Published Jun 24, 2019



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Jenifer Ramos-Ríos, MSc http://orcid.org/0000-0003-0482-4421

Diego Fernando Manotas-Duque, PhD http://orcid.org/0000-0003-0148-9840

Juan Carlos Osorio-Gómez, PhD https://orcid.org/0000-0001-5625-5609

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Abstract

Objective: This study aims to propose a methodology that identifies and prioritizes the operational risk factors in a supply chain (SC) to provide a tool according to the process-based SC approach that is useful for risk assessment throughout the SC. Materials and methods: Risk identification was conducted by a scenario analysis, which linked the risk factors with the standard key performance indicators (KPIs) of the processes and logistics activities proposed by the supply chain operational reference model (SCORM o SCOR). These influence relationships were quantified using a proposed scale, and then, the risk factors were prioritized by the definition of their influence levels. This approach was applied to a real SC. Results and discussion: Twenty risk factors were clearly and effectively identified, analyzed and prioritized, and priority was given to those with the highest influence level, which can be understood as the risk factors that have a larger capacity to negatively affect SC performance. Conclusions: The methodology allows the identification of the most influential risk factors in a SC, and as it is based on a standard model, it fosters a collaborative analysis among its echelons. The main contributions of this paper are the risk identification by means of the KPIs of the SCOR model and the measurement of their influence levels, which is a new and useful feature for risk prioritization.

Keywords

Riesgo en la cadena de suministro, Riesgo operacional, Modelo SCOR, Nivel de influencia de factor de riesgoSupply chain risk, Operational risk, SCOR Model, Risk factor influence level

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How to Cite
Ramos-Ríos, J., Manotas-Duque, D. F., & Osorio-Gómez, J. C. (2019). Operational supply chain risk identification and prioritization from SCOR model. Ingenieria Y Universidad, 23(1). https://doi.org/10.11144/Javeriana.iyu23-1.oscr
Section
Industrial and systems engineering

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