| Title | System dynamics simulation of green innovation and policy optimization considering decision bias |
|---|---|
| ID_Doc | 35765 |
| Authors | Cheng, F; Chen, T; Sun, M |
| Title | System dynamics simulation of green innovation and policy optimization considering decision bias |
| Year | 2024 |
| Published | |
| Abstract | Promoting the development of green innovation is crucial for achieving the green transformation of society. This paper considers the decision bias of different agents in policy implementation and presents a theoretical model that captures the structure of the green innovation system. The model includes six subsystems: government, technology, public, energy, environment, and population. The study examines the transmission effect of green innovation and the influence mechanism of multiple decision biases on policy combination effects using a combination of various policy tools. The results show that: Various policy tools and their implementation differences have distinct effects on the green innovation and environmental performance. In most cases, the synergistic policy mix effect, surpassing the impact of individual policies, is driven by the resource effect. However, the synergistic effect of policy combination may not be fully realized, leading to potential conflicts. Due to various decision biases, particularly the gap in the public's green behavior, the policy mix faces challenges in achieving immediate synergistic effects. Combining tax policies with other policy instruments increases the risk of incoherence and inconsistency. However, in the long term, the combination of policy tools can exert strong late-developing advantages. This study provides insights for green innovation policy improvement. |
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