交通运输系统工程与信息 ›› 2012, Vol. 12 ›› Issue (6): 100-105.

• 系统工程理论与方法 • 上一篇    下一篇

基于模糊聚类的城际高铁旅客出行行为实证研究

刘健,张宁*   

  1. 北京航空航天大学 经济管理学院,北京 100191
  • 收稿日期:2012-07-21 修回日期:2012-10-19 出版日期:2012-12-25 发布日期:2012-12-29
  • 作者简介:刘健(1983-),女,辽宁朝阳人,博士生.
  • 基金资助:

    国家自然科学基金创新研究群体科学基金(70521001);国家自然科学基金 (70971003).

Empirical Research of Intercity Highspeed Rail Passengers’ Travel Behavior Based on Fuzzy Clustering Model

LIU Jian, ZHANG Ning   

  1. School of Economics and Management, Beihang University, Beijing 100191, China
  • Received:2012-07-21 Revised:2012-10-19 Online:2012-12-25 Published:2012-12-29

摘要:

高速铁路是我国计划在未来重点发展的交通运输方式.本文运用模糊聚类模型,对京津城际高铁建成前后的旅客出行行为及选择偏好影响因素进行实证分析.分析结果表明,城际高铁能够通过提升城际间的旅客通行能力,释放和激发商务、探亲、旅游等多种活动需求,从而加深城际间的经济和情感互动联系.同时,研究还发现,“快”是高速铁路的标志性竞争力,高铁安全性能提升和服务改善应以保证速度为前提.本文实证研究充分证明,高速铁路是让个人、城市和国家发展多方受益的交通运输方式,在改善出行条件的同时也获得了比较满意的服务评价,值得重点推广.

关键词: 铁路运输, 城际高铁, 出行行为, 影响因素, 模糊聚类模型

Abstract:

Highspeed rail (HSR) is a rising industry in China and its development will be accelerated in the future. An empirical research is conducted to analyze passengers’ travel behavior and selection preference factors before and after the completion of BeijingTianjin intercity HSR using fuzzy clustering model. The results indicate that through improving the transportation capacity between cities, HSR can create and release multiple travel activity needs such as for business, visiting relatives and friends, tourism activities, etc. It can also help strengthen the economic and social intercity interactions. It is also clarified that “speed” is the symbolic competitive advantage of HSR. The improvement for HSR’s security and service should be based on reasonable speed. The empirical results clearly prove that HSR is a winwin transportation industry that is beneficial for individual, city and the nation. It will get satisfactory service evaluation through improving travel conditions and is worth further promotion. 

Key words: railway transportation, intercity high-speed rail, travel behavior, preference factor, fuzzy clustering model

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