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An Optimization Design Method of Express Delivery Service Based on Quantitative Kano Model and Fuzzy QFD Model
Author(s) -
Hongmei Shan,
Xinmeng Fan,
Siyu Long,
Xuejing Yang,
Shuhan Yang
Publication year - 2022
Publication title -
discrete dynamics in nature and society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 39
eISSN - 1607-887X
pISSN - 1026-0226
DOI - 10.1155/2022/5945908
Subject(s) - quality function deployment , computer science , kano model , service quality , service (business) , fuzzy logic , house of quality , service design , service delivery framework , customer satisfaction , service level objective , process management , mass customization , personalization , risk analysis (engineering) , business , marketing , new product development , customer retention , artificial intelligence , world wide web
Service quality is the soul of express enterprises forever. It is of great practical significance for winning customer satisfaction, improving the market competition, and realizing sustainable performance. Unlike tangible products, express delivery service has the characteristics of intangibility, heterogeneity, indivisibility, and instability. While customer demands are complex and changeable and unpredictable, incorporating complex customer requirements into service design has been a growing interest of researchers and practitioners. This paper proposed an optimization design framework based on the quantitative Kano (QKNO) and the fuzzy quality function deployment (FQFD) to effectively achieve the best matching of enterprise service elements under the uncertainty and imprecise judgment information. An empirical study is conducted to verify the feasibility of the proposed approach. The results show that the framework could guide the express company to prioritize the enterprise service elements to maximize customer satisfaction and provide a reasonable budget allocation scheme to set the best resources match. It has theoretical and practical meaning for express enterprises to implement customization service strategy and improve service quality under the limited budget, which could be further extended to other service industries to make optimization decisions.

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