Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/12372
Title: A performance benchmarking system to support supplier selection
Authors: Lau, HCW
Lee, CKM
Ho, GTS
Pun, KF
Choy, KL 
Keywords: Artificial neurral network
Genetic algorithm
Performance benchmarking
Supplier management
Supplier selection
Supply chain management
Issue Date: 2006
Source: International journal of business performance management, 2006, v. 8, no. 2-3, p. 132-151 How to cite?
Journal: International Journal of Business Performance Management 
Abstract: In today's competitive business environment, management of suppliers is essential for companies to monitor the value chain of the entire production network. Evidence suggests that undesirable occurrences in companies, such as extensive delays in the planned schedule, serious quality problems and cost overruns, are, to a certain extent, related to the unfulfilled promises of business partners. Subjective judgment and the lack of a systematic method for supplier selection hinder the analysis of the current and projected performance of the suppliers, which is necessary before making a final decision. This paper attempts to propose a generic model for supplier selection, focusing on the methodology to benchmark the potential suppliers and providing a comparison of performance measures based on a number of relevant criteria. To validate the feasibility of the proposed system, this paper makes use of existing AI tools that have been developed for selecting and benchmarking suppliers for manufacturing firms.
URI: http://hdl.handle.net/10397/12372
ISSN: 1368-4892
DOI: 10.1504/IJBPM.2006.009033
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