Evaluating supply partner's capability for seasonal products using machine learning techniques

被引：7

作者：

Hong, Gye-hang ^{[2
]}

Ha, Sung Ho ^{[1
]}

机构：

[1] Kyungpook Natl Univ, Sch Business Adm, Taegu 702701, South Korea

[2] Dongbu Financial Ctr, Dongbu CNI, Seoul 135523, South Korea

来源：

COMPUTERS & INDUSTRIAL ENGINEERING | 2008年 / 54卷 / 04期

关键词：

supply chain management; supply capability; seasonal products; data mining; multi-criteria decision making;

D O I：

10.1016/j.cie.2007.10.009

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

We develop a dynamic partner assessment system (DPAS) in order to assess change in a supply partner's capability over a period of time. The system embeds a multi-criteria decision model and machine learning methods, and is designed to evaluate a partner's supply capability that can change over time and to maximize revenue with different procurement conditions across time periods. We apply the system to the procurement and management of the agricultural industry. The results are compared with real-world auction markets. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：721 / 736

页数：16

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