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Predictive performance model in collaborative supply chain using decision tree and clustering technique

机译:基于决策树和聚类技术的协同供应链预测绩效模型

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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.
机译:本文提出了一个B2B供应链(B2B-SC)和绩效评估系统之间的集成框架。该框架基于数据挖掘技术,可以开发具有前瞻性协作功能的预测性协作绩效演进模型和决策。结果是部署了协作性能准则,该准则已由领域专家根据其实际实际使用效率进行了验证。该框架使管理人员能够开发系统的方式来预测未来的协作绩效并识别其关系中潜在的问题。还讨论了它的用法和困难。此外,最终的预测结果和规则包含与SC长期改善相关的重要信息。

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