IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i6p1996-d152333.html

Research on Passenger’s Travel Mode Choice Behavior Waiting at Bus Station Based on SEM-Logit Integration Model

Author

Listed:
  • Yan Han

    (Key Laboratory of Traffic Engineering, College Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China)

  • Wanying Li

    (Key Laboratory of Traffic Engineering, College Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China)

  • Shanshan Wei

    (Key Laboratory of Traffic Engineering, College Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China)

  • Tiantian Zhang

    (Key Laboratory of Traffic Engineering, College Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China)

Abstract

To improve the mode share of public transport and reduce the transition to private transport of passengers waiting at bus station, the mechanism of passengers’ decision-making procedure and influence factors of the travel mode choice were analyzed. Some latent variables such as safety, comfort, convenience, flexibility and economy were selected to reflect the satisfaction degree of passengers on the service level of public transport. Taking Jinan City as an example, the questionnaire of passengers’ travel choice behavior at bus station was designed and carried out. Based on the structure equation model (SEM), the relationship between the satisfaction degree and some latent variables such as safety and comfort was discussed. The SEM method analysis shows that, of the influence level of the latent variables to the service level of public transport, flexibility is the most significant variable affecting passenger’s satisfaction degree followed by safety, convenience, comfort and economy. Travel mode choice model of passengers waiting at bus station was established with an integration approach of SEM and nested logit (NL) model. The SEM-NL integration model results reveal that gender, monthly income, purpose of the trip, travel distance, safety and convenience service level have a significant effect on the choice of the upper model (public transport or private transport). Passenger’s age, vehicle ownership and bus ride frequency have great influence on the choice of the lower mode (ORB: original route bus; ARB: alternative route bus; Taxi; and Shared bike). Sensitivity analysis reveals that the transition probabilities from private transport to public transport can reach the highest point (respectively, 69.85%, 68.84% and 35.51%) when safety service reaches level 4, convenience service reaches level 3, or comfort service reaches level 2, indicating that the safety level equal to 4, convenience level equal to 3 and comfort level equal to 2 are the key threshold to increase the public transport mode share. Some proposals such as ensuring good accessibility of public transport, shortening the transfer distance of different routes, creating a comfortable travel environment and integrating bus ticket system have been put forward for the sustainable development of public transport system.

Suggested Citation

  • Yan Han & Wanying Li & Shanshan Wei & Tiantian Zhang, 2018. "Research on Passenger’s Travel Mode Choice Behavior Waiting at Bus Station Based on SEM-Logit Integration Model," Sustainability, MDPI, vol. 10(6), pages 1-23, June.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:6:p:1996-:d:152333
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/6/1996/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/10/6/1996/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Vredin Johansson, Maria & Heldt, Tobias & Johansson, Per, 2006. "The effects of attitudes and personality traits on mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(6), pages 507-525, July.
    2. Golob, Thomas F., 2003. "Structural equation modeling for travel behavior research," Transportation Research Part B: Methodological, Elsevier, vol. 37(1), pages 1-25, January.
    3. Qin, Huanmei & Gao, Jianqiang & Zhang, Guohui & Chen, Yanyan & Wu, Songhua, 2017. "Nested logit model formation to analyze airport parking behavior based on stated preference survey studies," Journal of Air Transport Management, Elsevier, vol. 58(C), pages 164-175.
    4. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304, January.
    5. Khandker M. Nurul Habib & Md. Hamid Zaman, 2012. "Effects of incorporating latent and attitudinal information in mode choice models," Transportation Planning and Technology, Taylor & Francis Journals, vol. 35(5), pages 561-576, June.
    6. F. Biélen & N. Demoulin, 2007. "Waiting time influence on the satisfaction-loyalty relationship in services," Post-Print hal-00254951, HAL.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, January.
    8. Jichao Geng & Ruyin Long & Hong Chen & Ting Yue & Wenbo Li & Qianwen Li, 2017. "Exploring Multiple Motivations on Urban Residents’ Travel Mode Choices: An Empirical Study from Jiangsu Province in China," Sustainability, MDPI, vol. 9(1), pages 1-16, January.
    9. Erik Ekstrom & Per Lotstedt & Johan Tysk, 2009. "Boundary Values and Finite Difference Methods for the Single Factor Term Structure Equation," Applied Mathematical Finance, Taylor & Francis Journals, vol. 16(3), pages 253-259.
    10. Ben-Akiva, Moshe & McFadden, Daniel & Train, Kenneth & Börsch-Supan, Axel, 2002. "Hybrid Choice Models: Progress and Challenges," Sonderforschungsbereich 504 Publications 02-29, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    11. Xiaoshu Cao & Feiwen Liang & Huiling Chen & Yongwei Liu, 2017. "Circuity Characteristics of Urban Travel Based on GPS Data: A Case Study of Guangzhou," Sustainability, MDPI, vol. 9(11), pages 1-21, November.
    12. Yun Wang & Xuedong Yan & Yu Zhou & Qingwan Xue, 2017. "Influencing Mechanism of Potential Factors on Passengers’ Long-Distance Travel Mode Choices Based on Structural Equation Modeling," Sustainability, MDPI, vol. 9(11), pages 1-22, October.
    13. Chris De Gruyter & Graham Currie & Geoff Rose, 2016. "Sustainability Measures of Urban Public Transport in Cities: A World Review and Focus on the Asia/Middle East Region," Sustainability, MDPI, vol. 9(1), pages 1-21, December.
    14. Ken Butcher & Asad Kayani, 2008. "Waiting for service: modelling the effectiveness of service interventions," Service Business, Springer;Pan-Pacific Business Association, vol. 2(2), pages 153-165, June.
    15. Santos, Georgina & Maoh, Hanna & Potoglou, Dimitris & von Brunn, Thomas, 2013. "Factors influencing modal split of commuting journeys in medium-size European cities," Journal of Transport Geography, Elsevier, vol. 30(C), pages 127-137.
    16. Yáñez, M.F. & Raveau, S. & Ortúzar, J. de D., 2010. "Inclusion of latent variables in Mixed Logit models: Modelling and forecasting," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 744-753, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Andani, I Gusti Ayu & La Paix Puello, Lissy & Geurs, Karst, 2021. "Modelling effects of changes in travel time and costs of toll road usage on choices for residential location, route and travel mode across population segments in the Jakarta-Bandung region, Indonesia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 81-102.
    2. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    3. Di Ciommo, Floridea & Monzón, Andrés & Fernandez-Heredia, Alvaro, 2013. "Improving the analysis of road pricing acceptability surveys by using hybrid models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 302-316.
    4. Bergantino, Angela S. & Bierlaire, Michel & Catalano, Mario & Migliore, Marco & Amoroso, Salvatore, 2013. "Taste heterogeneity and latent preferences in the choice behaviour of freight transport operators," Transport Policy, Elsevier, vol. 30(C), pages 77-91.
    5. Andy S. Choi & Kelly S. Fielding, 2016. "Cultural Attitudes as WTP Determinants: A Revised Cultural Worldview Scale," Sustainability, MDPI, vol. 8(6), pages 1-18, June.
    6. Stephane Hess & Nesha Beharry-Borg, 2012. "Accounting for Latent Attitudes in Willingness-to-Pay Studies: The Case of Coastal Water Quality Improvements in Tobago," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 52(1), pages 109-131, May.
    7. Álvaro Fernández-Heredia & Sergio Jara-Díaz & Andrés Monzón, 2016. "Modelling bicycle use intention: the role of perceptions," Transportation, Springer, vol. 43(1), pages 1-23, January.
    8. Di Ciommo, Floridea & Comendador, Julio & López-Lambas, María Eugenia & Cherchi, Elisabetta & Ortúzar, Juan de Dios, 2014. "Exploring the role of social capital influence variables on travel behaviour," Transportation Research Part A: Policy and Practice, Elsevier, vol. 68(C), pages 46-55.
    9. Kim, Seheon & Rasouli, Soora, 2022. "The influence of latent lifestyle on acceptance of Mobility-as-a-Service (MaaS): A hierarchical latent variable and latent class approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 304-319.
    10. Choi, Andy S. & Ritchie, Brent W. & Papandrea, Franco & Bennett, Jeff, 2010. "Economic valuation of cultural heritage sites: A choice modeling approach," Tourism Management, Elsevier, vol. 31(2), pages 213-220.
    11. Guang Yang & Yan Han & Hao Gong & Tiantian Zhang, 2020. "Spatial-Temporal Response Patterns of Tourist Flow under Real-Time Tourist Flow Diversion Scheme," Sustainability, MDPI, vol. 12(8), pages 1-28, April.
    12. Ababio-Donkor, Augustus & Saleh, Wafaa & Fonzone, Achille, 2020. "The role of personal norms in the choice of mode for commuting," Research in Transportation Economics, Elsevier, vol. 83(C).
    13. Bouscasse, H., 2018. "Integrated choice and latent variable models: A literature review on mode choice," Working Papers 2018-07, Grenoble Applied Economics Laboratory (GAEL).
    14. Schmid, Basil & Becker, Felix & Axhausen, Kay W. & Widmer, Paul & Stein, Petra, 2023. "A simultaneous model of residential location, mobility tool ownership and mode choice using latent variables," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    15. Macea, Luis F. & Cantillo, Victor & Arellana, Julian, 2018. "Influence of attitudes and perceptions on deprivation cost functions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 112(C), pages 125-141.
    16. Choi, Andy S., 2011. "Implicit prices for longer temporary exhibitions in a heritage site and a test of preference heterogeneity: A segmentation-based approach," Tourism Management, Elsevier, vol. 32(3), pages 511-519.
    17. Jennifer Roberts & Gurleen Popli & Rosemary J. Harris, 2018. "Do environmental concerns affect commuting choices?: hybrid choice modelling with household survey data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(1), pages 299-320, January.
    18. Rungie, Cam & Scarpa, Riccardo & Thiene, Mara, 2014. "The influence of individuals in forming collective household preferences for water quality," Journal of Environmental Economics and Management, Elsevier, vol. 68(1), pages 161-174.
    19. Pan Shuangli & Zheng Guijun & Chen Qun, 2020. "The Psychological Decision-Making Process Model of Giving up Driving under Parking Constraints from the Perspective of Sustainable Traffic," Sustainability, MDPI, vol. 12(17), pages 1-19, September.
    20. Luis Márquez & Víctor Cantillo & Julián Arellana, 2020. "Assessing the influence of indicators’ complexity on hybrid discrete choice model estimates," Transportation, Springer, vol. 47(1), pages 373-396, February.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:10:y:2018:i:6:p:1996-:d:152333. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.