Efficient Techniques for Predicting Suppliers Churn Tendency in E-Commerce Based on Website Access Data
| Main Authors: | Moertini, Veronica S., Ibrahim, Niko, Lionov, Lionov |
|---|---|
| Format: | Article PeerReviewed Book |
| Terbitan: |
, 2015
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| Subjects: | |
| Online Access: |
http://repository.maranatha.edu/19022/1/Efficient%20Techniques%20for%20Predicting%20Suppliers%20Churn%20Tendency.pdf http://repository.maranatha.edu/19022/ |
Daftar Isi:
- Electronic supplier relationship management (e-SRM) is important in order to maintain strong, long lasting and beneficial relatiosnhip between e-commerce firms and their suppliers. One important function of e-SRM is to predict suppliers who tend to churn such that early "treatment" can be given. In the e-commerce systems that involve suppliers as the website users, predicting "suppliers" churn tendency can be based on analyzing their frequencies in accessing the e-commerce websites. Our proposed techniques include data warehouse design (supporting the data collection and preprocessing) and unsupervised algorithms that analyze the preprocessed bitmaps of time series data representing efficient (the time complexity is O(n) as proven with oure experiments. In experimenting with real world data of an e-commerce system selling hotel rooms, our techniques produce output of supplier segment where each segment has certain churn level tendency and need specific treatment.