Method for determining the importance of customer requirements based on preference consensus and trust relations

In view of the shortcomings of the evaluation method and ignoring the weights of experts in the traditional approach of customer requirements (CRs) importance determination, this study proposes an improved method for deciding the importance of CRs based on social network analysis (SNA) and preference consensus. Firstly, the hesitant fuzzy linguist preference relation (HFLPR) is used to represent the experts’ preference evaluations between CRs, and the consistencies of HFLPR matrices are measured. Secondly, SNA is introduced to describe the trust relationships among experts, and the comprehensive weights of experts are calculated in combination with the consensus levels of the preference evaluations. Finally, according to the total collective performance scores of HFLPR matrices, the importance of CRs is ranked. To demonstrate the feasibility and effectiveness of the proposed method, an example regarding the product development of fully automatic washing machines is provided.