Study on design for outsourcing using evidence theory decision tree

One of the most popular strategies in business today is global outsourcing, where maintenance as a non-core process is often outsourced. Outsourced maintenance information can affect the product development sustainability, achievement transformation capacity and product quality. Data generated in the processes of outsourced maintenance are inherently uncertain and seldom classified according to their importance. From these data the relevant uncertain information can be able to search. Since evidence theory is a powerful tool can deal with uncertain data, this paper propose a search mechanism use evidence theory decision tree algorithm to classify uncertain data generated form outsourced maintenance and to dig out the rules. The experimental results shows this algorithm can efficient classify uncertain data and generate rules which can guide the products research and development.