NDLI: Applying SVM to build supplier evaluation model - comparing likert scale and fuzzy scale

Content Provider	IEEE Xplore Digital Library
Author	Hsu, C.F. Chang, B. Hung, H.F.
Copyright Year	2007
Description	Author affiliation: Nat. Taiwan Univ., Taipei (Hsu, C.F.)
Abstract	This research was performed to generate a supplier evaluation (SE) model in order to enhance an enterprise's competitiveness, and apply this model to solve practical business problems. Through past studies, we applied representative supplier evaluation principles while designing supplier evaluation questionnaire, and classified the suppliers into three categories: perform excellently (class 1), perform ordinary (class 2), and perform poorly (class 3). The Likert scale and fuzzy scale are applied individually to compute a score according to these principles. We then apply the support vector machine (SVM) to build the supplier evaluation classifier, and observe under SVM whether using the Likert or fuzzy scale produces better classification performance. The result revealed that the performance is invariant under both scales. Therefore, we find SVM combined with efficient feature reduction to be a better strategy for building a supplier evaluation model.
Starting Page	6
Ending Page	10
File Size	479949
Page Count	5
File Format	PDF
ISBN	9781424415281
DOI	10.1109/IEEM.2007.4419140
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-02
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Performance evaluation Supply chain management Costs Supply chains Information technology Supplier evaluation model Support vector machines Computer science Technology management support vector machine Engineering management Support vector machine classification fuzzy scale
Content Type	Text
Resource Type	Article

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