An investment evaluation of supply chain RFID technologies: A group decision-making model with multiple information sources

Selection of radio frequency identification (RFID) technology is important to improving supply chain competitiveness. The objective of this paper is to develop a group decision-making model using fuzzy multiple attributes analysis to evaluate the suitability of supply chain RFID technology. Since numerous attributes have been considered in evaluating the RFID technology suitability, most information available in this stage exhibits imprecise, subjective and vague. Fuzzy set theory appears as an essential tool to provide a decision framework for modeling imprecision and vagueness inherent in the RFID technology selection process. In this paper, a fuzzy multiple attributes group decision-making algorithm using the principles of fusion of fuzzy information, 2-tuple linguistic representation model, and maximum entropy ordered weighted averaging operator is developed. The proposed method is apt to manage evaluation information assessed using both linguistic and numerical scales in group decision making problem with multiple information sources. The aggregation process is based on the unification of fuzzy information by means of fuzzy sets on a basic linguistic term set. Then, the unified information is transformed into linguistic 2-tuple in a way to rectify the problem of loss information of other fuzzy linguistic approaches. The proposed method can facilitate the complex RFID technology selection process and consolidate efforts to enhance group decision-making process. Additionally, this study presents an example using a case study to illustrate the availability of the proposed method and its advantages.