IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i16p12610-d1221169.html
   My bibliography  Save this article

The Impacts of Low-Carbon Incentives and Carbon-Reduction Awareness on Airport Ground Access Mode Choice under Travel Time Uncertainty: A Hybrid CPT-MNL Model

Author

Listed:
  • Mengru Shao

    (Urban Planning and Transportation, Department of the Built Environment, Eindhoven University of Technology, 5600MB Eindhoven, The Netherlands)

  • Chao Chen

    (State Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, School of Automotive Engineering, Dalian University of Technology, Dalian 116024, China)

  • Qingchang Lu

    (School of Electronics and Control Engineering, Chang’an University, Xi’an 710064, China)

  • Xinyu Zuo

    (School of Electronics and Control Engineering, Chang’an University, Xi’an 710064, China)

  • Xueling Liu

    (Don School, International Education College, Shandong Jiaotong University, Jinan 250357, China)

  • Xiaoning Gu

    (State Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, School of Automotive Engineering, Dalian University of Technology, Dalian 116024, China)

Abstract

Developing strategies to incentivize travelers towards adopting sustainable mobility options is one of the effective approaches to mitigate carbon emissions. Using Xi’an Xianyang International Airport as a case study, this study aims to explore the effects of low-carbon incentives and carbon-reduction awareness on airport ground access mode choices. In addition, to account for the complex road environment, an innovative stated preference choice experiment was designed, integrating the factor of travel time uncertainty. Then, a hybrid cumulative prospect theory–Multinomial Logit (CPT-MNL) model was also developed. The estimated results revealed that travelers increasingly prioritize emissions reduction and consciously prefer sustainable mobility options to reach the airport. Furthermore, the potential of low-carbon incentives to encourage public transport usage over private vehicles has been highlighted. Notably, travel time uncertainty had a significant impact on the choice of private cars. When the travel time to the airport is uncertain, travelers exhibit a greater inclination towards selecting public transport. The findings of this study offer nuanced insights for transportation authorities, aiding them in fostering the adoption of sustainable mobility options and achieving carbon reduction objectives.

Suggested Citation

  • Mengru Shao & Chao Chen & Qingchang Lu & Xinyu Zuo & Xueling Liu & Xiaoning Gu, 2023. "The Impacts of Low-Carbon Incentives and Carbon-Reduction Awareness on Airport Ground Access Mode Choice under Travel Time Uncertainty: A Hybrid CPT-MNL Model," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:16:p:12610-:d:1221169
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/16/12610/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/16/12610/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    2. Fanyuan Deng & Zhaofeng Lv & Lijuan Qi & Xiaotong Wang & Mengshuang Shi & Huan Liu, 2020. "A big data approach to improving the vehicle emission inventory in China," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
    3. Jia Guo & Tao Feng & Harry J. P. Timmermans, 2020. "Modeling co-dependent choice of workplace, residence and commuting mode using an error component mixed logit model," Transportation, Springer, vol. 47(2), pages 911-933, April.
    4. Quiggin, John, 1982. "A theory of anticipated utility," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 323-343, December.
    5. Brand, Christian & Anable, Jillian & Tran, Martino, 2013. "Accelerating the transformation to a low carbon passenger transport system: The role of car purchase taxes, feebates, road taxes and scrappage incentives in the UK," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 132-148.
    6. Jou, Rong-Chang & Hensher, David A. & Hsu, Tzu-Lan, 2011. "Airport ground access mode choice behavior after the introduction of a new mode: A case study of Taoyuan International Airport in Taiwan," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(3), pages 371-381, May.
    7. Chang, Yu-Chun, 2013. "Factors affecting airport access mode choice for elderly air passengers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 57(C), pages 105-112.
    8. Jou, Rong-Chang & Chen, Ke-Hong, 2013. "An application of cumulative prospect theory to freeway drivers’ route choice behaviours," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 123-131.
    9. Aleksandra Colovic & Salvatore Gabriele Pilone & Katarina Kukić & Milica Kalić & Slavica Dožić & Danica Babić & Michele Ottomanelli, 2022. "Airport Access Mode Choice: Analysis of Passengers’ Behavior in European Countries," Sustainability, MDPI, vol. 14(15), pages 1-23, July.
    10. Geng, Jichao & Long, Ruyin & Chen, Hong, 2016. "Impact of information intervention on travel mode choice of urban residents with different goal frames: A controlled trial in Xuzhou, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 134-147.
    11. Alhussein, Saad N., 2011. "Analysis of ground access modes choice King Khaled International Airport, Riyadh, Saudi Arabia," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1361-1367.
    12. Gokasar, Ilgin & Gunay, Gurkan, 2017. "Mode choice behavior modeling of ground access to airports: A case study in Istanbul, Turkey," Journal of Air Transport Management, Elsevier, vol. 59(C), pages 1-7.
    13. Hensher, David A., 2017. "Future bus transport contracts under a mobility as a service (MaaS) regime in the digital age: Are they likely to change?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 98(C), pages 86-96.
    14. Satoshi Fujii & Ryuichi Kitamura, 2003. "What does a one-month free bus ticket do to habitual drivers? An experimental analysis of habit and attitude change," Transportation, Springer, vol. 30(1), pages 81-95, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xuanwei Zhao & Jinsong Han, 2025. "How Is Transportation Sector Low-Carbon (TSLC) Research Developing After the Paris Agreement (PA)? A Decade Review," Sustainability, MDPI, vol. 17(5), pages 1-28, March.

    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. Aleksandra Colovic & Salvatore Gabriele Pilone & Katarina Kukić & Milica Kalić & Slavica Dožić & Danica Babić & Michele Ottomanelli, 2022. "Airport Access Mode Choice: Analysis of Passengers’ Behavior in European Countries," Sustainability, MDPI, vol. 14(15), pages 1-23, July.
    2. Kristoffersson, Ida & Berglund , Svante, 2020. "Modelling connection trips to long-distance travel : state-of-the-art and directions for future research," Papers 2020:5, Research Programme in Transport Economics.
    3. Silva, Henrique Guilherme Montes & Guterres, Marcelo Xavier & Bandeira, Michelle Carvalho Galvão da Silva Pinto & Alves, Cláudio Jorge Pinto & Sonáglio, Cláudio Abano, 2022. "The role of security in passengers' airport ground access choices: A statistical evaluation," Journal of Air Transport Management, Elsevier, vol. 103(C).
    4. Zhou, Yuyang & Wang, Peiyu & Zheng, Shuyan & Zhao, Minhe & Lam, William H.K. & Chen, Anthony & Sze, N.N. & Chen, Yanyan, 2024. "Modeling dynamic travel mode choices using cumulative prospect theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    5. Yazdanpanah, Mahdi & Hosseinlou, Mansour Hadji, 2016. "The influence of personality traits on airport public transport access mode choice: A hybrid latent class choice modeling approach," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 147-163.
    6. Gao, Kun & Sun, Lijun & Yang, Ying & Meng, Fanyu & Qu, Xiaobo, 2021. "Cumulative prospect theory coupled with multi-attribute decision making for modeling travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 1-21.
    7. Bergantino, Angela Stefania & Madio, Leonardo, 2017. "High-speed rail, inter-modal substitution and willingness-to-pay. A stated preference analysis for the ‘Bari-Rome’," Working Papers 17_6, SIET Società Italiana di Economia dei Trasporti e della Logistica.
    8. Danwen Bao & Shijia Tian & Rui Li & Tianxuan Zhang & Ting Zhu, 2022. "Multi-Objective Decision Method for Airport Landside Rapid Transit Network Design," Networks and Spatial Economics, Springer, vol. 22(4), pages 767-801, December.
    9. Gunay, Gurkan & Gokasar, Ilgin, 2021. "Market segmentation analysis for airport access mode choice modeling with mixed logit," Journal of Air Transport Management, Elsevier, vol. 91(C).
    10. Bergantino, Angela Stefania & Capurso, Mauro & Hess, Stephane, 2020. "Modelling regional accessibility to airports using discrete choice models: An application to a system of regional airports," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 855-871.
    11. Zaidan, Esmat & Abulibdeh, Ammar, 2018. "Modeling ground access mode choice behavior for Hamad International Airport in the 2022 FIFA World Cup city, Doha, Qatar," Journal of Air Transport Management, Elsevier, vol. 73(C), pages 32-45.
    12. Wang, Zi-Jia & Jia, Hui-Hui & Dai, Fangzhou & Diao, Mi, 2022. "Understanding the ground access and airport choice behavior of air passengers using transit payment transaction data," Transport Policy, Elsevier, vol. 127(C), pages 179-190.
    13. Bergantino, Angela Stefania & Capurso, Mauro & Hess, Stephane, 2017. "Modelling regional accessibility towards airports using discrete choice models: an application to the Apulian airport system," Working Papers 17_4, SIET Società Italiana di Economia dei Trasporti e della Logistica.
    14. Laurino, Antonio & Beria, Paolo & Debernardi, Andrea & Ferrara, Emanuele, 2019. "Accessibility to Italian remote regions: Comparison among different transport alternatives," Transport Policy, Elsevier, vol. 83(C), pages 127-138.
    15. Shi, Yun & Cui, Xiangyu & Zhou, Xunyu, 2020. "Beta and Coskewness Pricing: Perspective from Probability Weighting," SocArXiv 5rqhv, Center for Open Science.
    16. Massimiliano Amarante & Mario Ghossoub & Edmund Phelps, 2012. "Contracting for Innovation under Knightian Uncertainty," Cahiers de recherche 18-2012, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    17. Mohammed Abdellaoui & Olivier L’Haridon & Horst Zank, 2010. "Separating curvature and elevation: A parametric probability weighting function," Journal of Risk and Uncertainty, Springer, vol. 41(1), pages 39-65, August.
    18. H. Peter Boswijk & Jeroen Dalderop & Roger J. A. Laeven & Niels Marijnen, 2025. "Semiparametric Estimation of Probability Weighting Functions Implicit in Option Prices," Tinbergen Institute Discussion Papers 25-022/III, Tinbergen Institute.
    19. Daniel Woods & Mustafa Abdallah & Saurabh Bagchi & Shreyas Sundaram & Timothy Cason, 2022. "Network defense and behavioral biases: an experimental study," Experimental Economics, Springer;Economic Science Association, vol. 25(1), pages 254-286, February.
    20. Xue Dong He & Sang Hu & Jan Obłój & Xun Yu Zhou, 2017. "Technical Note—Path-Dependent and Randomized Strategies in Barberis’ Casino Gambling Model," Operations Research, INFORMS, vol. 65(1), pages 97-103, 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:15:y:2023:i:16:p:12610-:d:1221169. 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.