基于出行者潜在类别的公交出行行为研究
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摘要
不同类型的公交使用者对公交的评价、使用公交出行的意愿不相同,如何对公交使用者进行有效划分,分析各类因素对划分的影响,并研究不同类型出行者使用公交意愿等受到各类影响因素的异同是值得关注的问题.文中引入潜在回归模型,基于公交使用者对公交满意度、使用意愿等几类因素,对其进行类别划分,并根据类别划分,分别分析每一类公交出行者总体满意度、使用公交意愿受到的影响因素的异同.研究结果表明,公交使用可划分为机会乘客、忠诚乘客两类群体,且小汽车拥有情况、收入水平会影响出行者的类别划分.拥有小汽车时,出行者更可能成为机会乘客,随着收入的增加,出行者成为机会乘客的概率增加.对比分析影响出行者总体满意度的因素,发现速度评价、准点性评价、等车时间评价、票价评价等因素对机会乘客总体满意度的影响大于对忠诚乘客总体满意度的影响.分析成功推荐他人使用公交的情况,发现机会乘客总体满意度对推荐结果的影响极为显著,随着总体满意度的增加,推荐的概率大致呈线性增长趋势.研究使用公交频率影响因素,发现拥有小汽车会降低机会乘客和忠诚乘客使用公交频率,而增加总体满意度会增加机会乘客使用公交频率.
Different types of bus users have different opinions on public transport and their willingness to use public transport.Different types of bus users have different opinions on public transport and their willingness to use public transport.Based on bus users' satisfaction and their traveling behavior,bus users were classified with the latent class regression model.Then based on the classification,factors that affect the overall satisfaction and the willingness to traveling by bus were analyzed among different subgroup.This result shows that bus users can be classified into two subgroups: the occasional bus users and the loyal bus users,and that private car ownership and income have a great influence on the classification.That is users with private car are more likely to be occasional bus users,and along with income increases,the user is more likely to be a occasional bus user.The analysis result of factors affecting satisfaction shows that the evaluation on bus speed,time reliability,waiting time and ticket price have stronger influence on occasional bus users' overall satisfaction than that on loyal bus users'.As to the effect of recommendation to use bus,it is found that the overall satisfaction of occasional bus users significantly affect the recommendation effect,and the recommendation effect increases as the overall satisfaction increases.Also,travelers' traveling by bus decreases after they have private cars and the occasional bus users' frequency of traveling by bus increases as the overall satisfaction increases.
Different types of bus users have different opinions on public transport and their willingness to use public transport.Different types of bus users have different opinions on public transport and their willingness to use public transport.Based on bus users' satisfaction and their traveling behavior,bus users were classified with the latent class regression model.Then based on the classification,factors that affect the overall satisfaction and the willingness to traveling by bus were analyzed among different subgroup.This result shows that bus users can be classified into two subgroups: the occasional bus users and the loyal bus users,and that private car ownership and income have a great influence on the classification.That is users with private car are more likely to be occasional bus users,and along with income increases,the user is more likely to be a occasional bus user.The analysis result of factors affecting satisfaction shows that the evaluation on bus speed,time reliability,waiting time and ticket price have stronger influence on occasional bus users' overall satisfaction than that on loyal bus users'.As to the effect of recommendation to use bus,it is found that the overall satisfaction of occasional bus users significantly affect the recommendation effect,and the recommendation effect increases as the overall satisfaction increases.Also,travelers' traveling by bus decreases after they have private cars and the occasional bus users' frequency of traveling by bus increases as the overall satisfaction increases.
引文
[1] PRUD′HOMME R,KONING M,LENORMAND L,et al.Public transport congestion costs:The case of the paris subway [J].Transport Policy,2012,21(C):101- 109.
[2] LU X-S,LIU T-L,HUANG H-J.Pricing and mode choice based on nested logit model with trip-chain costs [J].Transport Policy,2015,44:76- 88.
[3] SHEN W,XIAO W,WANG X.Passenger satisfaction evaluation model for urban rail transit:A structural equation modeling based on partial least squares [J].Transport Policy,2016,46:20- 31.
[4] STUART K R,MEDNICK M,BOCKMAN J.Structural equation model of customer satisfaction for the new york city subway system [J].Transportation Research Record:Journal of the Transportation Research Board,2000,1735(1):133- 137.
[5] ZHAO J,WEBB V,SHAH P.Customer loyalty differences between captive and choice transit riders [J].Transportation Research Record:Journal of the Transportation Research Board,2014,2415(1):80- 88.
[6] IMAZ A,HABIB K M N,SHALABY A,et al.Investigating the factors affecting transit user loyalty [J].Public Transport,2014,7(1):39- 60.
[7] MA X,ZHANG J,DING C,et al.A geographically and temporally weighted regression model to explore the spatio-temporal influence of built environment on transit ridership [J].Computers,Environment and Urban Systems,2018,70:113- 124.
[8] SINGHAL A,KAMGA C,YAZICI A.Impact of weather on urban transit ridership [J].Transportation Research Part a-Policy And Practice,2014,69:379- 391.
[9] HOANG-TUNG N,KOJIMA A,KUBOTA H.Recognising customers' patterns of bus service patronage using a loyalty framework [J].IATSS Research,2014,37(2):148- 156.
[10] TRAIN K.A structured logit model of auto ownership and mode choice [J].The Review of Economic Studies,1980,47(2):357- 370.
[11] CHENG Y-H,CHEN S-Y.Perceived accessibility,mobi-lity,and connectivity of public transportation systems [J].Transportation Research Part A:Policy and Practice,2015,77(C):386- 403.
[12] CHENG Y-H,LIU K-C.Evaluating bicycle-transit users’ perceptions of intermodal inconvenience [J].Transportation Research Part A:Policy and Practice,2012,46(10):1690- 1706.
[13] BHAT C R.An endogenous segmentation mode choice model with an application to intercity travel [J].Transportation Science,1997,31(1):34- 48.
[14] 邱皓政.潜在类别模型的原理与技术 [M].北京:教育科学出版社,2008.
[15] LAZARSFELD P F.The logical and mathematical foundation of latent structure analysis [J].Studies in Social Psychology in World War II Vol.IV:Measurement and Prediction,1950:362- 412.
[16] DEMPSTER A P,LAIRD N M,RUBIN D B.Maximum likelihood from incomplete data via the em algorithm [J].Journal of the Royal Statistical Society(Series B)(methodological),1977:39(1):1- 38.
[17] LINZER D A,LEWIS J B.Polca:An r package for poly-tomous variable latent class analysis [J].Journal of Statistical Software,2011,42(10):1- 29.
[18] LIN T H,DAYTON C M.Model selection information criteria for non-nested latent class models [J].Journal of Educational and Behavioral Statistics,1997,22(3):249- 264.
[2] LU X-S,LIU T-L,HUANG H-J.Pricing and mode choice based on nested logit model with trip-chain costs [J].Transport Policy,2015,44:76- 88.
[3] SHEN W,XIAO W,WANG X.Passenger satisfaction evaluation model for urban rail transit:A structural equation modeling based on partial least squares [J].Transport Policy,2016,46:20- 31.
[4] STUART K R,MEDNICK M,BOCKMAN J.Structural equation model of customer satisfaction for the new york city subway system [J].Transportation Research Record:Journal of the Transportation Research Board,2000,1735(1):133- 137.
[5] ZHAO J,WEBB V,SHAH P.Customer loyalty differences between captive and choice transit riders [J].Transportation Research Record:Journal of the Transportation Research Board,2014,2415(1):80- 88.
[6] IMAZ A,HABIB K M N,SHALABY A,et al.Investigating the factors affecting transit user loyalty [J].Public Transport,2014,7(1):39- 60.
[7] MA X,ZHANG J,DING C,et al.A geographically and temporally weighted regression model to explore the spatio-temporal influence of built environment on transit ridership [J].Computers,Environment and Urban Systems,2018,70:113- 124.
[8] SINGHAL A,KAMGA C,YAZICI A.Impact of weather on urban transit ridership [J].Transportation Research Part a-Policy And Practice,2014,69:379- 391.
[9] HOANG-TUNG N,KOJIMA A,KUBOTA H.Recognising customers' patterns of bus service patronage using a loyalty framework [J].IATSS Research,2014,37(2):148- 156.
[10] TRAIN K.A structured logit model of auto ownership and mode choice [J].The Review of Economic Studies,1980,47(2):357- 370.
[11] CHENG Y-H,CHEN S-Y.Perceived accessibility,mobi-lity,and connectivity of public transportation systems [J].Transportation Research Part A:Policy and Practice,2015,77(C):386- 403.
[12] CHENG Y-H,LIU K-C.Evaluating bicycle-transit users’ perceptions of intermodal inconvenience [J].Transportation Research Part A:Policy and Practice,2012,46(10):1690- 1706.
[13] BHAT C R.An endogenous segmentation mode choice model with an application to intercity travel [J].Transportation Science,1997,31(1):34- 48.
[14] 邱皓政.潜在类别模型的原理与技术 [M].北京:教育科学出版社,2008.
[15] LAZARSFELD P F.The logical and mathematical foundation of latent structure analysis [J].Studies in Social Psychology in World War II Vol.IV:Measurement and Prediction,1950:362- 412.
[16] DEMPSTER A P,LAIRD N M,RUBIN D B.Maximum likelihood from incomplete data via the em algorithm [J].Journal of the Royal Statistical Society(Series B)(methodological),1977:39(1):1- 38.
[17] LINZER D A,LEWIS J B.Polca:An r package for poly-tomous variable latent class analysis [J].Journal of Statistical Software,2011,42(10):1- 29.
[18] LIN T H,DAYTON C M.Model selection information criteria for non-nested latent class models [J].Journal of Educational and Behavioral Statistics,1997,22(3):249- 264.