User Experience Study: The Service Expectation of Hotel Guests to the Utilization of AI-Based Service Robot in Full-Service Hotels

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Abstract

With the dramatic development of AI technology, the concept of robotic hotel is entering the public’s awareness. Although AI application brings in high efficiency, low labor cost and novelty, practical operation of robotic hotels still faces with challenges. This quantitative research aims at understanding the current user expectation level of AI robotic hotel and robot appliance. Based on that, it tries to make the user classification by demographic, behavioral and attitude factors. By using the refined SERVQUAL model, it gathers the expectation from five dimensions involving tangibles, reliability, responsiveness, assurance and empathy. These research objectives were realized by using survey-designed questionnaires and distributed by a snowball sampling method conducted in Beijing. After validity and reliability test, data collected from the field were analyzed by a variety of inspections. It is found that education, attitude and income level have a significant effect on the expectation to stay in the robotic hotel, which provided the basis of market position for robotic hotel operators. Through regression analysis, the model was established to identify what factors played an important part and how they worked. It is found that tangibles and responsiveness expectation significantly and positively contributed to increases in general user expectation to robotic hotels. This thesis drew up several conclusions, which would help industry players including hoteliers, AI robot suppliers better understand details of the user group in their decision-making process, as well as academic side to formulate a tailored model to evaluate the interaction between AI robots and hotel guests.

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APA

Zhang, Y., & Qi, S. (2019). User Experience Study: The Service Expectation of Hotel Guests to the Utilization of AI-Based Service Robot in Full-Service Hotels. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11588 LNCS, pp. 350–366). Springer Verlag. https://doi.org/10.1007/978-3-030-22335-9_24

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