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• W3215021703 endingPage "129841" @default.
• W3215021703 startingPage "129841" @default.
• W3215021703 abstract "Global energy interconnection (GEI) is vital for countries to achieve clean energy production and carbon neutrality. To improve the construction efficiency of GEI projects, capital allocation efficiency and its driving factors must be analyzed. Therefore, this study uses a three-stage data envelopment analysis (DEA) model to evaluate the capital allocation efficiency of 161 countries. The results demonstrate that there is spatial heterogeneity in global capital allocation efficiency and that most countries have low levels of efficiency. The average pure efficiency is 0.364 and the average scale efficiency is only 0.176. To determine the fastest possible method of improving efficiency in different countries, this paper combined an adjusted three-stage DEA model with a geographically weighted regression (GWR) model to quantify the driving factors of capital allocation efficiency. The level of economic development is the main driving factor, whereas government support has the least influence on capital allocation efficiency. Furthermore, the coefficients of the influence of each driving factor vary significantly across different regions. In conclusion, this study quantitatively estimates the efficiency of capital allocation for GEI projects and explores the key driving factors of efficiency from the perspective of heterogeneity, and makes targeted recommendations for countries to improve efficiency." @default.
• W3215021703 created "2021-12-06" @default.
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• W3215021703 date "2022-01-01" @default.
• W3215021703 modified "2023-09-24" @default.
• W3215021703 title "How to improve the efficiency of global energy interconnection capital allocation? Analysis from the perspective of spatial heterogeneity and driving factors" @default.
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• W3215021703 doi "https://doi.org/10.1016/j.jclepro.2021.129841" @default.
• W3215021703 hasPublicationYear "2022" @default.
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