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Mean-variance analysis for supply ch...

Choi, Tsan-Ming.

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Mean-variance analysis for supply chain management models.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Mean-variance analysis for supply chain management models./
Author:	Choi, Tsan-Ming.
Description:	225 p.
Notes:	Mentors: Duan Li; Houmin Yan.
Contained By:	Dissertation Abstracts International63-10B
Subject:	Business Administration, Management -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3066608
ISBN:	0493859721

Mean-variance analysis for supply chain management models.
Choi, Tsan-Ming.

Mean-variance analysis for supply chain management models. - 225 p.

Mentors: Duan Li; Houmin Yan.

Thesis (Ph.D.)--Chinese University of Hong Kong (People's Republic of China), 2002.

In the supply chain management literature under the stochastic environment, most of the proposed policies target at improving the supply chain's efficiency in terms of the expected cost reduction or the expected profit improvement. However, the performance measure with an expected value alone lacks precision when the corresponding variance is high. It also ignores the risk preferences of individual supply chain's decision makers. In order to provide a tailor-fit optimal decision-making policy for the decision maker, it is desirable to have a systematic and quantifiable measure for risk preference.

ISBN: 0493859721Subjects--Topical Terms:

1260387
Business Administration, Management

Mean-variance analysis for supply chain management models.
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100 1 $a Choi, Tsan-Ming. $3 1067324
245 1 0 $a Mean-variance analysis for supply chain management models.
300 $a 225 p.
500 $a Mentors: Duan Li; Houmin Yan.
500 $a Source: Dissertation Abstracts International, Volume: 63-10, Section: B, page: 4844.
502 $a Thesis (Ph.D.)--Chinese University of Hong Kong (People's Republic of China), 2002.
520 $a In the supply chain management literature under the stochastic environment, most of the proposed policies target at improving the supply chain's efficiency in terms of the expected cost reduction or the expected profit improvement. However, the performance measure with an expected value alone lacks precision when the corresponding variance is high. It also ignores the risk preferences of individual supply chain's decision makers. In order to provide a tailor-fit optimal decision-making policy for the decision maker, it is desirable to have a systematic and quantifiable measure for risk preference.
520 $a In light of all these, we study in this dissertation the application of the classical Mean-Variance Theory in finance for supply chain models. In mathematical finance, pioneered by the Nobel laureate Harry Markowitz in the 1950s, the Mean-Variance Theory has been an important theory for risk control in portfolio management. Under the Mean-Variance Theory, we can quantify the profit and risk in a portfolio investment by the expected return and variance of return, respectively. The Mean-Variance Theory has been demonstrated to be very applicable in practice. Based on the spirit of the Mean-Variance Theory, many optimal investment policies in finance are developed
520 $a In this dissertation, using the idea of the Mean-Variance Theory, together with the Bayesian Decision Theory and the other optimization techniques, we study, analyze and build various supply chain management models, which include the inventory problems, the supply chain coordinating buyback contracts, and the optimal ordering policies with information updates
520 $a This dissertation is divided into two parts and each part contains several chapters. Each chapter can be treated as a self-contained paper and the Mean-Variance Theory has been applied in each one of them. Throughout this dissertation, short example cases and numerical studies with computer simulations are included to illustrate the applicability of the models. From the studies in this dissertation, we can see that the classical Mean-Variance Theory can provide a systematic framework for the scientific studies of risk and uncertainty control in stochastic supply chain models in the information age. Moreover, the importance of risk control in supply chain management should not be neglected
590 $a School code: 1307
650 $a Business Administration, Management $3 1260387
650 $a Engineering, Industrial $3 1260336
650 $a Operations Research $3 1260417
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690 $a 054
690 $a 079
710 2 $a Chinese University of Hong Kong (People's Republic of China) $3 1260514
773 0 $t Dissertation Abstracts International $g 63-10B
790 $a 130
790 1 $a Li, Duan, $e adviso
790 1 $a Yan, Houmin, $e adviso
791 $a Ph.D
792 $a 200
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3066608