AUTHOR=Zheng Jin , Li Yong-Hai , Fan Zhi-Ping 

TITLE=Demand-driven NEV supplier selection: An integrated method based on ontology–QFD–CBR

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 10 - 2022

YEAR=2023

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.958885

DOI=10.3389/fenrg.2022.958885

ISSN=2296-598X

ABSTRACT=With the rapid development of new energy vehicle (NEV), the market competition of NEV industry is becoming more and more fierce. Selecting a right supplier has become a critical decision for NEV manufacturer. Therefore, based on the user’s demand information, how to select a suitable NEV supplier to support the NEV manufacturer’s management decision is a noteworthy research problem. The purpose of this paper is to develop an integrated method for demand-driven NEV supplier selection based on ontology - quality function deployment (QFD) - case-based reasoning (CBR). The method is composed of three parts: 1) construction of domain ontology of NEV component supplier selection criteria based on text information mining; 2) extraction of demand attributes and determination of their weight based on latent dirichlet allocation (LDA) and Kano model, as well as determination of expected attributes and their weights based on QFD; 3) selection of NEV component supplier based on CBR. To illustrate the use of the proposed method, an empirical study on the supplier selection of XP NEV manufacturer is given. This method is helpful to select the most suitable component supplier for NEV manufacturers and relevant decision makers.