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Supplier selection in dynamic competitive environments

Supplier selection in dynamic competitive environments Supplier selection is one of the most critical decisions in a supply chain. While good suppliers can contribute to the supply chain's overall performance, incorrect selection can drive the whole supply chain into disarray. In this paper, we focus on the problem of supplier selection in a manufacturing firm. We allow each supplier to compete with each other to be selected by the buyer for procurement. The competition is modelled in an auction framework as a bidding process where a supplier cannot observe immediate actions of other suppliers but has complete knowledge of their previous actions. We allow a supplier to use this knowledge in guessing other suppliers' future actions and bid accordingly. Our model enables repeated games, which can be assumed to be more flexible compared to most game theory applications in the supplier selection literature. Reinforcement learning and fictitious play are used in the auction framework to implement repeated games. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Services Operations and Informatics Inderscience Publishers

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1741-539X
eISSN
1741-5403
DOI
10.1504/IJSOI.2008.02134
Publisher site
See Article on Publisher Site

Abstract

Supplier selection is one of the most critical decisions in a supply chain. While good suppliers can contribute to the supply chain's overall performance, incorrect selection can drive the whole supply chain into disarray. In this paper, we focus on the problem of supplier selection in a manufacturing firm. We allow each supplier to compete with each other to be selected by the buyer for procurement. The competition is modelled in an auction framework as a bidding process where a supplier cannot observe immediate actions of other suppliers but has complete knowledge of their previous actions. We allow a supplier to use this knowledge in guessing other suppliers' future actions and bid accordingly. Our model enables repeated games, which can be assumed to be more flexible compared to most game theory applications in the supplier selection literature. Reinforcement learning and fictitious play are used in the auction framework to implement repeated games.

Journal

International Journal of Services Operations and InformaticsInderscience Publishers

Published: Jan 1, 2008

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