摘要
以中国A股上市企业2007—2022年数据为样本,运用机器学习文本分析方法识别环境新闻报道及其情感倾向,实证检验媒体环境报道对企业绿色技术创新的影响与作用机制。研究发现:媒体正面环境报道和负面环境报道均能促进企业绿色技术创新。机制分析发现,媒体正面环境报道能够增加企业绿色信贷额度和绿色技术创新投入,而媒体负面环境报道可以减轻管理者短视主义和提高企业环境责任表现。异质性分析表明,政策导向型媒体的负面环境报道和财经类媒体的正面环境报道对企业绿色技术创新的促进作用更加明显。
Using data from Chinese A-share listed companies from 2007 to 2022 as a sample,this paper employs machine learning text analysis methods to identify environmental news reports and their sentiment.It empirically examines the impact of media environmental reporting on corporate green technology innovation and explores the underlying mechanisms.Results show that both positive media environmental reporting and negative media environmental reporting can promote corporate green technology innovation.The mechanism analysis shows that positive media environmental reporting can increase corporate green credit limits and investment in green technology innovation,while negative media environmental reporting can mitigate managerial myopia and improve corporate environmental responsibility performance.In terms of heterogeneity analysis,negative policy-oriented media coverage and positive financial media coverage are more likely to promote the quantity and quality of corporate green technology innovation.
作者
何冰洋
邓晶晶
周积琨
HE Bingyang;DENG Jingjing;ZHOU Jikun(College of Finance and Statistics,Hunan University,Changsha 410006;School of Economics,Hunan Agricultural University,Changsha 410125,China)
出处
《湖南科技大学学报（社会科学版）》
CSSCI
北大核心
2024年第5期85-94,共10页
Journal of Hunan University of Science and Technology(Social Science Edition)
基金
国家自然科学基金面上项目(72073043)。
关键词
媒体环境报道
媒体情绪
企业绿色技术创新
专利数量
专利质量
media environmental reporting
media sentiment
corporate green technology innovation
patent quantity
patent quality
