A fuzzy-based House of Risk assessment method for manufacturers in global supply chains

Purpose - Risk management is crucial for all organizations, especially those in the global supply chain network. Failure may result in huge economic loses and damage to company reputation. Risk assessment usually involves quantitative and qualitative decisions. The purpose of this paper is to apply fuzzy logic to capture and inference qualitative decisions made in the House of Risk (HOR) assessment method. Design/methodology/approach - In the existing HOR model, aggregate risk potential (ARP) is calculated by the risk event times the risk agent value and its occurrence. However, these values are usually obtained from interviews, which may involve subjective decisions. To overcome this shortcoming, a fuzzy-based approach is proposed to calculate ARP instead of the current deterministic approach. Findings - Risk analyses are conducted in five major categories of risk sources: internal, global environment, supplier, customer and third-party logistics provider. Moreover, each category is further divided into different sub-categories. The results indicate that the fuzzy-based HOR successfully inferences the inputs of the risk event, risk agents and its occurrence, and can prioritize the risk agents in order to take proactive decisions. Practical implications - The proposed fuzzy-based HOR model can be used practically by manufacturers in the global supply chain. It provides a framework for decision makers to systematically analyze the potential risks in different categories. Originality/value - The proposed fuzzy-based HOR approach improves the traditional approach by more precise modeling of the qualitative decision-making process. It contributes to a more accurate reflection of the real situation that manufacturers are facing.