A contingency framework for analysing supply chain performance

Abstract

The activities, processes and relationships that fall under the supply chain label are central to industrial modernity. As supply chains are now competing against supply chains, it is vital that they are managed effectively so as to enhance their performance. An examination of the literature on supply chain analysis reveals that it can be viewed from two separate perspectives. The first is the decisional perspective that prescribes to the premise that different decisional variables or factors lead to different performance levels. The second perspective centers on the fact that there is no one best way to manage all supply chains and different supply chains have to be managed differently. The literature also reveals that several different methodologies are employed in looking at those issues and their effects on supply chain performance. Because of the multiple issues involved and the lack of a common methodology in supply chain analysis, the literature paints an almost confusing picture of the subject. Thus, the purpose of this study is to investigate and develop a general framework that could be used as a platform to investigate or analyze the performance of supply chains whilst at the same time incorporating the characteristics of the two perspectives of supply chain analysis that was mentioned earlier. In order to achieve this, an extensive literature review and case study analysis was done. This leads to the coining of new concepts like the supply chain structure, which is made up of the physical variables, relationship variables and spatial variables, and contextual variables for supply chains. These new concepts formed the elements of the proposed contingency framework for supply chain analysis. This framework is based on two guiding principles. One is that different supply chain structures will give rise to different supply chain performances and the other is that there is an interaction between the supply chain structure variables and the contingent variables, which in turn will affect supply chain performance. A purely conceptual framework, though useful in its own right, would have been of limited use especially to practitioners. Thus the applicability of the contingency framework in analyzing supply chains is demonstrated via simulation. The simulation results confirm the hypothesis that different supply chain structures exhibited different performances. The proposed contingency framework could serve as a theoretical base for further research into supply chain analysis, which would give more insight into the dynamics of a supply chain.