IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i12p5090-d374998.html
   My bibliography  Save this article

Do Personal Norms Predict Citizens’ Acceptance of Green Transport Policies in China

Author

Listed:
  • Leibao Zhang

    (School of Public Finance and Taxation, Zhejiang University of Finance and Economics, Hangzhou 310018, China)

  • Liming Sheng

    (School of Public Finance and Taxation, Zhejiang University of Finance and Economics, Hangzhou 310018, China)

  • Wenyu Zhang

    (School of Information Management and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou 310018, China)

  • Shuai Zhang

    (School of Information Management and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou 310018, China)

Abstract

In order to solve the environmental problems caused by the increasing private car use in China, such as transport energy consumption, traffic congestion, and air pollution, many policy measures including car purchase taxes, restrictions on car use in the city center, and incentives to promote electric vehicles have been developed. By taking Hangzhou, a low-carbon metropolitan city in China, as an illustrative example, green transport policies have been proactively implemented in order to turn the metropolitan city into an ecologically livable city. However, citizens’ acceptance of comprehensive green transport policies has seldom been studied and explored, which is actually quite valuable information for implementing and assessing the effectiveness of green transport policies. This study presents a new integrated framework by extending the value belief norm (VBN) theory in order to explore the internal factors for predicting citizens’ acceptance of comprehensive green transport policies and other pro-environmental behaviors in the transport field. A survey on car use reduction was conducted among citizens in Hangzhou and a quantitative analysis was performed using a structural equation model (SEM) method. Results show that personal norms can successfully predict citizens’ acceptance of pull policies for reducing car use, while is less capable of predicting that of push ones. The theoretical implications of different pro-environmental behaviors are explained. This analysis may inspire policy makers to implement appropriate policies to encourage the public to use low-carbon transport in daily life.

Suggested Citation

  • Leibao Zhang & Liming Sheng & Wenyu Zhang & Shuai Zhang, 2020. "Do Personal Norms Predict Citizens’ Acceptance of Green Transport Policies in China," Sustainability, MDPI, vol. 12(12), pages 1-16, June.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:12:p:5090-:d:374998
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/12/5090/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/12/5090/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Seán Schmitz & Sophia Becker & Laura Weiand & Norman Niehoff & Frank Schwartzbach & Erika von Schneidemesser, 2019. "Determinants of Public Acceptance for Traffic-Reducing Policies to Improve Urban Air Quality," Sustainability, MDPI, vol. 11(14), pages 1-16, July.
    2. Wang, Rui, 2010. "Shaping urban transport policies in China: Will copying foreign policies work?," Transport Policy, Elsevier, vol. 17(3), pages 147-152, May.
    3. Lee Cronbach, 1951. "Coefficient alpha and the internal structure of tests," Psychometrika, Springer;The Psychometric Society, vol. 16(3), pages 297-334, September.
    4. Ünal, Ayça Berfu & Steg, Linda & Granskaya, Juliana, 2019. "“To support or not to support, that is the question”. Testing the VBN theory in predicting support for car use reduction policies inRussia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 73-81.
    5. Palos-Sanchez, Pedro & Saura, Jose Ramon & Martin-Velicia, Felix, 2019. "A study of the effects of programmatic advertising on users' concerns about privacy overtime," Journal of Business Research, Elsevier, vol. 96(C), pages 61-72.
    6. Yueling Xu & Wenyu Zhang & Haijun Bao & Shuai Zhang & Ying Xiang, 2019. "A SEM–Neural Network Approach to Predict Customers’ Intention to Purchase Battery Electric Vehicles in China’s Zhejiang Province," Sustainability, MDPI, vol. 11(11), pages 1-19, June.
    7. Letnik, Tomislav & Marksel, Maršenka & Luppino, Giuseppe & Bardi, Andrea & Božičnik, Stane, 2018. "Review of policies and measures for sustainable and energy efficient urban transport," Energy, Elsevier, vol. 163(C), pages 245-257.
    8. Jose J. Soto & Victor Cantillo & Julian Arellana, 2018. "Incentivizing alternative fuel vehicles: the influence of transport policies, attitudes and perceptions," Transportation, Springer, vol. 45(6), pages 1721-1753, November.
    9. Jarvis, Cheryl Burke & MacKenzie, Scott B & Podsakoff, Philip M, 2003. "A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(2), pages 199-218, September.
    10. 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.
    11. Katarzyna Nosal Hoy & Katarzyna Solecka & Andrzej Szarata, 2019. "The Application of the Multiple Criteria Decision Aid to Assess Transport Policy Measures Focusing on Innovation," Sustainability, MDPI, vol. 11(5), pages 1-23, March.
    12. Nordfjærn, Trond & Rundmo, Torbjørn, 2015. "Environmental norms, transport priorities and resistance to change associated with acceptance of push measures in transport," Transport Policy, Elsevier, vol. 44(C), pages 1-8.
    13. Leibao Zhang & Yanli Fan & Wenyu Zhang & Shuai Zhang, 2019. "Extending the Theory of Planned Behavior to Explain the Effects of Cognitive Factors across Different Kinds of Green Products," Sustainability, MDPI, vol. 11(15), pages 1-17, August.
    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. Xue Wang & Suwei Feng & Tianyi Tang, 2023. "Acceptability toward Policy Mix: Impact of Low-Carbon Travel Intention, Fairness, and Effectiveness," Sustainability, MDPI, vol. 15(20), pages 1-22, October.
    2. Ming-Yeu Wang & Shih-Mao Lin, 2020. "Intervention Strategies on the Wastewater Treatment Behavior of Swine Farmers: An Extended Model of the Theory of Planned Behavior," Sustainability, MDPI, vol. 12(17), pages 1-20, August.
    3. Ellen Matthies & Theresa de Paula Sieverding & Lukas Engel & Anke Blöbaum, 2023. "Simple and Smart: Investigating Two Heuristics That Guide the Intention to Engage in Different Climate-Change-Mitigation Behaviors," Sustainability, MDPI, vol. 15(9), pages 1-27, April.
    4. Weitao Zhang & Adaviah Mas’od & Zuraidah Sulaiman, 2022. "Moderating Effect of Collectivism on Chinese Consumers’ Intention to Adopt Electric Vehicles—An Adoption of VBN Framework," Sustainability, MDPI, vol. 14(19), pages 1-35, September.

    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. Xue Wang & Suwei Feng & Tianyi Tang, 2023. "Acceptability toward Policy Mix: Impact of Low-Carbon Travel Intention, Fairness, and Effectiveness," Sustainability, MDPI, vol. 15(20), pages 1-22, October.
    2. Tomislav Letnik & Katja Hanžič & Giuseppe Luppino & Matej Mencinger, 2022. "Impact of Logistics Trends on Freight Transport Development in Urban Areas," Sustainability, MDPI, vol. 14(24), pages 1-18, December.
    3. Mark Heitmann & Andreas Herrmann, 2007. "Die Zufriedenheit mit dem Entscheidungsprozess als Determinante der Kundenbindung," Schmalenbach Journal of Business Research, Springer, vol. 59(5), pages 530-566, August.
    4. Immacolata Di Napoli & Pasquale Dolce & Caterina Arcidiacono, 2019. "Community Trust: A Social Indicator Related to Community Engagement," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 145(2), pages 551-579, September.
    5. 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.
    6. John S. Hill & Myung-Su Chae & Jinseo Park, 2012. "The Effects of Geography and Infrastructure on Economic Development and International Business Involvement," Journal of Infrastructure Development, India Development Foundation, vol. 4(2), pages 91-113, December.
    7. García, Juan A. & Gómez, Mar & Molina, Arturo, 2012. "A destination-branding model: An empirical analysis based on stakeholders," Tourism Management, Elsevier, vol. 33(3), pages 646-661.
    8. Rafael R. Ramírez & Leanne Seeliger & Filippo Di Pietro, 2016. "Price, Virtues, Principles: How to Discern What Inspires Best Practices in Water Management? A Case Study about Small Farmers in the Yucatan Peninsula of Mexico," Sustainability, MDPI, vol. 8(4), pages 1-16, April.
    9. Sönke Albers & Lutz Hildebrandt, 2006. "Methodische Probleme bei der Erfolgsfaktorenforschung — Messfehler, formative versus reflektive Indikatoren und die Wahl des Strukturgleichungs-Modells," Schmalenbach Journal of Business Research, Springer, vol. 58(1), pages 2-33, February.
    10. Sajtos, Laszlo & Magyar, Bertalan, 2016. "Auxiliary theories as translation mechanisms for measurement model specification," Journal of Business Research, Elsevier, vol. 69(8), pages 3186-3191.
    11. Salim Moussa, 2016. "A Comment on the Estimation of the Reliability of Multidimensional Marketing Constructs: A Store Personality Scale Application," Global Business Review, International Management Institute, vol. 17(5), pages 1125-1144, October.
    12. Georg Fassott, 2006. "Operationalisierung latenter Variablen in Strukturgleichungsmodellen: Eine Standortbestimmung," Schmalenbach Journal of Business Research, Springer, vol. 58(1), pages 67-88, February.
    13. Yueling Xu & Wenyu Zhang & Haijun Bao & Shuai Zhang & Ying Xiang, 2019. "A SEM–Neural Network Approach to Predict Customers’ Intention to Purchase Battery Electric Vehicles in China’s Zhejiang Province," Sustainability, MDPI, vol. 11(11), pages 1-19, June.
    14. Francesco Giacobbe & Zoltan Matolcsy & James Wakefield & Tom Smith, 2016. "An investigation of wholly-owned foreign subsidiary control through transaction cost economics theory," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 56(4), pages 1041-1070, December.
    15. Salim Moussa, 2016. "A two-step item response theory procedure for a better measurement of marketing constructs," Journal of Marketing Analytics, Palgrave Macmillan, vol. 4(1), pages 28-50, March.
    16. Mehdizadeh, Milad & Zavareh, Mohsen Fallah & Nordfjaern, Trond, 2019. "Mono- and multimodal green transport use on university trips during winter and summer: Hybrid choice models on the norm-activation theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 317-332.
    17. Ohiomah, Alhassan & Andreev, Pavel & Benyoucef, Morad & Hood, David, 2019. "The role of lead management systems in inside sales performance," Journal of Business Research, Elsevier, vol. 102(C), pages 163-177.
    18. Huete-Alcocer, Nuria & Hernandez-Rojas, Ricardo David, 2022. "Do SARS-CoV-2 safety measures affect visitors experience of traditional gastronomy, destination image and loyalty to a World Heritage City?," Journal of Retailing and Consumer Services, Elsevier, vol. 69(C).
    19. Coltman, Tim & Devinney, Timothy M. & Midgley, David F. & Venaik, Sunil, 2008. "Formative versus reflective measurement models: Two applications of formative measurement," Journal of Business Research, Elsevier, vol. 61(12), pages 1250-1262, December.
    20. Ziwen Ling & Christopher R. Cherry & Yi Wen, 2021. "Determining the Factors That Influence Electric Vehicle Adoption: A Stated Preference Survey Study in Beijing, China," Sustainability, MDPI, vol. 13(21), pages 1-22, October.

    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:12:y:2020:i:12:p:5090-:d:374998. 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.