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

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  • 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.

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  • 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
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    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.

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