IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i5p2833-d511384.html
   My bibliography  Save this article

Research on Residents’ Willingness to Pay for Promoting the Green Development of Resource-Based Cities: A Case Study in Chifeng

Author

Listed:
  • Meng Zhao

    (State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Xueqi Zhang

    (State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Chenxing Wang

    (State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Yu Zhao

    (State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Gang Wu

    (State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Resource-based cities have made significant contributions to the development of human beings but have also accumulated various unsustainable ills. For this reason, China put forward the strategy of green development. This study used questionnaires to explore the extent of residents’ understanding of regional green development in Chifeng City and their willingness to support local green development, and further analyzed the differences in the residents’ attitudes and willingness to pay (WTP) with different socioeconomic characteristics. The results showed that most of the respondents supported the green development strategy and demonstrated a strong willingness to participate in regional green development investment. According to calculations, the per capita WTP for green development in Chifeng is 45.05 yuan/a (about 7 dollars/a, 5.7 euros/a). Urban residents, government employees, and well-educated respondents were more inclined to support regional green development and showed a greater WTP. Elderly and female respondents agreed more with the government’s green development promotion, while the young and middle-aged populations and men tended to have higher green development expenditures. The respondents’ annual income difference was reflected in the amounts of residents’ WTP. This study also offered scientific support and policy assistance to promote the environmental protection work from government-led to public participation.

Suggested Citation

  • Meng Zhao & Xueqi Zhang & Chenxing Wang & Yu Zhao & Gang Wu, 2021. "Research on Residents’ Willingness to Pay for Promoting the Green Development of Resource-Based Cities: A Case Study in Chifeng," Sustainability, MDPI, vol. 13(5), pages 1-24, March.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:5:p:2833-:d:511384
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/5/2833/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/5/2833/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zeng, Lijun & Guo, Jiaqi & Wang, Bingcheng & Lv, Jun & Wang, Qin, 2019. "Analyzing sustainability of Chinese coal cities using a decision tree modeling approach," Resources Policy, Elsevier, vol. 64(C).
    2. Xingwei Li & Jianguo Du & Hongyu Long, 2018. "A Comparative Study of Chinese and Foreign Green Development from the Perspective of Mapping Knowledge Domains," Sustainability, MDPI, vol. 10(12), pages 1-30, November.
    3. Jonas Schmidt & Tammo H. A. Bijmolt, 2020. "Accurately measuring willingness to pay for consumer goods: a meta-analysis of the hypothetical bias," Journal of the Academy of Marketing Science, Springer, vol. 48(3), pages 499-518, May.
    4. Özdemir, Semra & Johnson, F. Reed & Hauber, A. Brett, 2009. "Hypothetical bias, cheap talk, and stated willingness to pay for health care," Journal of Health Economics, Elsevier, vol. 28(4), pages 894-901, July.
    5. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    6. David Littlewood, 2014. "‘Cursed’ Communities? Corporate Social Responsibility (CSR), Company Towns and the Mining Industry in Namibia," Journal of Business Ethics, Springer, vol. 120(1), pages 39-63, March.
    7. Gina Waterfield & Scott Kaplan & David Zilberman, 2020. "Willingness to Pay versus Willingness to Vote: Consumer and Voter Avoidance of Genetically Modified Foods," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 505-524, March.
    8. Don L. Coursey & John L. Hovis & William D. Schulze, 1987. "The Disparity Between Willingness to Accept and Willingness to Pay Measures of Value," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(3), pages 679-690.
    9. Li, Li & Lei, Yalin & Wu, Sanmang & He, Chunyan & Yan, Dan, 2018. "Study on the coordinated development of economy, environment and resource in coal-based areas in Shanxi Province in China: Based on the multi-objective optimization model," Resources Policy, Elsevier, vol. 55(C), pages 80-86.
    10. Li, Huijuan & Long, Ruyin & Chen, Hong, 2013. "Economic transition policies in Chinese resource-based cities: An overview of government efforts," Energy Policy, Elsevier, vol. 55(C), pages 251-260.
    11. Emma J. Frew & David K. Whynes & Jane L. Wolstenholme, 2003. "Eliciting Willingness to Pay: Comparing Closed-Ended with Open-Ended and Payment Scale Formats," Medical Decision Making, , vol. 23(2), pages 150-159, March.
    12. Tian, Xu & Yu, Xiaohua & Holst, Rainer, 2011. "Applying the payment card approach to estimate the WTP for green food in China," IAMO Forum 2011: Will the "BRICs Decade" Continue? – Prospects for Trade and Growth 23, Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO).
    13. S. V. Ciriacy-Wantrup, 1947. "Capital Returns from Soil-Conservation Practices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 29(4_Part_II), pages 1181-1196.
    14. Edoh Y. Amiran & Daniel A. Hagen, 2003. "Willingness To Pay and Willingness To Accept: How Much Can They Differ? Comment," American Economic Review, American Economic Association, vol. 93(1), pages 458-463, March.
    15. Sachs, Jeffrey D. & Warner, Andrew M., 2001. "The curse of natural resources," European Economic Review, Elsevier, vol. 45(4-6), pages 827-838, May.
    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, Liming & Li, Huaqing & Shen, Wenlong & Zhao, Xiangyi & Liu, Zhe & Zheng, Zhixue & Hu, Jie & Meng, Shuo, 2023. "Applying GeoDetector to disentangle the contributions of the 4-As evaluation indicators to the spatial differentiation of coal resource security," Energy Policy, Elsevier, vol. 173(C).
    2. Yuxin Meng & Lu Liu & Jianlong Wang & Qiying Ran & Xiaodong Yang & Jianliang Shen, 2021. "Assessing the Impact of the National Sustainable Development Planning of Resource-Based Cities Policy on Pollution Emission Intensity: Evidence from 270 Prefecture-Level Cities in China," Sustainability, MDPI, vol. 13(13), pages 1-20, June.

    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. Zeng, Lijun & Wang, Jinfeng & Zhang, Jinshuo & Lv, Jun & Cui, Wei, 2020. "New Urbanization paths in mineral resource abundant regions in China: A three-dimensional cube framework," Resources Policy, Elsevier, vol. 68(C).
    2. Li, Mengxu & Liu, Jianghua & Chen, Yang & Yang, Zhijiu, 2023. "Can sustainable development strategy reduce income inequality in resource-based regions? A natural resource dependence perspective," Resources Policy, Elsevier, vol. 81(C).
    3. Yao Hu & Tai-Hua Yan & Feng-Wen Chen, 2020. "Energy and Environment Performance of Resource-Based Cities in China: A Non-Parametric Approach for Estimating Hyperbolic Distance Function," IJERPH, MDPI, vol. 17(13), pages 1-23, July.
    4. Li, Qiangyi & Zeng, Fu'e & Liu, Shaohui & Yang, Mian & Xu, Fei, 2021. "The effects of China's sustainable development policy for resource-based cities on local industrial transformation," Resources Policy, Elsevier, vol. 71(C).
    5. Jung-Eun Kim & Jungsung Yeo, 2010. "Valuation of Consumers’ Personal Information: A South Korean Example," Journal of Family and Economic Issues, Springer, vol. 31(3), pages 297-306, September.
    6. Chan, Kai-Ying & Oerlemans, Leon A.G. & Volschenk, Jako, 2015. "On the construct validity of measures of willingness to pay for green electricity: Evidence from a South African case," Applied Energy, Elsevier, vol. 160(C), pages 321-328.
    7. Cynthia I. Escobedo del Bosque & Achim Spiller & Antje Risius, 2021. "Who Wants Chicken? Uncovering Consumer Preferences for Produce of Alternative Chicken Product Methods," Sustainability, MDPI, vol. 13(5), pages 1-21, February.
    8. Clive L Spash, 2008. "The Contingent Valuation Method: Retrospect and Prospect," Socio-Economics and the Environment in Discussion (SEED) Working Paper Series 2008-04, CSIRO Sustainable Ecosystems.
    9. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part II. Conceptualisation of external validity, sources and explanations of bias and effectiveness of mitigation methods," Journal of choice modelling, Elsevier, vol. 41(C).
    10. Thomas M. Zellweger & Franz W. Kellermanns & James J. Chrisman & Jess H. Chua, 2012. "Family Control and Family Firm Valuation by Family CEOs: The Importance of Intentions for Transgenerational Control," Organization Science, INFORMS, vol. 23(3), pages 851-868, June.
    11. Oerlemans, Leon A.G. & Chan, Kai-Ying & Volschenk, Jako, 2016. "Willingness to pay for green electricity: A review of the contingent valuation literature and its sources of error," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 875-885.
    12. Yoo, Sunbin & Kumagai, Junya & Kawabata, Yuta & Keeley, Alexander & Managi, Shunsuke, 2021. "Willingness to Buy and/or Pay Disparity: Evidence from Fully Autonomous Vehicles," MPRA Paper 108882, University Library of Munich, Germany.
    13. Chen, Fu & Tiwari, Sunil & Mohammed, Kamel Si & Huo, Weidong & Jamróz, Paweł, 2023. "Minerals resource rent responses to economic performance, greener energy, and environmental policy in China: Combination of ML and ANN outputs," Resources Policy, Elsevier, vol. 81(C).
    14. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part II. Macro-scale analysis of literature and effectiveness of bias mitigation methods," Papers 2102.02945, arXiv.org.
    15. Luzar, E. Jane & Cosse, Kelli J., 1998. "Willingness to pay or intention to pay: The attitude-behavior relationship in contingent valuation," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 27(3), pages 427-444.
    16. John K. Horowitz & Kenneth E. McConnell & James J. Murphy, 2013. "Behavioral foundations of environmental economics and valuation," Chapters, in: John A. List & Michael K. Price (ed.), Handbook on Experimental Economics and the Environment, chapter 4, pages 115-156, Edward Elgar Publishing.
    17. Adrián Castro-López & Victor Iglesias & Javier Puente, 2021. "Slow Fashion Trends: Are Consumers Willing to Change Their Shopping Behavior to Become More Sustainable?," Sustainability, MDPI, vol. 13(24), pages 1-11, December.
    18. Menglin Xing & Fuzhou Luo, 2018. "Comparative Study on the Optimization Path of Industrial Value Chain in China’s Resource-Based Cities," Sustainability, MDPI, vol. 10(5), pages 1-20, April.
    19. Lu, Hongyou & Liu, Min & Song, Wenjing, 2022. "Place-based policies, government intervention, and regional innovation: Evidence from China's Resource-Exhausted City program," Resources Policy, Elsevier, vol. 75(C).
    20. Hui Hu & Weijun Ran & Yuchen Wei & Xiang Li, 2020. "Do Energy Resource Curse and Heterogeneous Curse Exist in Provinces? Evidence from China," Energies, MDPI, vol. 13(17), pages 1-26, August.

    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:13:y:2021:i:5:p:2833-:d:511384. 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.