Abstract
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.









Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Choi, D., Ha, J., Jung, M., Park, W., & Park, H. (2015). Development of robot scenario script language and tool for non-expert. Journal of Automation and Control Engineering, 3(6), 498–502.
Cronin, J. J., & Taylor, S. A. (1994). SERVPERF versus SERVQUAL: reconciling performance-based and perceptions-minus-expectations measurement of service quality. Journal of Marketing, 58(1), 125–131.
Datta, C., Jayawardena, C., Kuo, I. H., & MacDonald, B. A. (2012). RoboStudio—A visual programming environment for rapid authoring and customization of complex services on a personal service robot. Madrid: IROS.
DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60–95. https://doi.org/10.1287/isre.3.1.60.
Eksiri, A., & Kimura, T. (2015). Restaurant service robots development in Thailand and their real environment evaluation. Journal of Robotics and Mechatronics, 27, 91–102.
Hertzberg, J., Zhang, J., Zhang, L., Rockel, S., Neumann, B., Lehmann, J., et al. (2014). The race project. KI-Künstliche Intelligenz, 28(4), 297–304.
Kim, M., Lee, H., Lee, J., Kwak, S.S., & Joo, Y. (2015). Effectiveness and service quality of robot museum through visitors experience: A case study of RoboLife Museum in South Korea. In 2015 International Symposium on Micro-NanoMechatronics and Human Science (MHS) (pp 1–5). https://doi.org/10.1109/MHS.2015.7438289
Kim, Y., & Seok Lee, H. (2014). Quality, perceived usefulness, user satisfaction, and intention to use: An empirical study of ubiquitous personal robot service. Asian Social Science, 10, 1–16. https://doi.org/10.5539/ass.v10n11p1.
Ladhari, R. (2009). A review of twenty years of SERVQUAL research. International Journal of Quality and Service Sciences, 1, 172–198. https://doi.org/10.1108/17566690910971445.
Mei Lau, M., Cheung, R., Y C Lam, A., & Ting Chu, Y. (2013). Measuring service quality in the banking industry: A Hong Kong based study. Contemporary Management Research, 9(3), 263–282. https://doi.org/10.7903/cmr.11060.
Morita, T., Nakamura, K., Komatsushiro, H., & Yamaguchi, T. (2018). PRINTEPS: An integrated intelligent application development platform based on stream reasoning and ROS. The Review of Socionetwork Strategies, 12(1), 71–96. https://doi.org/10.1007/s12626-018-0020-y.
Parasuraman, A., Zeithaml, V., & Berry, L. (1988). SERVQUAL: A multi-item scale for measuring consumer perceptions of the service quality. Journal of Retailing, 64(1), 12–40.
Pot, E., Monceaux, J., Gelin, R., & Maisonnier, B. (2009). Choregraphe: a graphical tool for humanoid robot programming. In RO-MAN 2009—The 18th IEEE International Symposium on Robot and Human Interactive Communication, IEEE (pp 46–51). https://doi.org/10.1109/ROMAN.2009.5326209.
Reichheld, F. F., & Teal, T. (1996). The loyalty effect: The hidden force behind growth, profits, and lasting value/Frederick F. Reichheld with Thomas Teal. Harvard: Harvard Business School Press Boston.
Tenorth, M., & Beetz, M. (2013). KnowRob: A knowledge processing infrastructure for cognition-enabled robots. International Journal of Robotics Research, 32(5), 566–590. https://doi.org/10.1177/0278364913481635.
Waibel, M., Beetz, M., D’Andrea, R., Janssen, R., Tenorth, M., Civera, J., et al. (2011). RoboEarth—A World Wide Web for robots. Robotics & Automation Magazine, 18(2), 69–82.
Walch, M., & Karagiannis, D. (2019). How to connect design thinking and cyber-physical systems: the s*IoT conceptual modelling approach. In 52nd Hawaii International Conference on System Sciences, HICSS 2019. http://eprints.cs.univie.ac.at/5848/. Accessed 26 Aug 2019.
Yamaguchi, T. (2015). A Platform PRINTEPS to Develop Practical Intelligent Applications. In Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers (pp 919–920). Osaka, Japan: ACM. https://doi.org/10.1145/2800835.2815383.
Zander, S., Heppner, G., Neugschwandtner, G., Awad, R., Essinger, M., & Ahmed, N. (2016). A Model-Driven Engineering Approach for ROS using Ontological Semantics. CoRR cs. RO. https://arxiv.org/abs/1601.03998.
Acknowledgements
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).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Morita, T., Kashiwagi, N., Yorozu, A. et al. Evaluation of a Multi-robot Cafe Based on Service Quality Dimensions. Rev Socionetwork Strat 14, 55–76 (2020). https://doi.org/10.1007/s12626-019-00049-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12626-019-00049-x