SUPPLY CHAIN PERFORMANCE EVALUATION USING THE SCOR® MODEL AND FUZZY-TOPSIS

Abstract

The monitoring of SC development offers several benefits, including the evaluation of progress, identification of achievements, enhancement of understanding of crucial business processes, and identification of potential future challenges. This study introduces an innovative approach to evaluate the efficiency of a supply chain (SC) by using the performance metrics of the SCOR® model and employing the fuzzy-TOPSIS technique. The strategy provided in this study involves evaluating and comparing the overall performance of 10 different supply chain alternatives in a demonstration scenario. This study introduces a novel approach that combines the SCOR model with fuzzy TOPSIS to facilitate the assessment of supply chain performance. The Supply Chain Operations Reference (SCOR) model serves as a benchmarking tool, facilitating the comparison of a firm's performance with other businesses that are organized within the supply chain. The proposed approach offers numerous advantages over alternative approaches. These advantages include the capability to conduct benchmarking against other supply chains (SCs), the fuzzy TOPSIS method requiring minimal judgments for parameterization, thereby enhancing the agility of the decision-making process, the ability to evaluate multiple alternatives simultaneously, and the elimination of the ranking reversal issue. The fuzzy TOPSIS method enables the measurement of metrics and probability of alternatives using language phrases that are described by fuzzy numbers. The potential for evaluating numerous alternatives and measurements concurrently is boundless, distinguishing it from other methodologies such as AHP and TOPSIS. The proposed method was implemented in MATLAB and subsequently applied to an illustrative scenario. These findings demonstrate the appropriateness of this concept.