吉林大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (1): 98-104.doi: 10.13229/j.cnki.jdxbgxb20161198

• 论文 • 上一篇    下一篇

基于态度的公交出行信息使用市场细分

侯现耀1, 2, 3, 陈学武1, 2, 3   

  1. 1.东南大学 城市智能交通江苏省重点实验室,南京 210096;
    2.东南大学 现代城市交通技术江苏高校协同创新中心,南京 210096;
    3.东南大学 交通学院,南京 210096
  • 收稿日期:2016-11-07 出版日期:2018-02-26 发布日期:2018-02-26
  • 通讯作者: 陈学武(1968-),女,教授,博士. 研究方向:客运交通系统规划与评价. E-mail: chenxuewu@seu.edu.cn
  • 作者简介:侯现耀(1985-),男,博士研究生. 研究方向:城市公共交通规划与管理. E-mail: houxianyao@gmail.com
  • 基金资助:
    国家自然科学基金重点项目(51338003); “973”国家重点基础研究发展计划项目(2012CB725402)

Use of public transit information market segmentation based onattitudinal factors

HOU Xian-yao1, 2, 3, CHEN Xue-wu1, 2, 3   

  1. 1.Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 210096, China;
    2.Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 210096, China;
    3.School of Transportation, Southeast University, Nanjing 210096, China
  • Received:2016-11-07 Online:2018-02-26 Published:2018-02-26

摘要: 为识别不同出行者对公交出行信息使用选择偏好的差异,对基于态度的公交出行信息使用市场进行了细分。根据在南京市调查的数据,利用因子分析确定态度潜变量,采用结构方程模型分析了态度变量间的相关性,使用K-means聚类方法对公交出行信息使用的市场进行细分。以出行意愿、可靠性、方便性和主观感知等4个变量作为聚类变量,将公交出行信息使用市场细分为5个子市场,同一子市场内出行者公交出行意愿选择近似,不同子市场间出行者选择意愿明显不同。分析了每个子市场态度的差异和公交出行方式选择特征,针对不同子市场的出行者提出了相应的公交出行信息改善策略。

关键词: 交通运输系统工程, 市场细分, K-means聚类, 公交出行信息, 结构方程模型

Abstract: To identify travelers with different preferences on using public transit information, the market segmentation was conducted using attitudinal factors. Based on survey data of Nanjing, first the attitude latent variables were determined by factor analysis, and the relationships among the attitude latent variables were analyzed by structural equation modeling. Then, the K-means clustering method was employed to segment the travelers' use of public transit information. Four variables including willingness to use public transit, reliability of public transit information, accessibility of public transit information, and perception toward public transit information were selected as clustering variables to segment the use of public transit information market into five sub-markets. Travelers in the same sub-market have similar travel preferences, while those in different sub-markets have distinct preferences. Differences of the attitudinal factors and characteristics of public transit travel choices in each sub-market were examined, and the policies that serve different sub-markets were proposed to improve public transit information service.

Key words: engineering of communications and transportation system, market segmentation, K-means clustering, public transit information, structural equation modeling

中图分类号: 

  • U491.1
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