Finally, we study a multi-period, risk-averse inventory model. The objective is to maximize the expected pay-offs. The risk-averse behavior is modeled as to penalize the decision maker if a target-profit level is not satisfied for each financial reporting cycle. We recognize that the operational period is usually faster than the financial reporting cycle. Therefore, the financial reporting cycle can be considered as an integer times of the operational periods. We study this model under both accrual-basis accounting principle and cash-basis accounting principle. We prove that the optimal inventory policy is a state-dependent base-stock policy under the accrual-basis accounting method. We then show that the structure of an optimal policy is a complicated one for the cash-basis accounting method. / In this thesis we study three supply chain models which address downside risk from a different angle. We start with a commitment-option supply contract in a Conditional Value-at-Risk (CVaR) framework. We show that a CVaR trade-off analysis with advanced reservation can be carried out efficiently. Moreover, our study indicates how the corresponding contract decisions differ from decisions for optimizing an expected value. / Key words. Downside Risk Measure; CVaR; Risk; Loss-Averse; Dynamic Programming. / Owing to the growing globalization in economy and the advances in commerce, research in supply chain management has attracted large number of researchers in the last two decades. Yet standard treatments of supply chain models are mainly confined for the optimization of expected values with little reflection on risk considerations. Even for those that consider a risk measure in the objective function, there are quite few literatures employing downside risk measure. The downside risk measure takes into account only the part of the distribution that is below a critical value. Thus it indicates a safety-first strategy for decision maker. / The thesis is organized in five chapters. In Chapter 1, we provide the background and research motivation for considering downside risk measures in supply chain models. In Chapter 2, we study the pay-to-delay supply contracts with a Conditional Value-at-Risk (CVaR) framework. In Chapter 3, we study the loss-averse newsvendor problem. In Chapter 4, we extend the loss-averse model to a multi-period setting. We conclude the thesis in Chapter 5 with discussions for future research. / Then, we employ a loss-aversion utility function to characterize newsvendor's decision-making behavior. We find that when there is no shortage cost, the loss-averse newsvendor consistently orders less than a risk-neutral newsvendor. Further, we discover that the loss-averse newsvendor orders a constant quantity when the reference target is sufficiently large. We discuss the importance of initial inventory to achieve the target profit level. When the target is a decision variable, the newsvendor always sets the target no higher or no lower. / Ma, Lijun. / "October 2007." / Adviser: Houmin Yan. / Source: Dissertation Abstracts International, Volume: 69-08, Section: B, page: 5003. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 140-154). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_344135 |
| Date | January 2007 |
| Contributors | Ma, Lijun, Chinese University of Hong Kong Graduate School. Division of Systems Engineering and Engineering Management. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, theses |
| Format | electronic resource, microform, microfiche, 1 online resource (v, 154 p. : ill.) |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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