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线性需求下铁路客运差别定价模型研究

朱颖婷, 单杏花

朱颖婷, 单杏花. 线性需求下铁路客运差别定价模型研究[J]. 铁路计算机应用, 2020, 29(1): 25-28.
引用本文: 朱颖婷, 单杏花. 线性需求下铁路客运差别定价模型研究[J]. 铁路计算机应用, 2020, 29(1): 25-28.
ZHU Yingting, SHAN Xinghua. Differential pricing model of railway passenger transport based on linear demand[J]. Railway Computer Application, 2020, 29(1): 25-28.
Citation: ZHU Yingting, SHAN Xinghua. Differential pricing model of railway passenger transport based on linear demand[J]. Railway Computer Application, 2020, 29(1): 25-28.

线性需求下铁路客运差别定价模型研究

基金项目: 

中国铁道科学研究院青年基金科研课题(2017YJ102)

详细信息
    作者简介:

    朱颖婷,助理研究员;单杏花,首席研究员。

  • 中图分类号: U293.22;TP39

Differential pricing model of railway passenger transport based on linear demand

  • 摘要: 为提高席位资源利用率,研究了线性需求下我国铁路客运差别定价策略的优化模型。以收益最大化为目标,基于最优化理论和完全价格歧视策略,确定旅客群体最优细分数目以及每个旅客群体的最优票价,得出在客运淡季,铁路旅客最优细分数目为3~5个,各旅客群的最优票价由铁路客运市场细分数目决定。应用该模型为某城际高铁进行差别定价,试验结果表明,该模型可达到调节客流、增加收益的目的。
    Abstract: In order to improve the utilization rate of seat resources, this paper studied the optimization model of differential pricing strategy of China's railway passenger transport under linear demand. To maximize the revenue, based on the optimization theory and the total price discrimination strategy, the paper determined the optimal subdivision number of passenger groups and the optimal ticket price of each passenger group. It was concluded that in the off-season of passenger transport, the optimal subdivision number of railway passengers was 3-5, and the optimal ticket price of each passenger group was determined by the subdivision number of railway passenger market segments. The model was applied to the differential pricing of an intercity high-speed railway. The experimental results show that the model can adjust passenger flow and increase revenue.
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  • 期刊类型引用(3)

    1. 高玲,单杏花,王洪业,韩慧婷,丁静. 高速铁路客运票价最高限价调整机制研究. 铁路计算机应用. 2024(03): 1-6 . 本站查看
    2. 张涛,阎志远,吕占民,李贝贝. 铁路列车统一补票系统架构优化及演进. 铁道运输与经济. 2022(01): 73-79 . 百度学术
    3. 黄鑫. 基于收益管理思想的铁路货运经营管理. 综合运输. 2020(11): 87-90+110 . 百度学术

    其他类型引用(4)

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  • 被引次数: 7
出版历程
  • 收稿日期:  2019-07-11

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