IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i7p1466-d1200344.html
   My bibliography  Save this article

Reputation, Network, and Performance: Exploring the Diffusion Mechanism of Local Governments’ Behavior during Inter-Governmental Environmental Cooperation

Author

Listed:
  • Yihang Zhao

    (Institute of Urban and Demographic Studies, Shanghai Academy of Social Sciences, Shanghai 200020, China)

  • Jing Xiong

    (School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai 200030, China
    China Institute for Urban Governance, Shanghai Jiao Tong University, Shanghai 200030, China
    Institute of Eco-Chongming, East China Normal University, Shanghai 202162, China)

  • De Hu

    (School of Urban and Regional Science, East China Normal University, Shanghai 200241, China)

Abstract

The selective behavior of local governments during regional environmental cooperation could generate a diffusion effect through the black box of reputation mechanism. This study incorporates the reputation mechanism, social capital, and environmental governance performance into a unified analysis framework, empirically testing the moderating effect of the implementation rate of environmental cooperative projects (indicating reputation) on the relationship between two types of social capital and environmental governance performance among cities in the Yangtze River Delta (YRD) and Beijing–Tianjin–Hebei (BTH) regions. The inter-governmental environmental cooperation news and policies are collected by Data Capture technology as a dataset, and a set of social-economic data is also adopted. The spatial econometric regression results show that an increase in reputation could both strengthen the leadership and coordination ability (bridging social capital) of the central cities in the YRD and BTH regions, thus improving their environmental governance performance. However, the bonding social capital path could only significantly work in the BTH region, which unexpectedly increases pollutant emission through excessive internal cohesion. The results indicate that a “community of entangled interest” should be constructed among cities within urban agglomerations, which requires local governments to weaken the concept of their administrative boundary. At the same time, in order to avoid excessive internal condensation, a clear division of rights and responsibilities is also necessary during continuous inter-governmental environmental cooperation. We believe that these findings could provide empirical evidence for local governments to avoid failing to the traps of “agglomeration shadow”.

Suggested Citation

  • Yihang Zhao & Jing Xiong & De Hu, 2023. "Reputation, Network, and Performance: Exploring the Diffusion Mechanism of Local Governments’ Behavior during Inter-Governmental Environmental Cooperation," Land, MDPI, vol. 12(7), pages 1-17, July.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:7:p:1466-:d:1200344
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/7/1466/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/12/7/1466/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Zhen & Chen, Tong & Wang, Yongjie, 2017. "Leadership by example promotes the emergence of cooperation in public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 101(C), pages 100-105.
    2. Jie Tan & Jerry Zhirong Zhao, 2021. "Explaining the adoption rate of public-private partnerships in Chinese provinces: a transaction cost perspective," Public Management Review, Taylor & Francis Journals, vol. 23(4), pages 590-609, April.
    3. Debin Ma & Jie Zhang & Ziyi Wang & Dongqi Sun, 2022. "Spatio-Temporal Evolution and Influencing Factors of Open Economy Development in the Yangtze River Delta Area," Land, MDPI, vol. 11(10), pages 1-24, October.
    4. Ramiro Berardo & John T. Scholz, 2010. "Self‐Organizing Policy Networks: Risk, Partner Selection, and Cooperation in Estuaries," American Journal of Political Science, John Wiley & Sons, vol. 54(3), pages 632-649, July.
    5. Albert I. Goldberg & Gilat Cohen & Avi Fiegenbaum, 2003. "Reputation Building: Small Business Strategies for Successful Venture Development," Journal of Small Business Management, Taylor & Francis Journals, vol. 41(2), pages 168-186, April.
    6. Jiao, Yuhang & Chen, Tong & Chen, Qiao, 2020. "The impact of expressing willingness to cooperate on cooperation in public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    7. Wang, Le & Chen, Tong & Wu, Zhenghong, 2021. "Promoting cooperation by reputation scoring mechanism based on historical donations in public goods game," Applied Mathematics and Computation, Elsevier, vol. 390(C).
    8. Chen Huang & Wenna Chen & Hongtao Yi, 2021. "Collaborative networks and environmental governance performance: a social influence model," Public Management Review, Taylor & Francis Journals, vol. 23(12), pages 1878-1899, December.
    9. John T. Scholz & Cheng‐Lung Wang, 2009. "Learning to Cooperate: Learning Networks and the Problem of Altruism," American Journal of Political Science, John Wiley & Sons, vol. 53(3), pages 572-587, July.
    10. Yihang Zhao & Chen Liang & Xinlong Zhang, 2021. "Positive or negative externalities? Exploring the spatial spillover and industrial agglomeration threshold effects of environmental regulation on haze pollution in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 11335-11356, August.
    11. Dunia López-Pintado & Duncan J. Watts, 2008. "Social Influence, Binary Decisions and Collective Dynamics," Rationality and Society, , vol. 20(4), pages 399-443, November.
    12. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
    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. Christoph Engel & Alon Klement & Karen Weinshall Margel, 2017. "Diffusion of Legal Innovations: The Case of Israeli Class Actions," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2017_11, Max Planck Institute for Research on Collective Goods, revised Jan 2018.
    2. Zhenghong Wu & Huan Huang & Qinghu Liao, 2021. "The study on the role of dedicators on promoting cooperation in public goods game," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-17, September.
    3. H Peyton Young & Lucas Merrill Brown, 2016. "The Diffusion of a Social Innovation: Executive Stock Options from 1936," Economics Series Working Papers 777, University of Oxford, Department of Economics.
    4. Koster, Maurice & Lindner, Ines & Molina, Elisenda, 2010. "Networks and collective action," DES - Working Papers. Statistics and Econometrics. WS ws104830, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Sebastián Moreno & Danilo Bórquez-Paredes & Valentina Martínez, 2023. "Analysis of the Characteristics and Speed of Spread of the “FUNA” on Twitter," Mathematics, MDPI, vol. 11(7), pages 1-18, April.
    6. Sharad Goel & Ashton Anderson & Jake Hofman & Duncan J. Watts, 2016. "The Structural Virality of Online Diffusion," Management Science, INFORMS, vol. 62(1), pages 180-196, January.
    7. López-Pintado, Dunia, 2012. "Influence networks," Games and Economic Behavior, Elsevier, vol. 75(2), pages 776-787.
    8. Kang, Jia-Ning & Wei, Yi-Ming & Liu, Lan-cui & Yu, Bi-Ying & Liao, Hua, 2021. "A social learning approach to carbon capture and storage demonstration project management: An empirical analysis," Applied Energy, Elsevier, vol. 299(C).
    9. Pradelski, Bary S.R., 2023. "Social influence: The Usage History heuristic," Mathematical Social Sciences, Elsevier, vol. 123(C), pages 105-113.
    10. H Peyton Young, 2014. "The Evolution of Social Norms," Economics Series Working Papers 726, University of Oxford, Department of Economics.
    11. Jonas Hedlund & Carlos Oyarzun, 2018. "Imitation in heterogeneous populations," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 65(4), pages 937-973, June.
    12. Sergio Currarini & Carmen Marchiori & Alessandro Tavoni, 2016. "Network Economics and the Environment: Insights and Perspectives," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 65(1), pages 159-189, September.
    13. Friedman, Rachel S. & Guerrero, Angela M. & McAllister, Ryan R.J. & Rhodes, Jonathan R. & Santika, Truly & Budiharta, Sugeng & Indrawan, Tito & Hutabarat, Joseph A. & Kusworo, Ahmad & Yogaswara, Herry, 2020. "Beyond the community in participatory forest management: A governance network perspective," Land Use Policy, Elsevier, vol. 97(C).
    14. Boerner, Lars & Severgnini, Battista, 2015. "Time for growth," LSE Research Online Documents on Economics 64495, London School of Economics and Political Science, LSE Library.
    15. Sgrignoli, P. & Agliari, E. & Burioni, R. & Schianchi, A., 2015. "Instability and network effects in innovative markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 108(C), pages 260-271.
    16. Edouard Civel & Marc Baudry, 2018. "The Fate of Inventions. What can we learn from Bayesian learning in strategic options model of adoption ?," EconomiX Working Papers 2018-47, University of Paris Nanterre, EconomiX.
    17. Elisabeth SADOULET, 2016. "Review of Theories of Learning for Adopting," Working Papers P163, FERDI.
    18. Tat Y. Chan & Jia Li & Lamar Pierce, 2014. "Learning from Peers: Knowledge Transfer and Sales Force Productivity Growth," Marketing Science, INFORMS, vol. 33(4), pages 463-484, July.
    19. Mercure, Jean-François, 2018. "Fashion, fads and the popularity of choices: Micro-foundations for diffusion consumer theory," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 194-207.
    20. Enrico Spolaore & Romain Wacziarg, 2022. "Fertility and Modernity," The Economic Journal, Royal Economic Society, vol. 132(642), pages 796-833.

    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:jlands:v:12:y:2023:i:7:p:1466-:d:1200344. 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.