摘要
出行即服务(MaaS)集成了多种交通方式,为出行者提供便捷、高效的一站式服务,具有良好的应用前景。了解用户对MaaS系统的选择偏好及其影响因素,是开展MaaS系统设计和推广的前提。论文基于上海市问卷调查数据,构建了有序Probit模型,识别了影响MaaS系统使用意愿的主要因素。研究发现,高频使用公交车、共享交通、组合通勤出行,以及认为当前出行费用高、换乘不便捷的受访者,使用MaaS系统的意愿更加强烈。而高收入人群及月出行花费较低人群对MaaS系统的使用意愿不强。通过边际效应分析发现,受访者对交通支出、公交车使用偏好、月收入、通勤及工作情况等因素的敏感性更强。研究成果可为MaaS服务设计及推广提供理论支撑。
Mobility as a service(MaaS) integrates various transportation modes to provide convenient and efficient one-stop service for travelers, and has great application potential. Understanding users’ preferences on the MaaS system, along with its influential factors is the prerequisite for MaaS design and promotion. Based on the questionnaire survey data at Shanghai, this paper proposed an Ordered Probit Model and identified the major factors affecting travelers’ willingness on MaaS system. The study found that travelers using buses,shared transportation frequently, commuting by multi-modes, holding the view that the current travel costs were high, and current transfers were inconvenient, had strong willingness to use MaaS system. However,MaaS system was not attractive to high-income people and people with low travel expenses. This study further analyzed the marginal effects of each influential factor and found that MaaS willingness were more sensitive to transportation expenditure, public transport, income, commuting and work conditions. These results can provide data support for MaaS service design and promotion.
作者
王洧
牛晓晖
张晓光
赵军舰
王博灏
成诚
WANG Wei;NIU Xiaohui;ZHANG Xiaoguang;ZHAO Junjian;WANG Bohao;CHENG Cheng(The Key Laboratory of Road and Traffic Engineering of the Ministry of Education,Tongji University,Shanghai 201804,China;China Transportation Institute at Tongji,No.1239,Siping Road,Shanghai 200092,China;China Roads Communications Science&Technology Group Co.,Ltd.,Shijiazhuang 050035,China)
出处
《综合运输》
2022年第11期171-176,共6页
China Transportation Review
基金
上海市社会发展科技攻关项目(21DZ1205102)
中国交通建设集团有限公司科技研发项目(2019-ZJKJ-ZDZX02)。
关键词
城市交通
出行即服务
有序PROBIT模型
使用意愿
Urban transportation
MaaS(Mobility as a Service)
Ordered probit model
Willingness to use