Supply chains contain the management of all processes and information from raw materials to finished products. Therefore, it is getting important to deal with holistic approach and performance measurement for supply chains. SCOR model is one of the most common approaches that used for measuring the performance of supply chains. In this study, two different performance measurement systems that base on SCOR model is proposed. According to the first proposed approach, different clusters are obtained by clustering analysis in order to evaluate the performance of the enterprises with similar characteristics. The k-means approach is used to implement the clustering analysis. In the second approach, the fuzzy entropy based alpha level is applied for weighting attributes and performance evaluation is performed for the SCOR model accordingly. In the case study, dataset with 17 different attributes are obtained from 54 different enterprises and the results of the fundamental SCOR model and the two proposed approaches are investigated.