Evolutionary Game Analysis of Knowledge Sharing in Low-Carbon Innovation Network

Cuicui Zheng,Zhihan Lv

doi:10.1155/2021/9995344

Abstract

Low-carbon technological innovation is the main means to develop a low-carbon economy, and network knowledge sharing and collaborative innovation is an effective model for the development of low-carbon technologies. First of all, this article adopts a decision-making experiment and evaluation laboratory method and interpretation structure model, combines the two methods, extracts the advantages of the two, and discards the shortcomings of the two, thus constructing a new optimized and upgraded interpretation structure model. We give methods to explore the main influencing factors of collaborative innovation of low-carbon technologies for online knowledge sharing. Based on the industrial network knowledge sharing and cooperation network environment, the network evolution game model of network knowledge sharing knowledge collaboration is constructed to study the rewards and punishments, the profit distribution rate, the knowledge potential difference, and the parameter pairing of the network knowledge sharing cooperation network structure in the process of network knowledge sharing and collaborative knowledge innovation. The influence of the network knowledge sharing cooperation strategy is obtained through simulation to change the size of the relevant parameters so that the network knowledge sharing cooperation agent chooses the network evolution game of the sharing strategy to realize the optimal evolutionary stable strategy. According to the simulation results, this article proposes suggestions from the following aspects, aiming to improve the overall knowledge synergy effect of the network knowledge sharing and cooperation network.

Highlights

With the rapid development of the knowledge economy, network knowledge sharing has entered a critical period of innovation-driven development strategy
It is mainly affected by the initial state of the game, and the difference in the initial values of the parameters will promote the evolution of the system to converge to different equilibrium points. (1) e impact of low-carbon innovation network knowledge sharing incentives on evolution: the upgrade factor of sample points in Figure 5 determines the probability of the system evolving to different results, and the position of the critical line is determined by the saddle point E(θ ∗, δ ∗ ). en, find the first order of λ2 and λ1 for θ ∗ and δ ∗, respectively
The area of N increases, and the probability of the system evolving to D (1, 1) increases. at is, network 2 will choose knowledge sharing. e same analysis shows that when λ1 increases, network 1 will choose knowledge sharing. (2) e impact of low-carbon innovation network knowledge sharing penalty on evolution: find the first derivative of c2 and c1 for θ ∗ and δ ∗, respectively, and get θ ∗ < 0. erefore, when c2 increases, θ decreases

Summary

Introduction

With the rapid development of the knowledge economy, network knowledge sharing has entered a critical period of innovation-driven development strategy. In order to solve the above dilemma, collaborative innovation of network knowledge sharing came into being. Network knowledge sharing and cooperation is a complex process. Due to the scarcity of resources and the asymmetry of the status of the network and academic research institutions, collaborative innovation entities will reduce the efficiency of network knowledge sharing and cooperation due to conflicts in the distribution of interests, which will affect the cooperation stability and sustainability [3]. Network knowledge sharing and cooperation may put actively collaborative members in a disadvantageous position, making the partners face prisoners’ dilemma and adverse selection in the process of network knowledge sharing collaborative innovation [4]

Methods

Results

Discussion

Conclusion