Urban Rail Transit Peak And Off-peak Periods Variable Logging Ticket Pricing Strategies Study Based On Elastic Coefficient

The urban rail transit has developed rapidly in recent years in China. Many urban rail transits like Beijing, Guangzhou, Shanghai have entered the era of network operations. Beijing urban rail transit fare system reformed in order to adapt the urban rail transit network operation, to meet the safety and efficient travel needs of the majority passengers, and began to implement on 28 December 2014. To different traffic modes, passenger flow volume is affected largely by traffic fare. When a certain mode of traffic fare increases, the passenger flow of this traffic mode would decrease, and the passenger flow of the rest traffic modes would increase. Contrarily when a certain mode of traffic fare decreases, the passenger flow of this traffic mode would increase, and the passenger flow of the rest traffic modes would decrease. So the traffic fare and the passenger flow is interactional, and affected by each other. On the urban rail transit fare and passenger flow, the existed academic research focuses more on qualitative research rather than quantitative research. On the elastic coefficient applied to the urban rail transit variable pricing, the existed academic research refers to the foreign urban rail transit related numerical years ago, the domestic related research is less. Therefore, this paper refers to the foreign and domestic urban rail transit ticket price related research, combines the characteristics of the urban rail transit passenger flow, focuses on the Beijing urban rail transit passenger flow and fare system, studies the urban rail transit elasticity coefficient and the peak and off-peak variable logging ticket pricing schemes.The main contents of this paper are as follows:(1)This paper summarizes China’s major urban rail transit passenger flow, fare systems, preferential measures according to data collection, analyzes the influence of China’s major urban rail transit Fare adjustment on passenger flow.(2)Based on Beijing urban rail transit fare system reform by the end of 2014, this paper analyzes the influence of the Fare adjustment on the daily passenger flow, different travel distance passenger flow, different travel time passenger flow, the passenger flow ingredients at AM peak hours (7:00-9:00) and at AM-BM off-peak hours (9:00-17:00), which provide data support for the urban rail transit demand elastic coefficient analysis.(3)The demand elasticity theory of micro economics is introduced to study the urban rail transit demand elasticity coefficient in Beijing. This paper analyzes the sensitiveness of the different travel distance, different travel time passenger flow of Beijing urban rail transit to fare, which provides data support and theoretical support for the propose of the Beijing urban rail transit peak and off-peak variable logging ticket pricing strategies and schemes.(4)According to China’s urban rail transit metered logging ticket price and foreign urban rail transit peak and off-peak periods fare preferential measures, this paper proposes Beijing urban rail transit peak and off-peak variable logging ticket pricing strategies, and establishes variable pricing system models for different pricing strategies based on the urban rail transit elastic coefficient. Combined with the analysis of the elasticity coefficient, this paper solves the pricing schemes and compares several available schemes, which provides a reference advice for the further adjustment of Beijing urban rail transit fare system.