{"title":"中国电力产业集聚水平及其影响因素——基于省际面板的空间计量分析","authors":"Tanbo Zhu, Wenxing Li, Wei Bu","doi":"10.1002/ese3.70020","DOIUrl":null,"url":null,"abstract":"<p>The agglomeration of the power industry can not only improve industrial production efficiency but also promote energy structure adjustment, which is of great significance for improving national energy security and environmental protection levels. This paper is based on panel data from 30 provinces in China from 2001 to 2021, using the improved location entropy method to measure the agglomeration level of the power industry. The spatial Durbin model (SDM) is used to empirically test the influencing factors and spatial effects of the agglomeration level of the power industry. Research has found that (1) there is a significant spatial correlation in the agglomeration level of China's power industry, and the agglomeration level of the power industry in a region is influenced by neighboring regions; (2) the industrial structure, economies of scale, and power consumption of this region have a significant positive spatial effect on the level of power industry agglomeration, while the population of this region and factors such as the industrial structure, economies of scale, and power consumption of adjacent regions have a significant negative spatial effect on power industry agglomeration. Based on empirical results, relevant suggestions have been proposed to improve the agglomeration level of China's power industry. Based on empirical results, relevant suggestions have been proposed to improve the agglomeration level of China's power industry.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 4","pages":"2153-2163"},"PeriodicalIF":3.5000,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70020","citationCount":"0","resultStr":"{\"title\":\"Agglomeration Level and Its Influencing Factors of the Power Industry: A Spatial Econometric Analysis Based on Interprovincial Panel in China\",\"authors\":\"Tanbo Zhu, Wenxing Li, Wei Bu\",\"doi\":\"10.1002/ese3.70020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The agglomeration of the power industry can not only improve industrial production efficiency but also promote energy structure adjustment, which is of great significance for improving national energy security and environmental protection levels. This paper is based on panel data from 30 provinces in China from 2001 to 2021, using the improved location entropy method to measure the agglomeration level of the power industry. The spatial Durbin model (SDM) is used to empirically test the influencing factors and spatial effects of the agglomeration level of the power industry. Research has found that (1) there is a significant spatial correlation in the agglomeration level of China's power industry, and the agglomeration level of the power industry in a region is influenced by neighboring regions; (2) the industrial structure, economies of scale, and power consumption of this region have a significant positive spatial effect on the level of power industry agglomeration, while the population of this region and factors such as the industrial structure, economies of scale, and power consumption of adjacent regions have a significant negative spatial effect on power industry agglomeration. Based on empirical results, relevant suggestions have been proposed to improve the agglomeration level of China's power industry. Based on empirical results, relevant suggestions have been proposed to improve the agglomeration level of China's power industry.</p>\",\"PeriodicalId\":11673,\"journal\":{\"name\":\"Energy Science & Engineering\",\"volume\":\"13 4\",\"pages\":\"2153-2163\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2025-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70020\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Science & Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/ese3.70020\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Science & Engineering","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ese3.70020","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Agglomeration Level and Its Influencing Factors of the Power Industry: A Spatial Econometric Analysis Based on Interprovincial Panel in China
The agglomeration of the power industry can not only improve industrial production efficiency but also promote energy structure adjustment, which is of great significance for improving national energy security and environmental protection levels. This paper is based on panel data from 30 provinces in China from 2001 to 2021, using the improved location entropy method to measure the agglomeration level of the power industry. The spatial Durbin model (SDM) is used to empirically test the influencing factors and spatial effects of the agglomeration level of the power industry. Research has found that (1) there is a significant spatial correlation in the agglomeration level of China's power industry, and the agglomeration level of the power industry in a region is influenced by neighboring regions; (2) the industrial structure, economies of scale, and power consumption of this region have a significant positive spatial effect on the level of power industry agglomeration, while the population of this region and factors such as the industrial structure, economies of scale, and power consumption of adjacent regions have a significant negative spatial effect on power industry agglomeration. Based on empirical results, relevant suggestions have been proposed to improve the agglomeration level of China's power industry. Based on empirical results, relevant suggestions have been proposed to improve the agglomeration level of China's power industry.
期刊介绍：
Energy Science & Engineering is a peer reviewed, open access journal dedicated to fundamental and applied research on energy and supply and use. Published as a co-operative venture of Wiley and SCI (Society of Chemical Industry), the journal offers authors a fast route to publication and the ability to share their research with the widest possible audience of scientists, professionals and other interested people across the globe. Securing an affordable and low carbon energy supply is a critical challenge of the 21st century and the solutions will require collaboration between scientists and engineers worldwide. This new journal aims to facilitate collaboration and spark innovation in energy research and development. Due to the importance of this topic to society and economic development the journal will give priority to quality research papers that are accessible to a broad readership and discuss sustainable, state-of-the art approaches to shaping the future of energy. This multidisciplinary journal will appeal to all researchers and professionals working in any area of energy in academia, industry or government, including scientists, engineers, consultants, policy-makers, government officials, economists and corporate organisations.
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