Open AccessImpact of incentive and selection strength on green technology innovation in Moran process
Author(s) -
Runtian Zhang,
Jinye Li
Publication year - 2020
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0235516
Subject(s) - incentive , randomness , process (computing) , selection (genetic algorithm) , population , economics , microeconomics , outcome (game theory) , computer science , operations research , industrial organization , mathematical optimization , engineering , mathematics , artificial intelligence , statistics , demography , sociology , operating system
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.