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数字化转型对制造业全要素生产率的影响:来自中国上市公司的证据

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数字生产力逐渐展现出强大的驱动力,数字化转型成为主导趋势,这能否提升中国制造企业全要素生产率?文章基于2007-2019年A股上市公司数据,通过机器学习文本分析方法构建企业层面数字化转型指标,实证检验了数字化转型对全要素生产率的影响及其渠道机制.结果显示,数字化转型对企业全要素生产率具有促进作用,且这种作用是非线性的,具有人力资本水平、数字基础设施建设的单门槛特征和企业创新能力的双门槛特征.企业数字化转型通过降低供应链集中度和经济政策不确定性感知度对全要素生产率产生影响.研究结果从微观层面为企业数字化转型对全要素生产率的影响提供了直接证据,为实体经济企业高质量发展提供了政策见解.
The Impact of Digital Transformation on Total Factor Productivity in Manufacturing:Evidence from Publicly Listed Companies in China
Digital productivity is gradually showing a strong driving force,and digital transformation has become the dominant trend.Can this improve the total factor productivity of Chinese manufacturing enter-prises?Based on the data of listed companies from 2007 to 2019,this paper constructs enterprise-level dig-ital transformation indicators through machine learning text analysis method,and empirically tests the im-pact of digital transformation on total factor productivity and its channel mechanism.The results show that digital transformation can promote the total factor productivity of enterprises,and this effect is non-linear,with human capital level,digital infrastructure construction single threshold characteristics and en-terprise innovation ability double threshold characteristics.Enterprise digital transformation has an impact on total factor productivity by reducing the concentration of supply chain and the perceived uncertainty of economic policy.The research results provide direct evidence for the impact of enterprise digital transfor-mation on total factor productivity from the micro level,and provide policy insights for the high-quality de-velopment of real economy enterprises.

digital transformationtotal factor productivitymachine learningthreshold effect

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浙江工业大学经济学院,杭州 310014

数字化转型 全要素生产率 机器学习 门槛效应

2024

上海管理科学
上海市管理科学协会

上海管理科学

CHSSCD
影响因子:0.466
ISSN:1005-9679
年,卷(期):2024.46(4)