Quantifying reputation risk using a fuzzy cognitive map : a case of a pharmaceutical supply chain

Purpose: Reputation risk onsets in focal firm whenever any entity of its supply chain (SC) faces risk-crisis event. A framework for modeling and predicting holistic SC reputation risk is proposed by integrating operational risk (OR) drivers originating from upstream and downstream partners and focal firm. A fuzzy cognitive map (FCM) is then developed to predict and quantify Pharmaceutical SC reputation risk. Design/methodology/approach: Using event study methodology, SC reputation risk framework with 13 input OR drivers was developed. Based on pharmaceutical supply chain experts’ opinion, the correlation between reputation risk and its input drivers was estimated. The developed FCM tool was validated using nine real-life instances. A series of “what-if” scenario analyses were performed to demonstrate effectiveness of proactive and reactive mitigation strategies against reputation risk. Findings: Quality and unethical governance risks significantly impacted reputation in Pharmaceutical SC and a firm should prefer “risk avoidance” against these risks. The upstream risks significantly affect reputation in a Pharmaceutical SC as compared to the downstream risks. Proactive mitigation strategies and assertive crisis communication are suggested for upstream risks while diminishment/ bolstering/rebuilding reactive crisis communication is recommended for downstream risks. Originality/value: Reputation risk is often overlooked in SC literature. This work develops a model to quantify the reputation risk considering the indirect consequences of the ORs that originates at any point in a SC. The proposed FCM tool aids SC manager to focus on higher attribution risk events and devise an optimal combination of proactive and reactive mitigation strategies to avoid/minimize the economic loss due to reputation crisis.