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

Abstract

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.

A Fuzzy-Based Holistic Approach for Supply Chain Risk Assessment and Aggregation Considering Risk Interdependencies

“…In this step, we proceed to identify the risk events for which consequences can affect the objectives. At the same time, more than one agent can cause the same event, and an agent can cause more than one event [22]. In this analysis, we must consider both the effect that the agent of risk could directly cause, as well as the causality that may exist between the events.…”

“…The aim of this step is to determine the ARS jl for each risk agent as it is exposed in the expression (2) with elements that have been determined in previous steps (O j , S kl , R jk ). For the basis of our proposal, we use the approaches developed by Pujawan and Geraldin [21] and Ma and Wong [22], and we include the correlations between risk events and the analysis by objective. This includes the existence and weighting of agents (causes) that can trigger several events (consequences), as well as the interrelationships between the events in a holistic way.…”

“…In this expression, we also consider the use of fuzzy logic as a support tool to achieve the assignment of the qualities to the expression (subjectivity, vague information, ambiguities) that the conventional form of calculation would not allow [22]. By means of the operators and quantifiers of this logic [50], it is possible to obtain a value of ARS jl that will be mainly determined by the probability of occurrence of the agent and will take into account the possibility that these events that are caused by the same agent to improve accuracy and reliability of the calculation.…”

“…Qualitative techniques are mostly used for risk identification and risk analysis steps. According to Ho et al [16], failure mode and effects analysis (FMEA) is one of the most widespread methods for risk analysis; however, it presents limitations in the calculation of the risk priority number (RPN), as have been discussed in several investigations [19][20][21][22][23]. Some of these limitations include:…”

“…This has been one of the main drivers for developing hybrid models. Fuzzy theory has proven to be effective and efficient in handling these types of uncertainties [14,22,[24][25][26][27].…”