IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0235516.html
   My bibliography  Save this article

Impact of incentive and selection strength on green technology innovation in Moran process

Author

Listed:
  • Runtian Zhang
  • Jinye Li

Abstract

Methods of previous researches on green technology innovation will have difficulty in finite population. One solution is the use of stochastic evolutionary game dynamic-Moran process. In this paper we study stochastic dynamic games about green technology innovation with a two-stage free riding problem. Results illustrate the incentive and selection strength play positive roles in promoting participant to be more useful to society, but with threshold effect: too slighted strength makes no effect due to the randomness of the evolution process in finite population. Two-stage free riding problem can be solved with the use of inequality incentives, however, higher inequality can make policy achieves faster but more unstable, so there would be an optimal range. In this paper we provided the key variables of green technology innovation incentive and principles for the environmental regulation policy making. Also reminded that it’s difficult to formulate policies reasonably and make them achieve the expected results.

Suggested Citation

  • Runtian Zhang & Jinye Li, 2020. "Impact of incentive and selection strength on green technology innovation in Moran process," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-15, June.
    • Handle: RePEc:plo:pone00:0235516
    DOI: 10.1371/journal.pone.0235516
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0235516
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0235516&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0235516?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Michael Moutoussis & Raymond J Dolan & Peter Dayan, 2016. "How People Use Social Information to Find out What to Want in the Paradigmatic Case of Inter-temporal Preferences," PLOS Computational Biology, Public Library of Science, vol. 12(7), pages 1-17, July.
    2. Boulanger, Paul-Marie & Brechet, Thierry, 2005. "Models for policy-making in sustainable development: The state of the art and perspectives for research," Ecological Economics, Elsevier, vol. 55(3), pages 337-350, November.
    3. Cabrales, Antonio, 2000. "Stochastic Replicator Dynamics," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 41(2), pages 451-481, May.
    4. Zhang, Suyong & Wang, Chuanxu & Yu, Chao, 2019. "The evolutionary game analysis and simulation with system dynamics of manufacturer's emissions abatement behavior under cap-and-trade regulation," Applied Mathematics and Computation, Elsevier, vol. 355(C), pages 343-355.
    5. Martin A. Nowak & Akira Sasaki & Christine Taylor & Drew Fudenberg, 2004. "Emergence of cooperation and evolutionary stability in finite populations," Nature, Nature, vol. 428(6983), pages 646-650, April.
    6. Zhao, Rui & Zhou, Xiao & Han, Jiaojie & Liu, Chengliang, 2016. "For the sustainable performance of the carbon reduction labeling policies under an evolutionary game simulation," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 262-274.
    7. Brunnermeier, Smita B. & Cohen, Mark A., 2003. "Determinants of environmental innovation in US manufacturing industries," Journal of Environmental Economics and Management, Elsevier, vol. 45(2), pages 278-293, March.
    8. Rassier, Dylan G. & Earnhart, Dietrich, 2015. "Effects of environmental regulation on actual and expected profitability," Ecological Economics, Elsevier, vol. 112(C), pages 129-140.
    9. Izquierdo, Luis R. & Izquierdo, Segismundo S. & Sandholm, William H., 2019. "An introduction to ABED: Agent-based simulation of evolutionary game dynamics," Games and Economic Behavior, Elsevier, vol. 118(C), pages 434-462.
    10. Zglobisz, Natalia & Castillo-Castillo, Arturo & Grimes, Sue & Jones, Peter, 2010. "Influence of UK energy policy on the deployment of anaerobic digestion," Energy Policy, Elsevier, vol. 38(10), pages 5988-5999, October.
    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. Tuochen Li & Xinyu Zhou, 2022. "Research on the Mechanism of Government–Industry–University–Institute Collaborative Innovation in Green Technology Based on Game–Based Cellular Automata," IJERPH, MDPI, vol. 19(5), pages 1-25, March.

    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. Daozhi Zhao & Jiaqin Hao & Cejun Cao & Hongshuai Han, 2019. "Evolutionary Game Analysis of Three-Player for Low-Carbon Production Capacity Sharing," Sustainability, MDPI, vol. 11(11), pages 1-20, May.
    2. Xie, Rong-hui & Yuan, Yi-jun & Huang, Jing-jing, 2017. "Different Types of Environmental Regulations and Heterogeneous Influence on “Green” Productivity: Evidence from China," Ecological Economics, Elsevier, vol. 132(C), pages 104-112.
    3. Gu, Cuiling & Wang, Xianjia & Zhao, Jinhua & Ding, Rui & He, Qilong, 2020. "Evolutionary game dynamics of Moran process with fuzzy payoffs and its application," Applied Mathematics and Computation, Elsevier, vol. 378(C).
    4. Dai, Darong, 2012. "On the Existence of Pareto Optimal Endogenous Matching," MPRA Paper 43125, University Library of Munich, Germany.
    5. Ni, Xiaoran & Jin, Qi & Huang, Kunhao, 2022. "Environmental regulation and the cost of debt: Evidence from the carbon emission trading system pilot in China," Finance Research Letters, Elsevier, vol. 49(C).
    6. Chen, Shangrong & Bravo-Melgarejo, Sai & Mongeau, Romain & Malavolti, Estelle, 2023. "Adopting and diffusing hydrogen technology in air transport: An evolutionary game theory approach," Energy Economics, Elsevier, vol. 125(C).
    7. Zhang, Yijun & Song, Yi, 2022. "Tax rebates, technological innovation and sustainable development: Evidence from Chinese micro-level data," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    8. Dai, Darong & Shen, Kunrong, 2012. "A New Stationary Game Equilibrium Induced by Stochastic Group Evolution and Rational Individual Choice," MPRA Paper 40586, University Library of Munich, Germany, revised 09 Aug 2012.
    9. Li, Shoude & Fu, Tong, 2022. "Abatement technology innovation, worker productivity and firm profitability: A dynamic analysis," Energy Economics, Elsevier, vol. 115(C).
    10. Dai, Darong, 2012. "On the Existence and Stability of Pareto Optimal Endogenous Matching with Fairness," MPRA Paper 40560, University Library of Munich, Germany.
    11. Ponti, Giovanni, 2000. "Cycles of Learning in the Centipede Game," Games and Economic Behavior, Elsevier, vol. 30(1), pages 115-141, January.
    12. Martin, Ralf & Muûls, Mirabelle & de Preux, Laure B. & Wagner, Ulrich J., 2012. "Anatomy of a paradox: Management practices, organizational structure and energy efficiency," Journal of Environmental Economics and Management, Elsevier, vol. 63(2), pages 208-223.
    13. Chen, Yunong & Belmonte, Andrew & Griffin, Christopher, 2021. "Imitation of success leads to cost of living mediated fairness in the Ultimatum Game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    14. Hu, Hui & Qi, Shaozhou & Chen, Yuanzhi, 2023. "Using green technology for a better tomorrow: How enterprises and government utilize the carbon trading system and incentive policies," China Economic Review, Elsevier, vol. 78(C).
    15. Carrión-Flores, Carmen E. & Innes, Robert, 2010. "Environmental innovation and environmental performance," Journal of Environmental Economics and Management, Elsevier, vol. 59(1), pages 27-42, January.
    16. Hille, Erik & Althammer, Wilhelm & Diederich, Henning, 2020. "Environmental regulation and innovation in renewable energy technologies: Does the policy instrument matter?," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    17. Vitaliy Roud & Thomas Wolfgang Thurner, 2018. "The Influence of State‐Ownership on Eco‐Innovations in Russian Manufacturing Firms," Journal of Industrial Ecology, Yale University, vol. 22(5), pages 1213-1227, October.
    18. 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.
    19. Francesco Vona & Francesco Nicolli & Lionel Nesta, 2012. "Determinants of renewable energy innovation: environmental policies vs. market regulation," Sciences Po publications 2012-05, Sciences Po.
    20. Gale, John & Binmore, Kenneth G. & Samuelson, Larry, 1995. "Learning to be imperfect: The ultimatum game," Games and Economic Behavior, Elsevier, vol. 8(1), pages 56-90.

    More about this item

    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:plo:pone00:0235516. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.