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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

Integrating environmental criteria into the supplier selection process

Wong, Yin-king. January 2000 (has links)
Thesis (M. Phil.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 163-177).

An investigation of collaborative buyer-supplier relationships in Hong Kong manufacturing firms

Shiu, Wing-kei. January 2000 (has links)
Thesis (M. Phil.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 166-178).

The Impact of supplier development on buyer-supplier performance

Li, Wenli, January 2001 (has links)
Thesis (Ph. D.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 214-235).

Implementing knowledge management as a strategic initiative /

DiGiacomo, Joseph. January 2003 (has links) (PDF)
Thesis (M.S. in Contract Management)--Naval Postgraduate School, December 2003. / Thesis advisor(s): David V. Lamm, Donald Summers. Includes bibliographical references (p. 81-83). Also available online.

Essays on sourcing strategies and inventory management : theory and empirical evidence /

Shan, Jun. January 2009 (has links)
Includes bibliographical references (p. 79-84).

Characteristics and techniques of industrial purchasing procedures in Hong Kong electronics industry.

Tang, Shun-yau. January 1900 (has links)
Thesis (M. Sc.)--University of Hong Kong, 1979.

Supply quality management of leading manufacturing related companies in Hong Kong /

Yeung, Ho-wah, Alice. January 2002 (has links)
Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 252-300).

A portfolio approach to procurement planning and risk hedging under uncertainty

Shi, Yuan, 石园 January 2010 (has links)
published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

Commodity procurement risk management using futures contracts: a dynamic financial hedging approach withmultistage rebalancing

Ni, Jian, 倪剑 January 2011 (has links)
published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

Long-term commodity procurement risk management using futures contracts: a dynamic stack-and-rollapproach

Shi, Li, 时莉 January 2013 (has links)
The procurement of commodity materials for production is an important issue in supply chain management. Effective procurement should consider both uncertain customer demand and fluctuating commodity price which, when act together, give rise to the procurement risk. To protect the bottom line, a manufacturer has to plan its procurement activities with special attention given to such procurement risk. Existing research has studied the use of exchange market-traded commodities in mitigating procurement risk. This study addresses the case of a manufacturer with long-term procurement commitments who wishes to hedge against the risk exposure by using long-dated futures contracts. In the commodities markets, however, long-dated futures are often illiquid or even unavailable, thus making the hedge ineffective. Alternatively, in a stack-and-roll hedge, the hedging positions are rolled forward in actively traded short-dated futures contracts of equal maturity until the procurement is executed. This in effect replicates the long-term futures contract in performing a hedge. This study therefore aims at developing a dynamic stack-and-roll approach that can effectively manage the long maturity procurement risk. The proposed dynamic stack-and-roll approach is inherently a discrete-time hedging strategy that divides the procurement planning horizon into multiple decision stages. The nearby futures are adopted as the short-dated futures as they are typically liquid. The hedging positions are adjusted periodically in response to the commodity price behaviour and updated information about the forward customer demand. For a manufacturer who wishes to mitigate the procurement risk as well as maximise the terminal revenue after the procurement, the mean-variance objective function is employed to model the manufacturer’s risk aversion behaviour. Then, a dynamic program formulation of the approach is presented for determining a closed-form expression of the optimal hedging positions. Notice that the hedging policy is a time-consistent mean-variance policy in discrete-time, in contrast to the existing discrete hedging approaches that employ minimum-variance policies. In this study, the commodity prices are modelled by a fractal nonlinear regression process that employs a recurrent wavelet neural network as the nonlinear function. The purpose of this arrangement is to incorporate the fractal properties discovered in commodity prices series. In the wavelet transform domain, fractal self-similarity and self-affinity information of the price series over a certain time scale can be extracted. The Extended Kalman Filter (EKF) algorithm is applied to train the neural network for its lower training error comparing with classical gradient descent algorithms. Monthly returns and volatility of commodity prices are estimated by daily returns data in order to increase the estimation accuracy and facilitate effective hedging. The demand information is updated stage by stage using Bayesian inference. The updating process are defined and adapted to a filtration, which can be regarded as the information received at the beginning of each decision stage. Numerical experiments are carried out to evaluate the performance of the proposed stack-and-roll approach. The results show that the proposed approach robustly outperforms other hedging strategies that employ minimum-variance or naïve policies, and effectively mitigate the procurement risk. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

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