Discriminant Analysis of Supply Chain Stability Clusters Based on Lean Tools

Today, pure tools for creating and improving customer value are considered in the waste elimination process. Elimination of fundamental losses is considered to achieve economic, environmental and social sustainability. Accordingly, the purpose of this study is to discriminant analysis of supply chain stability clusters based on lean tools. In this study, data collection tools are two types of questionnaires designed to assess the stability of supply chain sustainability and assessment of lean manufacturing tools in small and medium industries of East Azerbaijan Province. To determine the validity of the questionnaires, construct validity based on factor analysis and Cronbach's alpha coefficient were used to determine their reliability. The statistical population of this study is all the small and medium industries in East Azerbaijan Province. To analyze the data, the analysis of the cluster analysis and audit analysis has been used. The results show that based on cluster analysis, firms can be grouped into three clusters, one of which is not known as stable cluster because of low scores. The results of discriminant analysis showed an audit function that shows the contribution of each of the lean tools in the separation between sustainability clusters and classified in two groups: complete and stable sustainability. It should be noted that the accuracy of this function is 98.1%.