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

Abstract

With the rapid development of new energy vehicles (NEVs), the market competition in the NEV industry is becoming increasingly fierce. Selecting the right supplier has become a critical aspect for NEV manufacturers. Therefore, based on the user’s demand information, selecting a suitable NEV supplier to support the NEV manufacturer’s management decision is a noteworthy research problem. The purpose of this study 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; and 3) selection of an NEV component supplier based on CBR. To illustrate the use of the proposed method, an empirical study on the supplier selection of the XP NEV manufacturer is given. This method is helpful in selecting the most suitable component supplier for NEV manufacturers and relevant decision-makers.