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Feasibility Analysis of Green Travel in Public Transportation: A Case Study of Wuhan

Author

Listed:
  • Junjun Zheng

    (Economics and Management School, Wuhan University, Wuhan 430072, China)

  • Yi Cheng

    (Economics and Management School, Wuhan University, Wuhan 430072, China)

  • Gang Ma

    (Economics and Management School, Wuhan University, Wuhan 430072, China)

  • Xue Han

    (Economics and Management School, Wuhan University, Wuhan 430072, China)

  • Liukai Yu

    (Economics and Management School, Wuhan University, Wuhan 430072, China)

Abstract

The demand to alleviate urban traffic and reduce air pollution puts forward high requirements for green travel in public transportation. Thus, study of the feasibility of urban green travel in public transportation is necessary. This study focuses on it from two aspects: City level by complex network and individual level by structural equation model. As for the former, point of interest data on the spatial distribution of urban public transportation in Wuhan city are quantitatively analyzed. Then, a complex network of public transportation in Wuhan is constructed by using the Space L method, and the network characteristics are analyzed. Results show that accessibility coverage is mainly concentrated in the central urban area, and two significant central nodes exist, namely, Linshi and Zhaohu stations. At the individual level, 354 valid questionnaires and the structural equation model were used to explore the factors affecting individual intention of public transportation. Behavioral perceptual outcome, behavioral attitudes, and subjective norms have positive influences on the behavioral intention of public transportation, among which the behavioral attitudes are the most significant, and the subjective norms had the lowest influence. Some suggestions are proposed for Wuhan to improve urban accessibility and for individuals to increase green travel in public transportation.

Suggested Citation

  • Junjun Zheng & Yi Cheng & Gang Ma & Xue Han & Liukai Yu, 2020. "Feasibility Analysis of Green Travel in Public Transportation: A Case Study of Wuhan," Sustainability, MDPI, vol. 12(16), pages 1-22, August.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:16:p:6531-:d:398234
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    References listed on IDEAS

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    1. Chinh Ho & Corinne Mulley & Chi-Hong Tsai & Stephen Ison & Sue Wiblin, 2017. "Area-wide travel plans—targeting strategies for greater participation in green travel initiatives: a case study of Rouse Hill Town Centre, NSW Australia," Transportation, Springer, vol. 44(2), pages 325-352, March.
    2. C. von Ferber & T. Holovatch & Yu. Holovatch & V. Palchykov, 2009. "Public transport networks: empirical analysis and modeling," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 68(2), pages 261-275, March.
    3. Alexander Y. Krylatov & Victor V. Zakharov, 2016. "Competitive Traffic Assignment in a Green Transit Network," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 18(02), pages 1-14, June.
    4. Han Jia & Andrea Appolloni & Yunqi Wang, 2017. "Green Travel: Exploring the Characteristics and Behavior Transformation of Urban Residents in China," Sustainability, MDPI, vol. 9(6), pages 1-14, June.
    5. Nurul Hidayah Muslim & Ali Keyvanfar & Arezou Shafaghat & Mu’azu Mohammed Abdullahi & Majid Khorami, 2018. "Green Driver: Travel Behaviors Revisited on Fuel Saving and Less Emission," Sustainability, MDPI, vol. 10(2), pages 1-30, January.
    6. Seaton, Katherine A. & Hackett, Lisa M., 2004. "Stations, trains and small-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(3), pages 635-644.
    7. Junjun Zheng & Mingyuan Xu & Runfa Li & Liukai Yu, 2019. "Research on Group Choice Behavior in Green Travel Based on Planned Behavior Theory and Complex Network," Sustainability, MDPI, vol. 11(14), pages 1-15, July.
    8. Bruderer Enzler, Heidi, 2017. "Air travel for private purposes. An analysis of airport access, income and environmental concern in Switzerland," Journal of Transport Geography, Elsevier, vol. 61(C), pages 1-8.
    9. Han Jia, 2018. "Green Travel Behavior in Urban China: Influencing Factors and their Effects," Sustainable Development, John Wiley & Sons, Ltd., vol. 26(4), pages 350-364, July.
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