Modelling Supply Chain Resilience and Organisational Performance for Selected Small and Medium Scale Enterprises

Abstract

The ability of a supply chain to prepare for, resist, and recover from disruption is defined by its level of resilience. In recent times, the focus on the improvement of supply chain resilience has been characterised by subjectivity and vagueness of the attributes of the organisations. While small and medium enterprises (SMEs) contribute substantial part of the GDP in many nations, research has been sparse on their supply chain resilience. This study is aimed at bridging the research gap by developing a model for measuring supply chain resilience of SMEs using the Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and Fuzzy Inference System.

This study was carried out in three phases. Identification of critical attributes of supply chain resilience of SMEs was done in the first phase using Fuzzy-Analytic Hierarchy Process. In the second phase, a fuzzy inference system for measuring supply chain resilience levels was developed. Critical attributes were divided into 3 broad categories of preparedness, resistance, and response and recovery attributes which serve as inputs into the resilience fuzzy inference system. Data from seven (7) SMEs in the agricultural, water packaging, foods, and fabrication sectors were used to validate the system. The third phase of the study involved the identification of the relationship between supply chain resilience of the SMEs and organisational performance.

Seven attributes, financial capability, agility, recoverability, flexibility, redundancy, security, and awareness with percentage contribution of 17.0%, 13.6%, 10.8%, 10.5%, 9.9%, 9.1%, and 8.2% respectively were found to be critical to achieving more than 75% resilience of the supply chain for the SMEs. The resilience fuzzy inference system developed gave the supply chain resilience index of the selected SMEs. Resilience investments can be considered as sunk costs with benefits accruing at later dates.