The design of a decision support system for supply chain risk management

Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, June 2007. === Includes bibliographical references (p. 97-98). === Where can things go wrong? This deceptively simple question has fascinated mankind since time immemorial. The question in fact forms the basi...

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Main Author: Deshmukh, Vinay (Vinay D.)
Other Authors: David Simchi-Levi.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2008
Subjects:
Online Access:http://hdl.handle.net/1721.1/42354
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spelling ndltd-MIT-oai-dspace.mit.edu-1721.1-423542019-05-02T16:00:42Z The design of a decision support system for supply chain risk management Decision support system for supply chain risk management Deshmukh, Vinay (Vinay D.) David Simchi-Levi. System Design and Management Program. System Design and Management Program. System Design and Management Program. Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, June 2007. Includes bibliographical references (p. 97-98). Where can things go wrong? This deceptively simple question has fascinated mankind since time immemorial. The question in fact forms the basis of risk management. The focus of this thesis is the risk management of supply chains. Any factor that is likely to disrupt the procurement, production, or delivery of a good or a service constitutes a supply chain risk. As several case studies from around the world indicate [4], disruptions to an enterprise's supply chain could be catastrophic to business, human safety, market competitiveness, and even national and international economies. It is therefore imperative that an a priori assessment of the factors that pose a risk to the supply chain be conducted and contingency plans developed at strategic, tactical, and operational levels to monitor and mitigate those risks. This thesis will identify all major risks that are likely to disrupt a supply chain; identify the data needed to continuously monitor each risk; suggest a synthesized framework for managing supply chain risks; propose different models to quantify risks and asses their consequences; and suggest guidelines for model use. Further, it will present a case study based on the models developed and propose a decision support system based on these models and necessary data. This work will help enterprises develop risk management plans at the strategic, tactical and operational levels, along various time horizons, and be able to execute them when supply chain risks are encountered. The target audience for this thesis includes a broad spectrum of supply chain professionals, consultants, supervisors, top executives, risk professionals, managers, software entrepreneurs, academicians, and students. by Vinay Deshmukh. S.M. 2008-09-03T15:25:34Z 2008-09-03T15:25:34Z 2006 2007 Thesis http://hdl.handle.net/1721.1/42354 234191842 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 98 p. application/pdf Massachusetts Institute of Technology
collection NDLTD
language English
format Others
sources NDLTD
topic System Design and Management Program.
spellingShingle System Design and Management Program.
Deshmukh, Vinay (Vinay D.)
The design of a decision support system for supply chain risk management
description Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, June 2007. === Includes bibliographical references (p. 97-98). === Where can things go wrong? This deceptively simple question has fascinated mankind since time immemorial. The question in fact forms the basis of risk management. The focus of this thesis is the risk management of supply chains. Any factor that is likely to disrupt the procurement, production, or delivery of a good or a service constitutes a supply chain risk. As several case studies from around the world indicate [4], disruptions to an enterprise's supply chain could be catastrophic to business, human safety, market competitiveness, and even national and international economies. It is therefore imperative that an a priori assessment of the factors that pose a risk to the supply chain be conducted and contingency plans developed at strategic, tactical, and operational levels to monitor and mitigate those risks. This thesis will identify all major risks that are likely to disrupt a supply chain; identify the data needed to continuously monitor each risk; suggest a synthesized framework for managing supply chain risks; propose different models to quantify risks and asses their consequences; and suggest guidelines for model use. Further, it will present a case study based on the models developed and propose a decision support system based on these models and necessary data. This work will help enterprises develop risk management plans at the strategic, tactical and operational levels, along various time horizons, and be able to execute them when supply chain risks are encountered. The target audience for this thesis includes a broad spectrum of supply chain professionals, consultants, supervisors, top executives, risk professionals, managers, software entrepreneurs, academicians, and students. === by Vinay Deshmukh. === S.M.
author2 David Simchi-Levi.
author_facet David Simchi-Levi.
Deshmukh, Vinay (Vinay D.)
author Deshmukh, Vinay (Vinay D.)
author_sort Deshmukh, Vinay (Vinay D.)
title The design of a decision support system for supply chain risk management
title_short The design of a decision support system for supply chain risk management
title_full The design of a decision support system for supply chain risk management
title_fullStr The design of a decision support system for supply chain risk management
title_full_unstemmed The design of a decision support system for supply chain risk management
title_sort design of a decision support system for supply chain risk management
publisher Massachusetts Institute of Technology
publishDate 2008
url http://hdl.handle.net/1721.1/42354
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