期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 36, 期 5, 页码 9105-9112出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2008.12.039
关键词
Supplier selection; Data envelopment analysis (DEA); Decision tree (DT); Neural networks (NNs); Data mining (DM); Classification; Prediction
As the most important responsibility of purchasing management, the problem of vendor evaluation and selection has always received a great deal of attention from practitioners and researchers. This management decision is a challenge due to the complexity and various criteria involved. This paper presents a hybrid model using data envelopment analysis (DEA), decision trees (DT) and neural networks (NNs) to assess supplier performance, The model consists of two modules: Module 1 applies DEA and classifies suppliers into efficient and inefficient clusters based on the resulting efficiency scores. Module 2 utilizes firm performance-related data to train DT. NNs model and apply the trained decision tree model to new suppliers. Our results yield a favorable classification and prediction accuracy rate. (C) 2008 Elsevier Ltd. All rights reserved.
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