Research On Demand Forecast Of High Speed Railway Revenue Management Based On The Customer Segmentation

As Jing Hu, Ha Da Jing Guang and other high speed railway line have been established and put into operation and adjustment of the plan is in continuous progress, high-speed rail network in China has initially formed. How to make full use of the railway passenger transportation capacity, increase the ridership and operating income has become one of the important problems to be solved for railway passenger transport department. With the introduction of revenue management system, and analysis of passenger travel behavior features and patterns, maximized revenue can be derived. Drawing on the successful experience of foreign railway and aviation, revenue management in high-speed railway is imperative. Accurate ODF(origin-destination fare class) passenger flow forecast of railway and customer preference prediction can improve seat control method effectively that is more suitable for the market and for passenger department operation to provide scientific and reasonable decision reference, ultimately achieve the goal of profit maximization. By using the ticket data, questionnaire survey, literature review, computational simulation, the paper builds a high-speed railway demand forecasting model based on customer segmentation. The main researches of the paper are as follows:1. Combine customer value and high speed railway revenue management for the first time of which customer value is considered as the standard of market segmentation for high speed railway revenue management. By researching and analyzing the characteristics of high speed railway customer demand in each segment value, profit optimization model saves the ticket to the high value of customers as much as possible, so as to achieve maximum profit. According to the seasonal characteristics of China’s high-speed railway, the paper combines Markov chain and RFM model to attain the dynamic model of customer value segmentation with the seasonal changes which provide a more accurate market segmentation standard for the earnings management based on customer segmentation.2. Establish short-term passenger flow prediction model for high speed railway depending on whether the train enters booking period. When the high speed train is not open to booking period, take the characteristic of passenger flow in regular date and special date into consideration, two different situation of passenger data flow prediction models are established. When the high speed train enters the pre-order period, establish demand forecast model for target date according to current bookings. These two models, in each stage, provide inputs for revenue optimization model with indepent demand.3. Propose customer preference model with customer value segmentation based on customer onboard records and the analysis of ODF properties of high speed railways trains which have similarities. Except for using the traditional revenue management in the multinomial logit choice model based on customer preference, the paper also draws lessons from the algorithm of recommendation system model and improves the model according to the the characteristics of high speed railway customer preference which expands the theoretical application of revenue management preference model in all respects.4. Design the prototype of the high speed railway revenue management based on customer segmentation. An optimized revenue management model based on bidding is proposed according to customer demand forecasting mode. Construct an online and offline system, which makes the revenue management system, updates requirement values according to the factors that affect customer needs in real time. The high-speed railway revenue is improved in the maximum extend.