峰前折扣票价下轨道交通乘客出发时间弹性

以北京地铁峰前折扣票价政策为背景，利用自动售检票数据研究折扣票价对乘客出发时间的影响. 首先，从“消费行为”视角建立客观的分类指标并对客运市场进行细分；其次，以较长时期内出发时间中位数为指标，基于“事前-事后对比法”对出发时间发生转移的乘客进行辨识；最后，准确测定不同类型乘客出发时间对票价变动的敏感程度. 结果显示：乘客出发时间票价弹性随转移时长增加而急剧下降，30 min 几乎是乘客所能接受的最大转移时长；通勤类乘客弹性最低，低频及生活类乘客相对富有弹性；限制当前折扣票价政策效果的主要因素在于折扣截止时间过早.该研究能够为差别定价方案编制及优化提供关键参数.

Departure Time Elasticities of Transit Travelers under Pre-peak Discount Price

Taking the pre-peak discount fare policy of Beijing subway as the background, this work studies the impact of discount fares on passenger’s departure time by mining smart card data. Firstly, new classification indexes in the perspective of“consumer behaviors”are established to segment transit markets. Secondly, the median of departure times is used to determine shifted passengers who move forward departure times, by using an “before-and-after compare method”. Then, departure time elasticities of different passenger groups are measured. The results show that departure time elasticities decrease sharply with shift time increasing, and 30 minutes are almost the maximum time that passengers can accept. Commuters have the lowest flexibility, low-frequency and living-travel passengers are relatively flexible. The main reason for limiting the effectiveness of the current policy is unreasonable setting of the discount deadline. This study provides fundamental parameters for fare scheme programming and optimization.