Supply network design: Risk-averse or risk-neutral?

• We focus on supply disruptions that result in producing tainted materials.
• We design a supply network to prevent risk of sending tainted material to customer.
• Statistical analysis was conducted to identify factors for predicting facility selection.
• We consider new idea of facility inspection as a recent FDA requirement in some SC.
• Presented model enables practitioners to select the most qualified suppliers.

In this paper, we investigate a supply network design in supply chain with unreliable supply with application in the pharmaceutical industry. We consider two types of decision making policies: (1) a risk-neutral decision-making policy that is based on a cost-minimization approach and (2) a risk-averse policy wherein, rather than selecting facilities and identifying the pertinent supplier–consumer assignments that minimize the expected cost, the decision-maker uses a Conditional Value-at-Risk (CVaR) approach to measure and quantify risk and to define what comprises a worst-case scenario. The CVaR methodology allows the decision-maker to specify to what extent worst-case scenarios should be avoided and the corresponding costs associated with such a policy. After introducing the underlying optimization models, we present computational analysis and statistical analysis to compare the results of the risk-averse and risk-neutral policies. In addition, we provide several managerial insights.