Interpretive structural modeling of supply chain risks

Purpose - The aim of this paper is the structural analysis of potential supply chain risks. It will demonstrate how interpretive structural modeling (ISM) supports risk managers in identifying and understanding interdependencies among supply chain risks on different levels (e.g. 3PL, first-tier supp...

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Veröffentlicht in:International journal of physical distribution & logistics management 2011-01, Vol.41 (9), p.839-859
Hauptverfasser: Pfohl, Hans-Christian, Gallus, Philipp, Thomas, David
Format: Artikel
Sprache:eng
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Zusammenfassung:Purpose - The aim of this paper is the structural analysis of potential supply chain risks. It will demonstrate how interpretive structural modeling (ISM) supports risk managers in identifying and understanding interdependencies among supply chain risks on different levels (e.g. 3PL, first-tier supplier, focal company, etc.). Interdependencies among risks will be derived and structured into a hierarchy in order to derive subsystems of interdependent elements with corresponding driving power and dependency.Design methodology approach - ISM was used to identify inter-relationships among supply chain risks and to classify the risks according to their driving and dependence power. The theoretical findings of the modeling and the applicability for practical use has been tested in two case studies with two German industry and trade companies.Findings - ISM was proven as a useful methodology to structure supply chain risks in an easy and distributed approach that can also be carried out in a step-by-step process on several manufacturing stages. The input to the algorithm has to be well-defined to give the user an exact understanding of all risks that have to be assessed, i.e. the better the input to ISM is prepared the better the outcome and representation will be. Finally, when applying the method, a moderated process proved to be more reliable than an assessment based on paper questionnaires only.Originality value - This model's insight would assist supply chain (risk) managers in the effective allocation of risk management resources in the subsequent risk management phases.
ISSN:0960-0035
1758-664X
DOI:10.1108/09600031111175816