Mitigating environmental and density risk in global sourcing

In: International journal of physical distribution and logistics management, Band 39, Heft 10, S. 861-883

Abstract

PurposeThe purpose of the paper is to provide a conceptual foundation to enhance the body of knowledge related to supplier selection in light of global supply chain disruptions and risk.Design/methodology/approachThe proposed tool is based on a multi‐criteria optimization framework, which will enable the user to gain a better understanding of how the consideration of each of these risk measures will affect the recommended solution/supply base. The model serves as a complement to existing supplier selection models by incorporating regional risks associated with potential suppliers' locations and density risks based on great circle distance measures.FindingsThe paper demonstrated the proposed model by using the great circle distance measure to calculate the density risk and two secondary data sources to capture environmental risk. One measure captures a variety of environmental issues such as political, legal, security, fiscal, labor, and regulatory issues. The other measure captures the historical effects of weather on dollar and human losses in each country of the world, which represents the potential for severe weather events and the country's ability to react to these events.Research limitations/implicationsAlthough the paper does not consider all possible risks, it augments prior research through the development of a decision support tool that offers supply risk mitigation when sourcing globally. Specifically, the tool allows for the analysis and mitigation of two key global risk measures, environmental risk and density risk, when selecting suppliers for mission‐critical parts. The model is able to support various sourcing strategies such as sole, multiple and cross sourcing and can be used in conjunction with other disruption mitigation strategies such as supply redundancy.Practical implicationsGlobal sourcing has provided significant performance enhancements, but has put firms in a vulnerable position relative to the potential devastating effects of supply disruptions. While supply managers are cognizant of the risks associated with global sourcing, limited knowledge and tools are available to allow them to mitigate these risks. Although it would need to be adapted to the nuances of company supply chains, it is believed that the tool provides value to managerial decision making relative to the sourcing of mission critical parts/products.Originality/valuePrior work in this area has not adequately incorporated contemporary issues and risks in global sourcing. The paper augments prior research through the development of a multi‐objective decision support model for strategic supplier selection that is focused on two important contemporary factors: environmental risk and density risk. The proposed model captures important interdependent relationships between these two factors that have not been considered in prior selection models.