Assessing Supply Chain Performance through Applying the SCOR Model

Abstract

In recent years, supply chain performance measurement has received much attention from researchers and practitioners. Effective supply chain performance through supply chain antecedents such as business analytics has become a potentially valuable way of securing competitive advantage and improving supply chain performance. This study addressed the lack of the empirical studies by developing a comprehensive model to examine the effect of business analytics on supply chain performance. A quantitative methodology using a cross-sectional survey method was used to investigate the relationship between variables. Data were collected from automotive companies in Iran. The relationships between variables were examined using structural equation modelling (SEM) technique and partial least squares (PLS) software was used. The results revealed there is a significant positive relationship between business analytics and supply chain performance. The study combined resource- based theory, resource dependence theories to develop a new theoretical framework to demonstrate the importance of businesses analytics; in improving supply chain performance.