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作 者:郝晓培[1] 单杏花 张军锋 HAO Xiao-pei;SHAN Xing-hua;ZHANG Jun-feng(Postgraduate Department,China Academy of Railway Sciences,Beijing 100081,China;Institute of Computing Technology,China Academy of Railway Sciences Corporation Limited,Beijing 100081,China)
机构地区:[1]中国铁道科学研究院研究生部,北京100081 [2]中国铁道科学研究院集团有限公司电子计算技术研究所,北京100081
出 处:《铁道运输与经济》2018年第9期80-85,共6页Railway Transport and Economy
基 金:中国铁道科学研究院科研项目(2016YJ100);北京交通发展研究基地科研项目(B17H100020)
摘 要:随着铁路运输能力大幅增加,铁路客运服务的营销焦点已经从产品中心转换到用户中心,铁路需要从传统的营销策略转变为以旅客价值为依据的铁路利益最大化和旅客服务质量最优化的共赢策略。在建立以旅客价值指数为目标计算模型的基础上,实现基于聚类—BP神经网络的旅客历史价值指数计算,以及基于旅客同行关系的旅客潜在价值指数计算,并利用大量样本数据对铁路旅客价值指数计算模型进行实例分析。结果表明,该模型能够有效地对旅客价值进行计算并识别出不同价值指数的旅客群体,制定个性的营销和服务策略,合理配置铁路客运资源,实现铁路利益最大化和旅客服务质量最优化的共赢目标。With the dramatic increase of railway transportation capacity, the focus of railway passenger service marketing has shifted from product-centered to customer-centered. Railway needs changing from traditional marketing strategy to win-win strategy of maximizing railway benefits and optimizing passenger service quality based on passenger value. On the basis of establishing the calculation model with the passenger value index as the target, through the analysis of the passenger historical value index and the potential value index, the calculation of the passenger historical value index based on clustering-BP neural network and the calculation of the passenger potential value index based on the passenger Ran K are realized. At the same time, a large number of sample data are used to analyze the model. The results show that the model can effectively calculate the value of passengers and identify the different value index of passenger groups, formulate individual marketing and service strategies for different groups of passengers, rationally allocate railway passenger transport resources, and achieve the win-win goal of maximizing railway benefits as well as optimizing passenger service quality.
关 键 词:旅客价值 聚类 BP神经网络 服务质量 客运资源
分 类 号:U293[交通运输工程—交通运输规划与管理]
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