摘要
随着航空与铁路竞争越来越充分,航空公司更多采用灵活多变的价格来吸引客流,为了量化研究航空价格对铁路客流的影响,通过监测收集大量的航空价格时点数据,将动态变化的航空价格转化为可以计算的静态价格,在此基础上构建基于航空价格的铁路旅客列车票价调整模型,引入改进的皮尔逊相关系数来衡量航空价格对铁路客流的影响,根据相关性强弱,筛选出受航空价格影响较大的OD区间和车次,进而通过计算任意始发日期航空价格,采用与历史参考期比较来判断航空价格的“走势”,有助于铁路运营企业票价策略调整的研究。
Airlines adopt more flexible fare strategy to attract passenger flow to cope with the strong competition between air and railway.A large number of time-point data of air price is monitored and collected and then the dynamic air fare data is transformed into static fare to quantitatively study the impact of air fare on railway passenger flow.This paper introduces the improved Pearson correlation coefficient to measure the impact of air fare on railway passenger flow and builds a passenger train ticket fare adjustment model based on air fare.According to the correlation strength,the OD and train number which are greatly affected by air price are selected.Finally,the trend of air fare is judged by calculating the air fare on any departure date and compared with the historical reference period.The study results help the railway operators optimize their fare strategy accordingly.
作者
王煜
王亮
方伟
潘跃
田秘
周珊琪
WANG Yu;WANG Liang;FANG Wei;PAN Yue;TIAN Mi;ZHOU Shanqi(Institute of Computing Technology,China Academy of Railway Sciences Corporation Limited,Beijing 100081,China;Department of Passenger Transport,China State Railway Group Co.Ltd,Beijing 100844,China)
出处
《铁道运输与经济》
北大核心
2020年第12期17-23,37,共8页
Railway Transport and Economy
基金
国家重点研发计划重点专项课题(2018YFB1201400)。
关键词
航空价格计算
铁路客流
皮尔逊相关系数
票价策略
运营策略
Air Price Monitoring
Railway Passenger Flow
Pearson Correlation Coefficient
Fare Strategy
Business Strategy
