摘要
针对企业如何采取有效的市场营销组合策略来提高顾客忠诚度的问题,提出了基于BP(back-propagation)神经网络算法的企业市场营销组合策略分析方法;建立了基于4Ps理论的营销组合策略影响因素函数;通过对不同的营销组合策略影响因素进行加权、量化、各层之间权值的调整和迭代运算,最终构建了满足预定误差要求的BP神经网络模型;通过对十种手机品牌顾客忠诚度的实际调查值与网络模拟值相比较,得出了BP神经网络算法具有良好的模拟性,在此基础上证明了该方法在企业进行市场营销组合策略选择时具有良好的预见性和实用性。
To solve the problem of how corporations use effective marketing strategy combination to improve the faithfulness of customers, an analysis method based on back-propagation neural network （BPNN） algorithm for simulating corporations＇ marketing strategy combination is proposed, According to 4Ps theory, function of marketing strategy combination influence factors is established. A reliable BPNN model which satisfies scheduled error is set up eventually through weighing, quantizing the influence factors of marketing strategy combination, iteratively calculating and adjusting the weighing factor of each layer. Comparisons between the actual investigation value and the network simulated value of the faithful degree of ten kinds of mobile phone users show that BP network has a good simulation quality. On the basic of it, BP neural network is proved to have promising forecasting reliability and practicality in corporations＇ marketing strategy combination choices.
出处
《辽宁工程技术大学学报（自然科学版）》
CAS
北大核心
2008年第3期424-427,共4页
Journal of Liaoning Technical University (Natural Science)
基金
河南省自然科学研究基金资助项目(200510460019)
关键词
营销策略组合
BP神经网络
顾客忠诚度
手机市场
sale strategy combination
BP network
custom loyalty degree
mobile phone market
