不确定性环境下专利开放许可激励策略演化分析

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中图分类号：F224.32；D923.42 文献标识码：A doi：10.3969/j.issn.1672-2272.202504061

TheEvolutionary Analysis of Incentive Strategies for Patent Open Licensing under Uncertain Environments

Deng Wenjie

（Chongqing Intellectual Property School，Chongqing Universityof Technology，Chongqing 40oo，China）

Abstract：To optimize the incentive implementation path of the patent open licensing system under uncertain environments，this study constructs a three-party evolutionary game model involving patent administrative departments，patent holders，and potential licensees. To better capture environmental randomness，the stochastic evolutionary game model is further developed by introducing Gaussian white noise.，and the Taylor expansion method is employed to derive analytical solutions and conduct stability analysisand numerical simulations.The findings reveal that the intensity of environmental disturbances significantly affects the volatility of strategic choices and the speed of evolutionary processes， with potential licensees being most susceptible and patent administrative departments the least sensitive.Initial participation probabilities play a moderating role in theevolution of strategies：low initial probabilities require administrative guidance，whereas high initial probabilities lead to more rapid incentive responses.Moreover，punitive measures exhibit diminishing marginal utility，economic incentives mayinduce adverse selection，while convenience-based incentives effectively enhance patent holders’ willingness to participate.This study uncovers the heterogeneous behavioral mechanisms of the strategic agents，delineates the boundaries of incentive policy applicability，and ofers theoretical support for the optimization of the patent open licensing system.

Key Words：Patent Open Licensing；Uncertain Environment； Incentive Strategies；Stochastic Evolutionary Game

0 引言

2021年6月1日，《中华人民共和国专利法》完成修订并正式施行，其中增设了专利开放许可制度。（剩余11709字）