基于不同运输方式竞争的高速铁路票价制定方法研究

发布时间：2018-03-03 16:25

本文选题：高速铁路　切入点：竞争定价　出处：《西南交通大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着生活节奏的加快,人们的出行需求越来越高。高速铁路作为一种新兴的运输方式,凭借其快速、安全、舒适、便捷等特点在客运市场中迅速崛起,加剧了客运市场的竞争。本文以高速铁路快速发展带来的激烈竞争为研究背景,认为价格因素是决定一种运输方式市场竞争力的核心手段。制定合理的票价是保持高速铁路系统稳定与促进其健康发展的关键。积极研究高速铁路票价的定价策略,从理论与实践上探讨票价制定的过程,具有特别重要的意义。本文以多种运输方式票价的市场化决定机制为前提,通过分析高铁的竞争主体,建立基于市场竞争条件的票价优化模型,并找到理想的算法求出不同阶段高速铁路最优价格,为解决高铁定价问题提供一种新的尝试。首先从运输价格的一般定义及特点切入,分析高速铁路的产品构成及价格影响因素,对常用的定价理论进行归纳总结,为下文的定价研究作理论基础。通过与主要高铁国家对比分析,借鉴已有的成功经验并找出我国目前存在的问题。然后针对高速铁路的市场竞争力进行了研究,本文从高速铁路技术经济优势与旅客出行选择行为两方面切入,结合旅客出行过程分析影响出行方式选择的因素,找出高速铁路相比其它运输方式的优势方面。根据运输供给因素和旅客自身因素建立基于服务特性的效用函数模型,将各种影响因素分成费用测度指标与影响系数指标。通过Logit模型的计算,找出不同运输距离条件下高速铁路的竞争主体,结合具体算例进行验证。在对旅客票价与客运收入、运量之间关系研究的基础上,兼顾铁路运输企业与旅客两方面利益,建立双层规划模型描述票价制定问题。其中上层规划的目标函数根据高铁发展的两个阶段建立对应的两种形式,下层规划建立受费用影响的弹性需求配流模型,通过增设多余需求路段的网络图变换方法转化为固定需求问题。将改进后的粒子群算法与双层规划问题相结合,建立基于改进粒子群的双层迭代算法,通过上、下层反复迭代逐次逼近全局最优解。最后提出了一些高铁定价的相关建议。通过成渝高铁实例分析验证了论文理论方法的可行性,并求出成渝高铁不同发展阶段最优票价。
[Abstract]:With the quickening pace of life, people's travel demand is higher and higher. High-speed railway, as a new mode of transportation, with its characteristics of speed, safety, comfort, convenience and so on, is rising rapidly in the passenger transport market. This paper takes the fierce competition brought by the rapid development of high-speed railway as the research background. It is considered that the price factor is the core means to determine the market competitiveness of a mode of transportation. The key to maintain the stability of the high-speed railway system and promote its healthy development is to make a reasonable fare. The pricing strategy of the high-speed railway ticket price is studied actively. It is of great significance to discuss the process of fare making in theory and practice. On the premise of the market-oriented decision mechanism of various modes of transportation, this paper analyzes the main body of high speed railway competition, establishes the optimization model of ticket price based on market competition conditions, and finds out the ideal algorithm to find out the optimal price of high-speed railway in different stages. It provides a new attempt to solve the problem of high-speed rail pricing. First of all, from the general definition and characteristics of transport price, this paper analyzes the product composition and price influence factors of high-speed railway, and summarizes the common pricing theory. Through the comparison and analysis with the main high-speed rail countries, we can draw lessons from the existing successful experience and find out the existing problems in our country. Then the market competitiveness of high-speed railway is studied. This paper analyzes the factors that affect the choice of travel mode from the two aspects of high-speed railway's technical and economic advantages and passenger travel choice behavior combined with passenger travel process. To find out the advantages of high-speed railway compared with other modes of transportation. According to the factors of transport supply and passenger itself, the utility function model based on service characteristics is established. The influence factors are divided into cost measure index and influence coefficient index. Through the calculation of Logit model, the main competitors of high-speed railway under different transportation distance conditions are found out, and verified by a concrete example. On the basis of the study of the relationship between passenger ticket price and passenger transport revenue and volume, the interests of railway transport enterprises and passengers are taken into account. A bilevel programming model is established to describe the pricing problem, in which the objective function of the upper level programming is based on the two stages of the high-speed rail development, and the lower level programming establishes the elastic demand distribution model affected by the cost. The network graph transformation method of adding redundant demand sections is transformed into a fixed demand problem. The improved particle swarm optimization algorithm is combined with the bilevel programming problem to establish a two-level iterative algorithm based on the improved particle swarm optimization. The global optimal solution is approximated by successive iterations at the lower level. Finally, some suggestions on high-speed railway pricing are put forward, and the feasibility of the theoretical method is verified by analyzing the example of Chengdu-Chongqing high-speed railway, and the optimal ticket price of Chengdu-Chongqing high-speed railway at different stages of development is obtained.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U238;F532

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