Evaluation of a Multi-robot Cafe Based on Service Quality Dimensions

  • Takeshi MoritaEmail author
  • Naho Kashiwagi
  • Ayanori Yorozu
  • Hideo Suzuki
  • Takahira Yamaguchi


While AI applications are popular in many domains, they should work harmoniously with domain exerts and end users. Furthermore, to develop such harmonious AI applications, we need agile AI platforms for not only developers, but also domain experts. Currently, we have developed PRactical INTElligent aPplicationS (PRINTEPS), which is a user-centric platform to develop integrated intelligent applications. This paper reports on a multi-robot cafe as a practical application of PRINTEPS and evaluates its service quality at a university festival. It is not clear if robotic services are perceived as attractive and/or valuable, and how the concept of robotic services could lead to customer satisfaction. Therefore, the evaluation of the quality of such services is necessary to identify the key factors that could contribute to improving customer satisfaction. The purpose of this research is to identify key factors in improving customer satisfaction in robotic services by evaluating the service quality of the multi-robot cafe. We designed questionnaire items based on SERVQUAL which is one of the service quality evaluation measurement methods and conducted a questionnaire survey at a multi-robot cafe held at a university festival. From the collected data, we modeled and evaluated the relationship between service quality and customer satisfaction to identify key factors in robotic services using a Bayesian network. In addition, the experiment confirms the usefulness of PRINTEPS.


PRINTEPS multi-robot cafe service quality SERVQUAL 



We are grateful to Prof. Hideo Saito, Dr. Yuko Ozasa, and Mr. Toshiki Kikuchi for implementing the image processing modules, to Mr. Kodai Nakamura for implementing the knowledge modules, to Prof. Yukiko Nakano, Dr. Fumio Nihei, and Mr. Jie Zeng for implementing the spoken dialog system, and to Prof. Masaki Takahashi, Mr. Jun Kurosu, and Mr. Yosuke Kawasaki for implementing the motion management modules. This study was supported by the Project of “A Framework PRINTEPS to Develop Practical Artificial Intelligence,” (JPMJCR14E3) the Core Research for Evolutional Science and Technology (CREST) of the Japan Science and Technology Agency (JST).


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Copyright information

© Springer Japan KK, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Keio UniversityYokohamaJapan

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