A fuzzy ARAS method for supply chain management performance measurement in SMEs under uncertainty

Abstract

In this study, a novel framework is presented to assess supply chain management performance measurement (SCMPM) of small-medium sized enterprises (SMEs) under uncertainty by additive ratio assessment (ARAS) method that developed in fuzzy environment. Three decision phases with different levels of uncertainty in the supply chains were included in the evaluation process. More specifically, forty-three criteria were proposed to evaluate processes in three decision levels; strategic, tactical and operational. Also, the proposed criteria were assessed in terms of being financial, non-financial, qualitative and quantitative. A demonstration of the application of this methodology in a real case is presented accordingly. The results indicate that the quality of delivering goods, damage rates, rate of returning goods and full and on-time delivery, obtained the highest priority and A3 was chosen to be the best alternative in terms of performance