基于CBR和MAHP的新产品客户价值预测决策支持系统

Decision support system for customer value prediction of new product based on CBR and MAHP

针对新产品客户价值预测决策支持系统的不足,结合案例推理和连乘层次分析法,研究了一种改进的新产品客户价值预测决策支持系统,区分了客户购买模型中各影响因素对不同层次客户的影响效用,减少了专家通过调研评估获取模型参数的次数,同时拓展了系统用户的范围。通过算例验证了该决策支持系统的有效性。

Aiming at the shortcomings of customer value prediction Decision Support System （DSS） for new product proposed, an improved Case-Based Reasoning-based and Multiplicative Analytic Hierarchy Process-based Customer Value Prediction Decision Support System （C＆M-CVPDSS） was proposed, which could distinguish the influence utility of each influencing factors on different kinds of customers in customer purchasing model, reduce the times of experts to obtain the model parameters by research assessment, and expand the range of system users. The effectiveness of C＆M-CVEDSS was verified through a numerical example.