Purpose: This paper aims to identify various information risks that could impact a supply chain, and develops a conceptual framework to quantify and mitigate them. Design/methodology/approach: Graph theory has been used to quantify information risks while interpretive structural modelling (ISM) is employed to understand the interrelationships among the enablers of information risks mitigation. Findings: The research presents a classification of the enablers of information risks mitigation according to their driving power and dependence. It also presents a risk index to quantify information risks. The research suggests that management should focus on improving the high driving power enabler variables. Practical implications: The proposed risk index and the hierarchy-based model would help to develop suitable strategies to manage information risks in supply chains. Originality/value: The major contribution of this paper lies in the development of a framework to quantify information risks and a hierarchy based model for their mitigation in context of supply chains. © Emerald Group Publishing Limited.
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