Research on Collaborative Innovation of Carbon Neutral Industrial Technological Innovation Consortium Based on Tripartite Evolutionary Game

聚焦于多主体共同参与的碳中和产业技术创新联合体,构建碳中和领军企业、学研机构以及政府的三方演化博弈模型,分析各个均衡点的稳定性,并用Matlab进行数值仿真,模拟不同影响因素参数变化下各参与主体的策略选择变化过程。研究结果表明,合理的收益分配系数有助于促进产学研参与合作创新、过高的惩罚力度会抑制产学研协同创新的策略选择。最后,从碳中和企业、学研机构、政府层面提出了促进碳中和技术协同创新的优化策略建议。Focusing on the carbon neutral industrial technological innovation consortium with the participation of multiple actors, a tripartite evolutionary game model of carbon neutral leading enterprises, academic and research institutions and the government was constructed, and the stability of each equilibrium point was analyzed. Numerical simulation was carried out with Matlab to simulate the change process of strategy selection of each participant under the change of parameters of different influencing factors. The results show that reasonable income distribution coefficient is helpful to promote the participation of industry, university and research in cooperative innovation, and too high punishment intensity will inhibit the strategy choice of industry, university and research collaborative innovation. Finally, from the level of carbon neutral enterprises, research institutions and government, the optimization strategy of promoting carbon neutral technology collaborative innovation is proposed.

Authors

Publication Details

Journal
Journal of Low Carbon Economy
Published
2025-01-01
DOI
https://doi.org/10.12677/jlce.2025.142023
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on Collaborative Innovation of Carbon Neutral Industrial Technological Innovation Consortium Based on Tripartite Evolutionary Game

雪 李
Journal of Low Carbon Economy
Energy, Environment, Economic Growth
article

Research on Collaborative Innovation of Carbon Neutral Industrial Technological Innovation Consortium Based on Tripartite Evolutionary Game

雪 李
article en

Abstract

聚焦于多主体共同参与的碳中和产业技术创新联合体,构建碳中和领军企业、学研机构以及政府的三方演化博弈模型,分析各个均衡点的稳定性,并用Matlab进行数值仿真,模拟不同影响因素参数变化下各参与主体的策略选择变化过程。研究结果表明,合理的收益分配系数有助于促进产学研参与合作创新、过高的惩罚力度会抑制产学研协同创新的策略选择。最后,从碳中和企业、学研机构、政府层面提出了促进碳中和技术协同创新的优化策略建议。Focusing on the carbon neutral industrial technological innovation consortium with the participation of multiple actors, a tripartite evolutionary game model of carbon neutral leading enterprises, academic and research institutions and the government was constructed, and the stability of each equilibrium point was analyzed. Numerical simulation was carried out with Matlab to simulate the change process of strategy selection of each participant under the change of parameters of different influencing factors. The results show that reasonable income distribution coefficient is helpful to promote the participation of industry, university and research in cooperative innovation, and too high punishment intensity will inhibit the strategy choice of industry, university and research collaborative innovation. Finally, from the level of carbon neutral enterprises, research institutions and government, the optimization strategy of promoting carbon neutral technology collaborative innovation is proposed.

Journal of Low Carbon EconomyVol. 14(02)
Industry, innovation and infrastructure
Openalex Percentile: Top 83%
Energy, Environment, Economic Growth
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Research on Collaborative Innovation of Carbon Neutral Industrial Technological Innovation Consortium Based on Tripartite Evolutionary Game — 雪 李 · Journal of Low Carbon Economy (2025) | TGRS Research Map | TGRS