Abstract
Understanding and assessing risk are fundamental to success in Supply Chain Management. This paper develops and demonstrates a fuzzy risk assessment framework to effectively assess supply risk. The sources of risk were extracted based on industry expert views and prior research. A fuzzy inference engine which embeds human expert knowledge expressed through natural language is used. The case of a process industry showed that this method could capture imprecise perceptions about risk factors and quantify them effectively. The framework will be beneficial to researchers and practicing managers in identification of risk and improvement of reliability in the supply chain.
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