{"title":"数字化转型如何促进重污染企业的ESG绩效:基于国家大数据综合试验区的面板fsQCA","authors":"Li Jing , Li Qianqiang , Chen Yantai , An Qi","doi":"10.1016/j.techfore.2025.124366","DOIUrl":null,"url":null,"abstract":"<div><div>Digital transformation presents a promising pathway to improving Environmental, Social, and Governance (ESG) performance in heavy-polluting enterprises within emerging economies. However, it also introduces potential drawbacks, such as bounded rationality crowding-out effects and a focus on short-term financial goals. Therefore, to fully understand its multifaceted impact on ESG performance, a comprehensive analysis through the lens of complex systems management is crucial. This study applies panel data fuzzy-set qualitative comparative analysis (PD-fsQCA) to examine heavy-polluting enterprises in China's national big data comprehensive pilot zones. Grounded in the Technological-Organizational-Environmental (TOE) framework, the analysis uncovers the intricate causal relationships between digital transformation and ESG performance. The findings reveal that factors such as digital strategies (DS), digital technology (DT), internal control quality (IC), enterprise environmental attention allocation (EA), regional environmental regulation (ER), and public environmental concern (PEC) interact in multiple configurations to shape ESG outcomes, including “IC & DT” Driven, “ER & DS” Driven, and “DT & DS” Driven models. These pathways demonstrate significant temporal and organizational heterogeneity, highlighting the diverse impacts of digital transformation on ESG performance across different timeframes and enterprise contexts.</div></div>","PeriodicalId":48454,"journal":{"name":"Technological Forecasting and Social Change","volume":"221 ","pages":"Article 124366"},"PeriodicalIF":13.3000,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"How digital transformation facilitates ESG performance to heavy polluting enterprises:A panel fsQCA based on national big data comprehensive pilot zones\",\"authors\":\"Li Jing , Li Qianqiang , Chen Yantai , An Qi\",\"doi\":\"10.1016/j.techfore.2025.124366\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Digital transformation presents a promising pathway to improving Environmental, Social, and Governance (ESG) performance in heavy-polluting enterprises within emerging economies. However, it also introduces potential drawbacks, such as bounded rationality crowding-out effects and a focus on short-term financial goals. Therefore, to fully understand its multifaceted impact on ESG performance, a comprehensive analysis through the lens of complex systems management is crucial. This study applies panel data fuzzy-set qualitative comparative analysis (PD-fsQCA) to examine heavy-polluting enterprises in China's national big data comprehensive pilot zones. Grounded in the Technological-Organizational-Environmental (TOE) framework, the analysis uncovers the intricate causal relationships between digital transformation and ESG performance. The findings reveal that factors such as digital strategies (DS), digital technology (DT), internal control quality (IC), enterprise environmental attention allocation (EA), regional environmental regulation (ER), and public environmental concern (PEC) interact in multiple configurations to shape ESG outcomes, including “IC & DT” Driven, “ER & DS” Driven, and “DT & DS” Driven models. These pathways demonstrate significant temporal and organizational heterogeneity, highlighting the diverse impacts of digital transformation on ESG performance across different timeframes and enterprise contexts.</div></div>\",\"PeriodicalId\":48454,\"journal\":{\"name\":\"Technological Forecasting and Social Change\",\"volume\":\"221 \",\"pages\":\"Article 124366\"},\"PeriodicalIF\":13.3000,\"publicationDate\":\"2025-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Technological Forecasting and Social Change\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S004016252500397X\",\"RegionNum\":1,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technological Forecasting and Social Change","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S004016252500397X","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
How digital transformation facilitates ESG performance to heavy polluting enterprises:A panel fsQCA based on national big data comprehensive pilot zones
Digital transformation presents a promising pathway to improving Environmental, Social, and Governance (ESG) performance in heavy-polluting enterprises within emerging economies. However, it also introduces potential drawbacks, such as bounded rationality crowding-out effects and a focus on short-term financial goals. Therefore, to fully understand its multifaceted impact on ESG performance, a comprehensive analysis through the lens of complex systems management is crucial. This study applies panel data fuzzy-set qualitative comparative analysis (PD-fsQCA) to examine heavy-polluting enterprises in China's national big data comprehensive pilot zones. Grounded in the Technological-Organizational-Environmental (TOE) framework, the analysis uncovers the intricate causal relationships between digital transformation and ESG performance. The findings reveal that factors such as digital strategies (DS), digital technology (DT), internal control quality (IC), enterprise environmental attention allocation (EA), regional environmental regulation (ER), and public environmental concern (PEC) interact in multiple configurations to shape ESG outcomes, including “IC & DT” Driven, “ER & DS” Driven, and “DT & DS” Driven models. These pathways demonstrate significant temporal and organizational heterogeneity, highlighting the diverse impacts of digital transformation on ESG performance across different timeframes and enterprise contexts.
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