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公共交通系统作为城市运转的重要组成部分已成为学界研究的焦点。本文利用贵阳市中心城区调研数据，引入地形感知变量，构建包含潜变量的SEM-Logit模型来分析居民公共交通出行选择影响因素。结果表明：包含潜变量的SEM-Logit模型比不包含潜变量的Logit模型拟合度更佳，个人属性变量中，性别、年龄、受教育程度、个人月收入、驾照持有情况、家中小汽车规模显著影响居民公共交通出行选择；潜变量因素中，目的地可达性、吸引力、地形感知对居民公共交通出行选择造成显著负向影响，即公共服务设施越便捷、小区吸引力越强、地形感知越大，居民选择公共交通出行的概率越小，而出行态度和活动支持与居民公共交通出行选择具有正相关性。地形感知对老年人与中年人公共交通出行选择均产生负向影响，但对中年人的影响程度大于老年人；地形感知对长期居住者公共交通出行选择的影响具有持久性和适应性，对短期居住者公共交通选择削弱较小。研究结论可为山地城市规划和交通建设提供指导。
Abstract：Public transportation systems, as integral parts of urban operations, have become an increasingly popular research topic. Using data collected from systems in the city of Guiyang, the latent variable fitness values calculated by the structural equation model(SEM) are incorporated into the logit model, a logit model without latent variables and a structural equation modelling-logit(SEM-logit) model with latent variables were constructed to analyze the influence of variables on residents' public transportation travel choices. The results show that the SEM-logit model with latent variables is a better fit than the logit model without latent variables for personal attribute variables.Gender, age, education level, monthly income, holding a driver's license, and car size all significantly affect residents' public transportation travel mode choices. For latent variables, accessibility, attractiveness, and terrain perception negatively influence residents' public transportation travel mode choices. The more convenient public service facilities are, the more attractive the neighborhood is,and the greater the terrain perception is, the less likely residents are to choose travelling via public transportation. Conversely, travel attitude and activity support positively influence residents' public transportation travel mode choices. The results also show that terrain perception negatively influences public transportation travel choices for both elderly and middle-aged people, with middle-aged people more negatively influenced than elderly people. Moreover, the effect of terrain perception on public transportation travel mode choices for long-term residents is persistent and adaptive, while short-term residents are not as affected by terrain perception. The findings of this study can provide guidance for urban planning and transportation construction in mountainous areas.
[1]任倩.基于随机参数logit模型的公共交通出行方式选择行为研究[D].广州:华南理工大学, 2019.REN Qian. Research on the public transportation trip mode choice behavior based on random parameter logit model[D]. Guangzhou:South China University of Technology, 2019.
[2]周子皓,张莉,吴西伦,等.个体出行情景下上海中心城区地铁可达性研究[J].地理与地理信息科学, 2021, 37(2):71-76.ZHOU Zi-hao, ZHANG Li, WU Xi-lun, et al. Research on metro accessibility in central urban area of Shanghai under individual travelling scenario[J]. Geography and GeoInformation Science, 2021, 37(2):71-76.
[3]魏薇，赵航，龙立美，等.山地城市老年人公共交通可达性分析——以贵阳市中心城区为例[J].地理与地理信息科学, 2021, 37(6):64-70.WEI Wei, ZHAO Hang, LONG Li-mei, et al. Analysis on accessibility of public transportation for the elderly in mountainous cities:a case study of the central urban area of Guiyang[J]. Geography and Geo-Information Science,2021, 37(6):64-70.
[4]段梅花,赵航,龙立美,等.山地城市公交系统服务在老年人群体中分配公平性评价[J].地球信息科学学报,2021, 23(4):617-631.DUAN Mei-hua, ZHAO Hang, LONG Li-mei, et al. The evaluation of allocation fairness to urban transit system service for the elderly in mountainous city[J]. Journal of Geo-Information Science, 2021, 23(4):617-631.
[5] BALL K, JEFFERY R W, CRAWFORD D A, et al. Mismatch between perceived and objective measures of physical activity environments[J]. Preventive Medicine, 2008,47(3):294-298.
[6]李臣，陈艳艳，周雨阳，等.城市轨道交通突发事件下乘客出行选择影响因素研究[J].铁道运输与经济,2021,43(7):105-111.LI Chen, CHEN Yan-yan, ZHOU Yu-yang,et al.Influencing factors of passenger travelchoice under urban rail transit emergency conditions[J].Railway Transport and Economy, 2021,43(7):105-111.
[7]栾鑫，邓卫，程琳，等.特大城市居民出行方式选择行为的混合Logit模型[J].吉林大学学报(工学版），2018,48(4):1029-1036.LUAN Xin, DENGWei, CHENGLin, et al. Mixed logit model for understanding travel mode choice behavior of megalopolitan residents[J].Journal of Jilin University(Engineering and Technology Edition),2018,48(4):1029-1036.
[8] GENG J, LONG R, CHEN H, et al. Exploring multiple motivations on urban residents’travel mode choices:an empirical study from Jiangsu Province in China[J]. Sustainability, 2017, 9(1):136.
[9] LIU X, GAO L, NI A, et al. Understanding better the influential factors of commuters’multi-day trvelbehavior:evidence from Shanghai, China[J]. Sustainability, 2020,12(1):376.
[10] DE LUCA S, DI PACE R. Modelling users’behaviour in inter-urban carsharing program:a stated preference approach[J]. Transportation Research Part A:Policy and Practice, 2015, 71:59-76.
[11]曹新宇.社区建成环境和交通行为研究回顾与展望:以美国为鉴[J].国际城市规划,2015,30(4):46-52.CAO Xin-yu.Examining the relationship between beighborhood built environment and travel behavior:a review from the US perspective[J].Urban Planning International,2015,30(4):46-52.
[12] PARKK, EWING R, SCHEER B C, etal. The impacts of built environment characteristics of rail station areas on household travel behavior[J].Cities,2018,74:277-283.
[13] YANG Y, XU Y, RODRIGUEZ D A, et al. Active travel,public transportation use, and daily transport among older adults:the association of built environment[J]. Journal of Transport&Health, 2018,9:288-298
[14] DING C, CAO X, LIU C. How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds[J]. Journal of Transport Geography, 2019, 77:70-78.
[15]黄洁，王姣娥，靳海涛，等.北京市地铁客流的时空分布格局及特征——基于智能交通卡数据[J].地理科学进展, 2018, 37(3):397-406.HUANG Jie, WANG Jiao-e, JIN Hai-tao, et al. Investigating spatiotemporal patterns of passenger flows in the Beijing metro system from smart card data[J]. Progress in Geography, 2018, 37(3):397-406.
[16]王安琪，彭建东，任鹏，等.轨道站点周边建成环境对残疾人出行行为的影响研究——以武汉市189个轨道站点为例[J].地理科学进展,2021,40(7):1127-1140.WANG An-qi, PENG Jian-dong, REN Peng, et al. Impact of the built environment of rail transit stations on the travel behavior of persons with disabilities:taking189 rail transit stations in Wuhan Cityas an example[J].Progress in Geography, 2021, 40(7):1127-1140.
[17]赵鹏军，李南慧，李圣晓.TOD建成环境特征对居民活动与出行影响——以北京为例[J].城市发展研究,2016,23(6):45-51.ZHAO Peng-jun, LI Nan-hui, LI Sheng-xiao. The impacts of the built environment on residents’acitivities and travel behavior in TOD areas:a case study of Beijing[J]. Urban Development Studies, 2016, 23(6):45-51.
[18]董禹,秦椿棚,董慰,等.地铁站周边不同范围建成环境对居民出行方式的影响研究:哈尔滨的实证[J].南方建筑, 2020(2):35-41.DONG Yu, QIN Chun-peng, DONG Wei, et al. Impact of built environments within different ranges around subway stations on residents’travel modes:an empirical study in Harbin[J]. South Architecture, 2020(2):35-41.
[19]杨文越,梁斐雯,曹小曙.多尺度建成环境对居民通勤出行碳排放的影响——来自广州的实证研究[J].地理研究,2020,39(7):1625-1639.YANG Wen-yue, LIANG Fei-wen, CAO Xiao-shu. Examining the effects of the multi-scale built environment on residents’CO2emissions from commuting:an empirical study of Guangzhou[J]. Geographical Research,2020, 39(7):1625-1639.
[20] CAO X J. How does neighborhood design affect life satisfaction? Evidence from Twin Cities[J]. Travel Behaviour and Society, 2016, 5:68-76.
[21] LINDEL?W D, SVENSSON?, STERNUDD C, et al.What limits the pedestrian? Exploring perceptions of walking in the built environment and in the context of every-day life[J]. Journal of Transport&Health, 2014, 1(4):223-231
[22]钟异莹，邵毅明，陈坚.考虑居住环境的公共交通出行选择行为模型[J].科学技术与工程,2020,20(22):9217-9221.ZHONG Yi-ying, SHAO Yi-ming, CHEN Jian. Travel choice behavior model of public transportation considering residential environment[J]. Science Technology and Engineering, 2020, 20(22):9217-9221.
[23]陈坚，张弛，庹永恒，等.考虑环保意识和出行习惯的公交出行选择行为模型[J].交通运输系统工程与信息,2020,20(4):128-135.CHEN Jian, ZHANG Chi, TUO Yong-heng, et al. Travel mode choice behavior model of public transit in corporating environmental concern and habit[J]. Journal of Transportation Systems Engineering and Information Technology,2020,20(4):128-135.
[24] BOUSCASSEH, JOLY I, BONNELP. How does environmental concern influence mode choice habits? A mediation analysis[J]. Transportation Research Part D:Transportand Environment, 2018,59:205-222.
[25] LI L, XIONG J, CHEN A, et al. Key strategies for improving public transportation based on planned behaviortheory:case study in Shanghai, China[J]. Journal of Urban Planning and Development, 2015, 141(2):04014019.
[26]冯焕焕,邓建华.基于前景值和乘客最优理论的居民公交出行选择模型[J].科学技术与工程,2019,19(5):307-311.FENG Huan-huan,DENG Jian-hua.Model of public transport choice based on prospect value and passenger optimal theory[J]. Science Technology and Engineering,2019,19(5):307-311.
[27] SUN X, WANDELT S. Transportation mode choice behavior with recommender systems:A case study on Beijing[J]. Transportation research interdisciplinary perspectives, 2021, 11:100408.
[28]胡晓伟，石腾跃，于璐，等.基于扩展技术接受度模型的共享自动驾驶汽车用户使用意愿研究[J].交通运输工程与信息学报,2021,19(3):1-12.HU Xiao-wei,SHI Teng-yue,YU Lu,et al. Measuring users’willingness to use shared autonomous vehicles based on an extension technology acceptance model[J].Journal of Transportation Engineering and Information,2021,19(3):1-12.
[29]潘晓锋,左志.基于潜在类别模型的出行决策机理异质性研究[J].交通运输工程与信息学报,2022,20(1):55-62.PAN Xiao-feng, ZUO Zhi. Utilizing a latent class model to explore heterogeneity in travel decisionmechanism[J].Journal of Transportation Engineering and Information,2022,20(1):55-62.
[30]刘洛廷.基于SEM-Logit的城际旅客出行公共交通模式选择意向研究[D].西安:长安大学,2019.LIU Luo-ting. Study on the choice intention of intercity passengers'public transport mode based on SEM-logit[D].Xi'an:Changan University, 2019.
[31]陈坚,晏启鹏,杨飞,等.出行方式选择行为的SEMLogit整合模型[J].华南理工大学学报(自然科学版),2013, 41(2):51-57,65.CHEN Jian, YAN Qi-peng, YANG Fei, et al. SEM-logit integration model of travel mode choice behaviors[J].Journal of South China University of Technology(Natural Science Edition),2013, 41(2):51-57,65.
[32]沈玮薇,肖为周,杨磊,等.基于TPB的居民通勤出行公交选择意向模型[J].交通运输工程与信息学报,2016,14(3):106-112.SHEN Wei-wei, XIAO Wei-zhou, YANG Lei, et al. Public transport choice intention model of commute travel mode based on TPB[J]. Journal of Transportation Engineering and Information, 2016,14(3):106-112.
[33]张雪.住区建成环境的主观感知对居民通勤方式选择的影响研究:以深圳市南山区为例[D].哈尔滨:哈尔滨工业大学, 2018.ZHANG Xue. Perception on the residential environment for commuting model choice—a case study of Nanshan district Shenzhen[D]. Harbin:Harbin Institute of Technology, 2018.
[34]胡骥,刘艳,张艳,等.基于SEM的运输通道出行方式选择决策机理研究[J].交通运输工程与信息学报,2015, 13(3):7-15.HU Ji, LIU Yan, ZHANG Yan, et al. Decision-making mechanism of mode choice in transportation corridor based on SEM[J]. Journal of Transportation Engineering and Information, 2015, 13(3):7-15.
[35]吴明隆.结构方程模型：AMOS的操作与应用[M].重庆:重庆大学出版社, 2010.WU Ming-long. Structural equation model:operationand application of AMOS[M]. Chongqing:Chongqing University Press, 2010.
基本信息:
DOI：10.19961/j.cnki.1672-4747.2022.09.001
中图分类号:U491.17
引用信息:
[1]熊仁江,赵航,段梅花,等.地形感知对居民公共交通出行方式选择的影响研究——以贵阳市为例[J],2023,21(02):177-188.DOI:10.19961/j.cnki.1672-4747.2022.09.001.
基金信息:
国家自然科学基金项目（71864008）