Prioritizing factors influencing the performance of a supply chain system using hybrid structural interaction matrix

Abstract

Ascertaining and prioritizing the various factors that can influence the performance of a supply chain system is vital towards creating measures that are tailored towards controlling these factors, in order to ensure a sustainable supply chain. This research subject matter has been solved in the literature using multi-criteria decision making techniques, whose prioritization solutions are generated using experts opinions, which are subjective, thereby decision obtained could be prone to biases. In light of this, this study present an Hierarchical Structural Interaction Matrix (HSIM) approach, whose prioritization computation is premised on the theory of subordination derived via systems thinking, to prioritize various factors influencing the performance of a supply chain system. In order to achieve this, firstly, all the factors that could influence the performance of a supply chain system were identified from the literature. Thereafter, a Binary Interaction Matrix, which unveil the arrays of subordinations that exist amidst a number of the identified factors was developed. The result of this exercise was thereafter numerically analyzed using appropriate mathematical equations to determine the intensity rating score of each supply chain performance factor. Furthermore, Pareto analysis was conducted using the latter results, to unveil the vital few factors that could influence the performance of a supply chain system used in an organization. The result of the study unveiled that supply chain performance of an organization can be exponentially improved, if supply chain managers can focus and concentrate their management efforts more on 11 critical factors obtained from the prioritization analyses. With this approach, supply chain manager would obviously reduce errors in the ratings of the supply chain performance-driven factors.