Design of an intelligent supplier relationship management system: A hybrid case based neural network approach

King Lun Tommy Choy, Wing Bun Lee, V. Lo

Research output: Journal article publicationJournal articleAcademic researchpeer-review

117 Citations (Scopus)

Abstract

In today's accelerating world economy, the drive to continually cut costs and focus on core competencies has driven many to outsource some or all of their production. In this environment, improving supply chain execution and leveraging the supply base through effective supplier relationship management (SRM) has become more critical than ever in achieving competitive advantage. It was found that the use of artificial intelligence in the outsourcing function of SRM to identify appropriate suppliers to form a supply network has become a promising solution on which manufacturers depend for products, services and distribution. In this paper, an intelligent supplier relationship management system (ISRMS) using hybrid case based reasoning (CBR) and artificial neural networks (ANNs) techniques to select and benchmark potential suppliers is discussed. By using ISRMS in Honeywell Consumer Product (Hong Kong) Limited, the outsource cycle time from searching for potential suppliers to the allocation of order is greatly reduced.
Original languageEnglish
Pages (from-to)225-237
Number of pages13
JournalExpert Systems with Applications
Volume24
Issue number2
DOIs
Publication statusPublished - 1 Feb 2003

Keywords

  • Artificial neural network
  • Case based reasoning
  • Supplier relationship management
  • Supplier selection and benchmarking
  • Supply network

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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