| |
| his paper aims at investigating the feasibility of optimizing supply chain performance by analyzing customer data using data mining techniques. In particular, it introduces the C2S system that performs this task. In C2S, the overall supply chain management performance is measured by end customer satisfaction. And the working sequences of C2S can be summarized as follows. Firstly, customers are segmented into different groups using clustering algorithm and actionable cluster-defining rules are derived for each cluster. Secondly, for each segment, the Customer Lifetime Value (CLV) is computed and Customer Requirements are acquired. According to the distinct customer requirements in different customer segments, the association mining approach is employed to find possible factors through whole supply chain that are relevant to these requirements, to help the decision maker in making feasible actions to satisfy customer requirements. Thereafter, we can define the supply chain performance o |
|
| Keywords:Supply Chain, Data Mining, Clustering, Customer Lifetime Value, Competence Set, Customer Relationship Management. |
|
