{"title":"如何通过数字与实体经济的融合提升中国全要素能源效率:来自动态QCA分析的新证据","authors":"Kaijun Zhong, Yalin Lei, Jun Zhao, Yong Jiang","doi":"10.1016/j.eneco.2025.108689","DOIUrl":null,"url":null,"abstract":"<div><div>In response to global climate challenges and China's regional energy efficiency disparities, this study identifies how digital-real economy integration (DRI) enhances total-factor energy efficiency (TFEE) through a novel dynamic qualitative comparative analysis (QCA) of 30 Chinese provinces (2012−2022). The findings reveal three key conclusions. First, while no single condition is strictly necessary for achieving high TFEE, the importance of digital infrastructure and digital finance has increased significantly. Digital infrastructure enhances energy efficiency by optimizing resource allocation and promoting industrial synergy, whereas digital finance contributes through green credit and capital optimization. Second, three primary DRI pathways for improving TFEE are identified: the digital industry-driven pattern, for regions with strong digital foundations but insufficient industrial agglomeration; the industrial synergy optimization pattern, for developed eastern regions; and the technology–capital–space interaction pattern, for areas with advanced green finance and concentrated industries. Third, Kruskal–Wallis rank–sum tests reveal that regional structural differences strongly influence digitalization and TFEE. Eastern regions lead due to policy support, resource allocation, industrial modernization, and talent advantages, whereas central and western regions face challenges such as weaker infrastructure, limited policy support, and slower digital transformation, resulting in unbalanced regional development.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"148 ","pages":"Article 108689"},"PeriodicalIF":14.2000,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"How to enhance China's total-factor energy efficiency via digital-real economy integration: New evidence from dynamic QCA analysis\",\"authors\":\"Kaijun Zhong, Yalin Lei, Jun Zhao, Yong Jiang\",\"doi\":\"10.1016/j.eneco.2025.108689\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In response to global climate challenges and China's regional energy efficiency disparities, this study identifies how digital-real economy integration (DRI) enhances total-factor energy efficiency (TFEE) through a novel dynamic qualitative comparative analysis (QCA) of 30 Chinese provinces (2012−2022). The findings reveal three key conclusions. First, while no single condition is strictly necessary for achieving high TFEE, the importance of digital infrastructure and digital finance has increased significantly. Digital infrastructure enhances energy efficiency by optimizing resource allocation and promoting industrial synergy, whereas digital finance contributes through green credit and capital optimization. Second, three primary DRI pathways for improving TFEE are identified: the digital industry-driven pattern, for regions with strong digital foundations but insufficient industrial agglomeration; the industrial synergy optimization pattern, for developed eastern regions; and the technology–capital–space interaction pattern, for areas with advanced green finance and concentrated industries. Third, Kruskal–Wallis rank–sum tests reveal that regional structural differences strongly influence digitalization and TFEE. Eastern regions lead due to policy support, resource allocation, industrial modernization, and talent advantages, whereas central and western regions face challenges such as weaker infrastructure, limited policy support, and slower digital transformation, resulting in unbalanced regional development.</div></div>\",\"PeriodicalId\":11665,\"journal\":{\"name\":\"Energy Economics\",\"volume\":\"148 \",\"pages\":\"Article 108689\"},\"PeriodicalIF\":14.2000,\"publicationDate\":\"2025-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Economics\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S014098832500516X\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Economics","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S014098832500516X","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
How to enhance China's total-factor energy efficiency via digital-real economy integration: New evidence from dynamic QCA analysis
In response to global climate challenges and China's regional energy efficiency disparities, this study identifies how digital-real economy integration (DRI) enhances total-factor energy efficiency (TFEE) through a novel dynamic qualitative comparative analysis (QCA) of 30 Chinese provinces (2012−2022). The findings reveal three key conclusions. First, while no single condition is strictly necessary for achieving high TFEE, the importance of digital infrastructure and digital finance has increased significantly. Digital infrastructure enhances energy efficiency by optimizing resource allocation and promoting industrial synergy, whereas digital finance contributes through green credit and capital optimization. Second, three primary DRI pathways for improving TFEE are identified: the digital industry-driven pattern, for regions with strong digital foundations but insufficient industrial agglomeration; the industrial synergy optimization pattern, for developed eastern regions; and the technology–capital–space interaction pattern, for areas with advanced green finance and concentrated industries. Third, Kruskal–Wallis rank–sum tests reveal that regional structural differences strongly influence digitalization and TFEE. Eastern regions lead due to policy support, resource allocation, industrial modernization, and talent advantages, whereas central and western regions face challenges such as weaker infrastructure, limited policy support, and slower digital transformation, resulting in unbalanced regional development.
期刊介绍:
Energy Economics is a field journal that focuses on energy economics and energy finance. It covers various themes including the exploitation, conversion, and use of energy, markets for energy commodities and derivatives, regulation and taxation, forecasting, environment and climate, international trade, development, and monetary policy. The journal welcomes contributions that utilize diverse methods such as experiments, surveys, econometrics, decomposition, simulation models, equilibrium models, optimization models, and analytical models. It publishes a combination of papers employing different methods to explore a wide range of topics. The journal's replication policy encourages the submission of replication studies, wherein researchers reproduce and extend the key results of original studies while explaining any differences. Energy Economics is indexed and abstracted in several databases including Environmental Abstracts, Fuel and Energy Abstracts, Social Sciences Citation Index, GEOBASE, Social & Behavioral Sciences, Journal of Economic Literature, INSPEC, and more.