Government participation in low-carbon technology transfer: An evolutionary game study

Chen Zou, Yongchun Huang, Shiliang Hu and Zhan Huang

Technological Forecasting and Social Change, 2023, vol. 188, issue C

Abstract: Low-carbon technology transfer is the primary means of promoting the industrialization of low-carbon scientific and technological achievements, as well as an important component in accelerating the realization of carbon peak and carbon neutrality. This study uses the evolutionary game model to construct a three-party game relationship consisting of a low-carbon technology sender and receiver along with government participation. Additionally, based on the Green Technology Bank case, we demonstrate the impact of various factors on the three parties' choice of low-carbon technology transfer strategy in the game. The results reveal that the final participation behavior of the government is less influenced by the initial willingness of the sender and receiver to participate. However, the initial participation willingness of the government and low-carbon technology sender has a significant impact on the receiver's participation. Furthermore, the sender's participation is substantially influenced by the government's willingness to participate. Optimizing the cost and benefit distribution mechanism can encourage low-carbon technology transfer subjects to participate. Increasing government incentive and default punishment is more conducive to realizing the three parties' win-win situation in the game. While government incentive has a significant impact on the sender, the increase in default punishment has a considerable effect on the receiver.

Keywords: Low-carbon technology transfer; Government involvement; Evolutionary game; Carbon peak; Carbon neutrality (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:188:y:2023:i:c:s0040162523000057

DOI: 10.1016/j.techfore.2023.122320

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