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Quantitative Models for Supply Chain Risk Analysis From a Firm's Perspective.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Quantitative Models for Supply Chain Risk Analysis From a Firm's Perspective./
Author:	Vinayak, Arun.
Description:	1 online resource (75 pages)
Notes:	Source: Masters Abstracts International, Volume: 57-02.
Contained By:	Masters Abstracts International57-02(E).
Subject:	Industrial engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9780355337808

Quantitative Models for Supply Chain Risk Analysis From a Firm's Perspective.
Vinayak, Arun.

Quantitative Models for Supply Chain Risk Analysis From a Firm's Perspective. - 1 online resource (75 pages)

Source: Masters Abstracts International, Volume: 57-02.

Thesis (M.S.)--Iowa State University, 2017.

Includes bibliographical references

Supply chain risk analysis garnered increased attention, both in academia and in practice, since the early 2000s. Modern production methodologies such as just-in-time and lean manufacturing, globalized supply chains, shorter product life cycle, and the emphasis on efficiency have increased the risk faced by many supply chains. Managing such risks that is faced by a supply chain is vital to the success of any company. Currently employed methods lack consideration of market reaction and incorporation of decision maker preferences in managing supply chain risk. In this thesis, these two factors are taken into consideration to develop quantitative methods to analyze supply chain risk.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355337808Subjects--Topical Terms:

679492
Industrial engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Quantitative Models for Supply Chain Risk Analysis From a Firm's Perspective.
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245 1 0 $a Quantitative Models for Supply Chain Risk Analysis From a Firm's Perspective.
264 0 $c 2017
300 $a 1 online resource (75 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 57-02.
500 $a Includes supplementary digital materials.
500 $a Adviser: Cameron A. MacKenzie.
502 $a Thesis (M.S.)--Iowa State University, 2017.
504 $a Includes bibliographical references
520 $a Supply chain risk analysis garnered increased attention, both in academia and in practice, since the early 2000s. Modern production methodologies such as just-in-time and lean manufacturing, globalized supply chains, shorter product life cycle, and the emphasis on efficiency have increased the risk faced by many supply chains. Managing such risks that is faced by a supply chain is vital to the success of any company. Currently employed methods lack consideration of market reaction and incorporation of decision maker preferences in managing supply chain risk. In this thesis, these two factors are taken into consideration to develop quantitative methods to analyze supply chain risk.
520 $a The first study is focused on supply chain risk from the market side in case of a major disruption. A probabilistic model based on different types of customer behaviors is developed to identify the impact on the firm's revenue by forecasting the lost revenue in case of a production shut down from a disruption event. Results from a simulation of the developed model is analyzed to draw useful insights to manage the risk of such an event.
520 $a The second study is centered on supplier selection. It presents a 5-step framework based on KPIs derived from the performance metrics of the SCOR (Supply Chain Operations Reference) model. The framework can be used for supplier selection as well as for supplier performance monitoring as the firm continues to work with the selected supplier. Decision makers from a firm can incorporate their own preference within the presented framework to determine the most preferred supplier and assess the cost effectiveness to select a supplier in different scenarios to minimize supply side risk.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Industrial engineering. $3 679492
650 4 $a Business administration. $3 1148568
655 7 $a Electronic books. $2 local $3 554714
690 $a 0546
690 $a 0310
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Iowa State University. $b Industrial and Manufacturing Systems Engineering. $3 1182174
773 0 $t Masters Abstracts International $g 57-02(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10606947 $z click for full text (PQDT)