A New Integration Model to Evaluate Strategic Performance of Supply Chain

Nowadays, Supply Chain Management (SCM) is one of the most important and complex issues for automakers in the world. The main objectives of this research are to explore the factors to predict strategic performance of supply chain (SPSC) through quantitative research at IRANKHODRO (IKCO) in Iran. Based on supply chain theories, strategic performance of supply chain was predicted by information technology (IT), organizational learning (OL), and product innovation (PRI) in our research at the first time in an automotive company. The numbers of 792 questionnaires were distributed at IKCO, which produce automotive. According to SPSC as the main dependent variables, path analysis (PA) technique was used to explore casual relationships among variables using multi-regression in SPSS. The confirmatory factor analyses (CFA) were utilized based on the Maximum Likelihood (ML) to analysis normality, outliers, and composite reliability, validity and to test hypothesizes by Amos. Path analysis, measurement and structural model were analyzed in order to examine conceptual model. The results of multi-regression in path analysis and SEM were same and all hypothesizes were supported according to SPSS and SEM analyzing

Keywords:

SCM , strategic performance , IT , organizational learning , SEM