An uncertain target-oriented QFD approach to service design based on service standardization with an application to bank window service

Abstract

This article proposes an uncertain target-oriented QFD approach to service standardization-based service design with an application to bank window service, based on a probabilistic interpretation of weighting information. On the one hand, the proposed approach performs computations solely based on the order-based semantics of linguistic labels and comparisons of linguistic profiles, without needing to quantify the qualitative concepts. It can thus guarantee the robustness of QFD and easy of use in practice. On the other hand, the proposed approach sets uncertain targets for customer needs (WHATs) and service standards (HOWs) by competitors’ uncertain service performance on WHATs and HOWs, and conducts satisfactory-oriented competitive analysis from the perspective of uncertain target-oriented decision analysis. Moreover, the proposed approach is applied to an empirical case study of window service design based on service standardization in the Shanghai Branch of Bank JT. The results show that the bank should pay more attention to “Service specifications”, “Service providing specifications”, and “Service evaluation and improvement standards”. Industry feedback shows that the results are consistent with service acceptance and provide valuable insights to the service standardization in the bank. Comparisons with existing studies show that our proposed approach is comparable with existing studies.

Keywords:

• Service design
• service standardization
• uncertain QFD
• target-oriented decision analysis
• bank window service

Acknowledgements

We appreciate the constructive comments and valuable suggestions from the anonymous referee and Area Editor, which helped us to significantly improve the quality of this article.

Additional information

Funding

This study was supported by the National Natural Sciences Foundation of China (NSFC) under Grant Nos. 71471063 and 71871093.

Notes on contributors

Hong-Bin Yan

Hong-Bin Yan is a Professor of Management Science and Engineering in School of Business at East China University of Science and Technology, China. He received his Ph.D. degree in Knowledge Sciences from Japan Advanced Institute of Science and Technology in Japan, and M.Sc. & B.Sc. in Management from Dalian University of Technology in China, respectively. His current research interests include service management, new product development, Kansei/sensory Engineering, technology innovation management, and decision analysis. He has published research papers in Decision Sciences, Omega-International Journal of Management Science, European Journal of Operational Research, Annals of Operations Research, International Journal of Production Research, IEEE Transactions on Engineering Management, Information Sciences, Knowledge-Based Systems, Computers & Industrial Engineering, and Expert Systems with Applications.

Xiang-Sheng Meng

Xiang-Sheng Meng is an Office Director at Shanghai Municipal Bureau of Quality and Technical Supervision. He received his M.Sc. in Management from East China Normal University and B.Sc. in Law from East China University of Political Science and Law, respectively. He has been devoted to the management of quality and technical supervision over the long-term. His current research interests include service standardization and quality management.

Tieju Ma

Tieju Ma is a Professor of Management Science and Engineering in School of Business at East China University of Science and Technology, China. He has been a visiting researcher of International Institute for Applied Systems Analysis in Austria. He received his Ph.D. degree in Knowledge Sciences from Japan Advanced Institute of Science and Technology in Japan, and M.Sc. & B.Sc. in Management from Dalian University of Technology in China, respectively. His research interests include technology innovation management and energy system analysis, especially technological dynamics modelling with uncertainties and heterogeneous agents. He has published research papers in Management Science, Omega-International Journal of Management Science, Decision Sciences, European Journal of Operation Research, Annals of Operations Research, International Journal of Production Research, Energy Economics, Energy, Systems Research and Behavioral Science, and Information Sciences.

Van-Nam Huynh

Van-Nam Huynh is a Professor of Knowledge Science at Japan Advanced Institute of Science and Technology, Japan. He received a Ph.D. in Mathematics (1999) from the Institute of Information Technology, Vietnam Academy of Science and Technology, and a “Habilitation à Diriger des Recherches” (2012) at Université de Technologie de Compiègne, France. He was a post-doctoral fellow (2001--2002) awarded by Inoue Foundation for Science at Japan Advanced Institute of Science and Technology (JAIST). His research interests include decision theories, data mining and machine learning, computing and reasoning with words, information fusion, Kansei information processing and application. Currently he is an Associate Editor of the International Journal of Approximate Reasoning and an Associate Editor of the International Journal of Knowledge and Systems Science. He has published research papers in IEEE Transactions on Engineering Management, IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, IEEE Transactions on Fuzzy Systems, International Journal of Approximate Reasoning, Omega-International Journal of Management Science, Decision Sciences, Annals of Operations Research, International Journal of Production Research, Knowledge-Based Systems, Fuzzy Optimization & Decision Making, and Information Sciences.