IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i6p5375-d1100394.html
   My bibliography  Save this article

Analysis of Key Factors Affecting Low-Carbon Travel Behaviors of Urban Residents in Developing Countries: A Case Study in Zhenjiang, China

Author

Listed:
  • Pengfei Zhao

    (School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 102616, China)

  • Lingxiang Wei

    (School of Defense Engineering, Army Engineering University of PLA, Nanjing 210007, China
    School of Materials Science and Engineering, Yancheng Institute of Technology, Yancheng 224051, China)

  • Dong Pan

    (School of Automobile and Transportation and Engineering, Hefei University of Technology, Hefei 230009, China)

  • Jincheng Yang

    (School of Materials Science and Engineering, Yancheng Institute of Technology, Yancheng 224051, China)

  • Yuchuan Ji

    (School of Materials Science and Engineering, Yancheng Institute of Technology, Yancheng 224051, China)

Abstract

The transport sector accounts for 23% of global carbon emissions, the second largest after electricity and heat generation. Low-carbon travel, such as walking, cycling, and use of public transit, has become an effective way to reduce transportation-related emissions, however, what factors and how they affect low-carbon travel behavior remain unclear. This paper analyzes the key factors that affect the low-carbon travel behavior of urban residents by exploring 26 potential correlation indicators. Low-carbon travel survey data of urban residents in Zhenjiang, China are used as an example. Five factors derived from 26 indicators were identified and named as key factors influencing urban low-carbon travel behavior: traveler personal attributes (contribution rate 31.646%), user satisfaction with travel processes (contribution rate 17.438%), attitude towards low-carbon travel and environmental awareness (16.090%), the level of public transportation system development (10.793%), and overall attributes of travelers’ family (10.561%). The results provide a theoretical basis for the development and implementation of novel urban low-carbon travel concepts in the future.

Suggested Citation

  • Pengfei Zhao & Lingxiang Wei & Dong Pan & Jincheng Yang & Yuchuan Ji, 2023. "Analysis of Key Factors Affecting Low-Carbon Travel Behaviors of Urban Residents in Developing Countries: A Case Study in Zhenjiang, China," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5375-:d:1100394
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/6/5375/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/6/5375/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marsden, Greg & Docherty, Iain, 2013. "Insights on disruptions as opportunities for transport policy change," Transportation Research Part A: Policy and Practice, Elsevier, vol. 51(C), pages 46-55.
    2. Bristow, Abigail L. & Tight, Miles & Pridmore, Alison & May, Anthony D., 2008. "Developing pathways to low carbon land-based passenger transport in Great Britain by 2050," Energy Policy, Elsevier, vol. 36(9), pages 3427-3435, September.
    3. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    4. Xinyu Chen & Hongcai Zhang & Zhiwei Xu & Chris P. Nielsen & Michael B. McElroy & Jiajun Lv, 2018. "Impacts of fleet types and charging modes for electric vehicles on emissions under different penetrations of wind power," Nature Energy, Nature, vol. 3(5), pages 413-421, May.
    5. Heesup Han & Amr Al-Ansi & Bee-Lia Chua & Beenish Tariq & Aleksandar Radic & Su-hyun Park, 2020. "The Post-Coronavirus World in the International Tourism Industry: Application of the Theory of Planned Behavior to Safer Destination Choices in the Case of US Outbound Tourism," IJERPH, MDPI, vol. 17(18), pages 1-15, September.
    6. Yang, Yuan & Wang, Can & Liu, Wenling & Zhou, Peng, 2018. "Understanding the determinants of travel mode choice of residents and its carbon mitigation potential," Energy Policy, Elsevier, vol. 115(C), pages 486-493.
    7. Marsden, Greg & Mullen, Caroline & Bache, Ian & Bartle, Ian & Flinders, Matt, 2014. "Carbon reduction and travel behaviour: Discourses, disputes and contradictions in governance," Transport Policy, Elsevier, vol. 35(C), pages 71-78.
    8. Foran, Barney, 2011. "Low carbon transition options for Australia," Ecological Modelling, Elsevier, vol. 223(1), pages 72-80.
    9. Schwanen, Tim & Banister, David & Anable, Jillian, 2012. "Rethinking habits and their role in behaviour change: the case of low-carbon mobility," Journal of Transport Geography, Elsevier, vol. 24(C), pages 522-532.
    10. Steffen Unkel & Nickolay T. Trendafilov, 2010. "Simultaneous Parameter Estimation in Exploratory Factor Analysis: An Expository Review," International Statistical Review, International Statistical Institute, vol. 78(3), pages 363-382, December.
    11. Yan, Xiaoyu & Crookes, Roy J., 2009. "Reduction potentials of energy demand and GHG emissions in China's road transport sector," Energy Policy, Elsevier, vol. 37(2), pages 658-668, February.
    12. Li, Jun, 2011. "Decoupling urban transport from GHG emissions in Indian cities--A critical review and perspectives," Energy Policy, Elsevier, vol. 39(6), pages 3503-3514, June.
    13. Law, Teik Hua & Daud, Mohd Shazwan & Hamid, Hussain & Haron, Nuzul Azam, 2017. "Development of safety performance index for intercity buses: An exploratory factor analysis approach," Transport Policy, Elsevier, vol. 58(C), pages 46-52.
    14. Tang, Shaolong & Wang, Wenjie & Yan, Hong & Hao, Gang, 2015. "Low carbon logistics: Reducing shipment frequency to cut carbon emissions," International Journal of Production Economics, Elsevier, vol. 164(C), pages 339-350.
    15. Bi, Kexin & Huang, Ping & Wang, Xiangxiang, 2016. "Innovation performance and influencing factors of low-carbon technological innovation under the global value chain: A case of Chinese manufacturing industry," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 275-284.
    16. Pison, Greet & Rousseeuw, Peter J. & Filzmoser, Peter & Croux, Christophe, 2003. "Robust factor analysis," Journal of Multivariate Analysis, Elsevier, vol. 84(1), pages 145-172, January.
    17. Liobikienė, Genovaitė & Mandravickaitė, Justina & Bernatonienė, Jurga, 2016. "Theory of planned behavior approach to understand the green purchasing behavior in the EU: A cross-cultural study," Ecological Economics, Elsevier, vol. 125(C), pages 38-46.
    18. Basto, Mário & Pereira, José Manuel, 2012. "An SPSS R-Menu for Ordinal Factor Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 46(i04).
    19. Chen, Hong & Long, Ruyin & Niu, Wenjing & Feng, Qun & Yang, Ranran, 2014. "How does individual low-carbon consumption behavior occur? – An analysis based on attitude process," Applied Energy, Elsevier, vol. 116(C), pages 376-386.
    20. Phdungsilp, Aumnad, 2010. "Integrated energy and carbon modeling with a decision support system: Policy scenarios for low-carbon city development in Bangkok," Energy Policy, Elsevier, vol. 38(9), pages 4808-4817, September.
    21. Hafner, Rebecca J. & Walker, Ian & Verplanken, Bas, 2017. "Image, not environmentalism: A qualitative exploration of factors influencing vehicle purchasing decisions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 97(C), pages 89-105.
    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. Liu, Diyi & Du, Huibin & Southworth, Frank & Ma, Shoufeng, 2017. "The influence of social-psychological factors on the intention to choose low-carbon travel modes in Tianjin, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 105(C), pages 42-53.
    2. Frazen Tolentino-Zondervan & Enide Bogers & Luc van de Sande, 2021. "A Managerial and Behavioral Approach in Aligning Stakeholder Goals in Sustainable Last Mile Logistics: A Case Study in the Netherlands," Sustainability, MDPI, vol. 13(8), pages 1-17, April.
    3. Geng, Jichao & Long, Ruyin & Chen, Hong & Li, Wenbo, 2017. "Exploring the motivation-behavior gap in urban residents’ green travel behavior: A theoretical and empirical study," Resources, Conservation & Recycling, Elsevier, vol. 125(C), pages 282-292.
    4. Cass, Noel & Faulconbridge, James, 2016. "Commuting practices: New insights into modal shift from theories of social practice," Transport Policy, Elsevier, vol. 45(C), pages 1-14.
    5. Kamruzzaman, Md. & Baker, Douglas & Washington, Simon & Turrell, Gavin, 2013. "Residential dissonance and mode choice," Journal of Transport Geography, Elsevier, vol. 33(C), pages 12-28.
    6. Borhan, Muhamad Nazri & Ibrahim, Ahmad Nazrul Hakimi & Miskeen, Manssour A. Abdulasalm, 2019. "Extending the theory of planned behaviour to predict the intention to take the new high-speed rail for intercity travel in Libya: Assessment of the influence of novelty seeking, trust and external inf," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 373-384.
    7. Chaojun Li & Xinjia Huang, 2022. "How Does COVID-19 Risk Perception Affect Wellness Tourist Intention: Findings on Chinese Generation Z," Sustainability, MDPI, vol. 15(1), pages 1-20, December.
    8. Meles, Tensay Hadush & Ryan, Lisa & Mukherjee, Sanghamitra C., 2022. "Heterogeneity in preferences for renewable home heating systems among Irish households," Applied Energy, Elsevier, vol. 307(C).
    9. Yadav, Rambalak & Pathak, Govind S., 2017. "Determinants of Consumers' Green Purchase Behavior in a Developing Nation: Applying and Extending the Theory of Planned Behavior," Ecological Economics, Elsevier, vol. 134(C), pages 114-122.
    10. Changjoon Lee & Soyoun Lim & Byoungchun Ha, 2021. "Green Supply Chain Management and Its Impact on Consumer Purchase Decision as a Marketing Strategy: Applying the Theory of Planned Behavior," Sustainability, MDPI, vol. 13(19), pages 1-16, October.
    11. Xiaojian Hu & Nan Wu & Nuo Chen, 2021. "Young People’s Behavioral Intentions towards Low-Carbon Travel: Extending the Theory of Planned Behavior," IJERPH, MDPI, vol. 18(5), pages 1-15, February.
    12. Busch-Geertsema, Annika & Lanzendorf, Martin, 2017. "From university to work life – Jumping behind the wheel? Explaining mode change of students making the transition to professional life," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 181-196.
    13. Taneja, Shilpa & Ali, Liaqat, 2021. "Determinants of customers’ intentions towards environmentally sustainable banking: Testing the structural model," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    14. Licheng Sun & Qunwei Wang & Shilong Ge, 2018. "Urban resident energy-saving behavior: a case study under the A2SC framework," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(2), pages 515-536, March.
    15. Gregory Owen Thomas & Wouter Poortinga & Elena Sautkina, 2016. "Habit Discontinuity, Self-Activation, and the Diminishing Influence of Context Change: Evidence from the UK Understanding Society Survey," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-16, April.
    16. Heydari, Ali & Laroche, Michel & Paulin, Michèle & Richard, Marie-Odile, 2021. "Hofstede's individual-level indulgence dimension: Scale development and validation," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    17. Keren Kaplan Mintz & Jenny Kurman, 2020. "A cross-cultural perspective on facilitators of recycling," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(7), pages 6627-6643, October.
    18. Chunyao Deng & Zhenwu Shi & Yanli Zhang & Jinru Wang, 2025. "Analysis of Green Travel Choice Behavior of Residents in Central Urban Areas: Applying the Theory of Planned Behavior and Stimulus–Organism–Response Model," Sustainability, MDPI, vol. 17(5), pages 1-24, March.
    19. Xiaoyun Zhang & Feng Dong, 2020. "Why Do Consumers Make Green Purchase Decisions? Insights from a Systematic Review," IJERPH, MDPI, vol. 17(18), pages 1-25, September.
    20. Cindy G Grappe & Cindy Lombart & Didier Louis & Fabien Durif, 2021. ""Not tested on animals": How consumers react to cruelty-free cosmetics proposed by manufacturers and retailers?," Post-Print hal-03379593, HAL.

    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:6:p:5375-:d:1100394. 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.