A fuzzy MCDM model for knowledge service vendor evaluation and selection
Knowledge service vendor selection is an important task for the decision makers of the company in the knowledge economics. The purpose of this study is to investigate a fuzzy multiple criteria decision-making method for evaluating and selecting knowledge service vendor. In the paper, the multiple criteria should consider in the evaluation and selection process is presented. Then, a fuzzy MCDM approach based on fuzzy TOPSIS is proposed. The linguistic evaluation information given by the decision makers are transformed into the form of triangular fuzzy numbers. Based on the extended TOPSIS, the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS) are determined. The relative closeness of each alternatives to the FPIS and FNIS is calculated to determine the ranking order of all alternatives. The evaluation results of the knowledge service providers can be obtained through the proposed fuzzy method and then the proper vendor can be selected. Additionally, an illustrating example is given to show the feasibility and practicability of the proposed approach.