Data Mining for Supply Chain Management in Complex Networks: Concepts, Methodology and Application

Data Mining for Supply Chain Management in Complex Networks: Concepts, Methodology and Application

Manoj K. Singh (i2 Technologies, USA) and Mahesh S. Raisinghani (University of Dallas, USA)
DOI: 10.4018/978-1-878289-88-9.ch007
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Abstract

The concept and philosophy behind supply chain management is to integrate and optimize business processes across all partners in the entire production chain. Since these are not simple supply chains but rather complex networks, tuning these complex networks comprising supply chain/s to the needs of the market can be facilitated by data mining. Data mining is a set of techniques used to uncover previously obscure or unknown patterns and relationships in very large databases. It provides better information for achieving competitive advantage, increases operating efficiency, reduces operating costs and provides flexibility in using the data by allowing the users to pull the data they need instead of letting the system push the data. However, making sense of all this data is an enormous technological and logistical challenge. This chapter helps you understand the key concepts of data mining, its methodology and application in the context of supply chain management of complex networks.

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