近日,数字创新与全球价值链升级研究中心研究员厉婧、李欠强和基地负责人、工商管理学院(MBA学院)教授陈衍泰共同撰写的论文“How digital transformation facilitates ESG performance to heavy polluting enterprises: A panel fsQCA based on national big data comprehensive pilot zones” 被 Technological Forecasting & Social Change 期刊录用并在线发表。本文通讯作者为浙江科技大学李欠强副教授。
本项目得到国家自然科学基金重点项目(立项号:72032008);国家社科基金领军人才项目;浙江省高质量哲学社会科学重点研究基地重大课题(课题编号:2025JDKT08Z);国家自然科学基金青年项目(立项号:No.72402212)支持。
本研究聚焦于新兴经济体高污染企业的数字化转型与环境、社会和治理(ESG)绩效之间的复杂关系,旨在揭示数字化在推动可持续发展过程中可能产生的双重效应。一方面,数字化转型为提升企业环境治理能力和社会责任水平提供了重要契机;另一方面,其亦可能因有限理性挤出效应和短期财务目标的导向而带来潜在负面影响。基于中国国家大数据综合试验区的高污染企业样本,本研究引入技术—组织—环境(TOE)框架,运用面板数据模糊集定性比较分析(PD-fsQCA),系统梳理数字战略、数字技术、内部控制质量、企业环境关注配置、区域环境规制与公众环境关注等要素的交互作用。研究结果揭示了多条影响ESG绩效的配置路径,包括“IC & DT驱动型”“ER & DS驱动型”与“DT & DS驱动型”,并显示出显著的时间性与组织异质性。这一发现不仅深化了对数字化转型多维影响机制的理解,也为高污染企业实现可持续转型提供了新的理论视角与实践启示。
01结构化摘要
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.
关键词:Digital transformation, ESG performance ,Heavy polluting enterprises ,PD-fsQCA
原文引用:Li Jing, Li Qianqiang, Chen Yantai, An Qi. How digital transformation facilitates ESG performance to heavy polluting enterprises: A panel fsQCA based on national big data comprehensive pilot zones[J]. Technological Forecasting & Social Change 221 (2025) 124366. https://doi.org/10.1016/j.techfore.2025.124366
02期刊简介
Technological Forecasting And Social Change(TFSC)是一本在管理学领域享有国际盛誉的优秀杂志,由知名出版机构Elsevier主办并发行。该期刊致力于为直接探讨技术预测与未来研究方法论及实践的人士交流,这些研究作为规划工具,在社会、环境与技术因素之间建立关联,为ABS三星级期刊。自1969年创刊以来,该期刊一直致力于发表管理学领域的专业学术论文,展现独特且具有前瞻性的科研成果。国际刊号为ISSN:0040-1625,在2024-2025年的影响因子为13.3。它不仅是学术交流的重要平台,更促进了国内外同行间的深入研讨与思想碰撞,为管理学的发展做出了卓越贡献。
来源/浙江工商大学全球数字创新链研究