carried out by a service robot. Hence, managers have to consider that robotic interactions are still relatively new to the hospitality industry and some guests may at first feel uncomfortable at the thought of interacting with a service robot. Besides, women are also less likely to accept and use service robots.

Overall, it is important that hotels keep this discomfort in mind, and provide help when needed in supporting guests to use service robots.

Furthermore, the construct of Robotic Service Acceptance can be applied as a measurement way for organizations to assess whether planned or already implemented service robots are likely to be accepted by their guests. This would lead to cost reductions and could be used as a ‘trial-and-error’ method to optimize service robots for the organization.

7 Limitations and future research

This research is not without limitations. These limitations can be used as

opportunities for future research in the field of service robots in the hospitality industry.

Firstly, the experiment of this study only focused on one service robot, namely Pepper.

Therefore, it would be important for future research to introduce and include other types of service robots or other artificial intelligence technologies with different functions, as this could have an influence on the customers’ overall experience.

Secondly, as only 28.6% of the participants already interacted with technology in hotels, it would be interesting to replicate the study and see whether results change for more experienced customers. Therefore, future research could explicitly focus on acquiring participants who have prior experience in the field of technology.

Thirdly, even though the use of hypothetical scenarios is a well-established practice in the literature on service robots (Park, 2020; Fan et al., 2019), this could still be viewed as a limitation of this research. To fully understand the impact of the factors studied, it is necessary to conduct field experiments and expose people to real service robots, instead of only hypothetical scenarios.

Fourthly, the cross-sectional design of this study is a limitation, because it is only measured at one point in time. Therefore, it is not possible to infer any causal relationships among the different variables.

Fifthly, the non-probability convenience sampling technique can limit the generalizability of the results of this study (Farrokhi & Mahmoudi-Hamidabad, 2012). Since this limitation impacts the overall validity of the study, future research could replicate this study by using a probability sampling technique to overcome the limitation of low external validity.

Finally, most of the participants were from the Netherlands. Future research could try to replicate this research by including more other cultures to gain a global understanding of how cultural differences might influence the perception of service robots in hotels.

8 Conclusion

Despite the rapid growth of new technologies in the hospitality business, there is still a scarcity of studies on AI-enabled customer experience. This study aimed to answer the research question: What is the impact of robotic service acceptance on customer experience in the hotel industry and how is this effect moderated by the type of value (hedonic vs utilitarian) and reason for stay (business vs leisure)?

To answer the research question, a 2 (hedonic vs utilitarian value) x 2 (business vs leisure guest) experiment was conducted with a between-subject design, using convenience sampling. This online experiment resulted in 231 valid survey responses. Based on the reliability analysis, the internal consistency of the measurements of variables was confirmed and the hypotheses have been tested.

The results of this study confirm findings of prior research which show that the use of service robots has a positive direct effect on Customer Experience. This positive direct effect was not moderated by the Type of Value and Reason for Stay. In line with previous research, this study shows that women and older people are less likely to accept a new technology, such as service robots. Furthermore, this research confirmed that the level of Robotic Service Acceptance and Customer Experience is higher when customers are having hedonic values rather than utilitarian values.

This study contributes to the research of service robots, AI, and customer experience, which are highly relevant to advancing hospitality research. Besides, it expands the existing literature by investigating the moderating effects of Type of Value (hedonic vs utilitarian) and Reason for Stay (business vs leisure).

Finally, several limitations were observed and future research is advised to understand the acceptance of service robots and the impact of service robots on Customer Experience even better.

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10 Appendix