Models for supplier selection and risk mitigation: a holistic approach

Abstract

According to a study conducted by PwC and the Business Continuity Institute in 2013, 75% of companies experience at least one major supply chain disruption a year and majority of the disruptions were caused by supply-related problems. With an increasing emphasis on upstream risk, risk management in supplier selection has become a critical issue faced by companies. Although previous studies proposed different methods and tools for effective and efficient supplier selection, only few approaches have attempted to incorporate risk mitigation strategies in supplier selection decisions. Our study aims to fill this gap by considering a wide range of quantitative and qualitative risk factors in supplier selection and evaluates the efficacy of alternative risk mitigation strategies in this context. Moreover, we suggest that both upstream and downstream strategies should be utilised simultaneously rather than relying on a single type of strategy. We further suggest that it is critical to align upstream and downstream risk mitigation strategies to reduce risk. We employ multi-objective optimization-based simulation in developing a decision model and consider data from an automotive parts manufacturer to demonstrate the application of our approach.

Keywords:

• supply chain risk management
• supplier selection
• risk-mitigating strategy
• multi-objective optimization
• mathematical models

Notes

1. Risk drivers: factors including events and conditions that could increase the risk level in a supply chain (Jüttner, Peck, and Christopher 2003; Chopra and Sodhi 2004).

2. To determine the number of replications, we employ a simple graphical approach suggested by Robinson (2014). As more replications are performed, the cumulative mean of output should show minimal variability, and there should be no upward or downward trend. Our results show that after the 20th replication, the cumulative means are very stable.