Abstract

Supplier base management is an important strategy for managing global, customer driven supply chains. Successful supplier base management can effectively handle supply side exceptions, which may have significant business implications. Currently, there is a trend to reduce the size of the supplier base which makes the coordination and interaction among suppliers more effective, less costly and time consuming. The goal of this research is to present a clustering algorithm, named min-min-roughness (MMR) to cluster suppliers into smaller, more manageable groups with similar characteristics. Due to the fact that supplier data are mainly categorical in nature, MMR, based on rough set theory (RST) is developed for categorical data clustering which is also capable of handling the uncertainty during the clustering process. One potential benefit of applying MMR to supplier base management is that more realistic benchmarking can be obtained and the fulfilment operation can be sped up by reducing the number of variables impacting the operations. In addition, the characteristics of each smaller group of suppliers can be summarised and exploited to handle supply side disruptions.

Original languageEnglish (US)
Pages (from-to)3803-3821
Number of pages19
JournalInternational Journal of Production Research
Volume48
Issue number13
DOIs
StatePublished - Jan 1 2010

Keywords

  • Data mining
  • Rough set theory
  • Supplier base management

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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