학술논문

Predictive performance model in collaborative supply chain using decision tree and clustering technique
Document Type
Conference
Source
2011 4th International Conference on Logistics Logistics (LOGISTIQUA), 2011 4th International Conference on. :412-417 May, 2011
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Transportation
Signal Processing and Analysis
Robotics and Control Systems
Collaboration
Predictive models
Data mining
Data models
Decision trees
Supply chains
Mathematical model
Business to Business (B2B)
Supply chain (SC)
Data Mining
Multi Attribute Decision Making
Performance Measurement
Language
ISSN
2162-9021
Abstract
This paper proposes an integrated framework between B2B supply chains (B2B-SC) and performance evaluation systems. This framework is based on data mining techniques, enabling the development of a predictive collaborative performance evolution model and decision making which has forward-looking collaborative capabilities. The results are deployment for collaborative performance guidelines, which were validated by the domain experts in terms of its real practical usage efficiency. This framework enables managers to develop systematic manners to predict future collaborative performance and recognize latent problems in their relationship. Its usages and difficulties were also discussed. Furthermore, the final predictive results and rules contain vital information relating to SC improvement in the long term.