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作 者:张家峰[1] 王世豪 吴松强[1] Zhang Jiafeng;Wang Shihao;Wu Songqiang(School of Economics and Management,Nanjing Tech University,Nanjing 211816,China)
机构地区:[1]南京工业大学经济管理学院,江苏南京211816
出 处:《创新科技》2024年第10期61-71,共11页Innovation science and technology
基 金:国家社会科学基金项目“集成电路产业集群韧性测度、影响因素与提升路径研究”(21BJY020)。
摘 要:基于数字化转型视角,选取长三角地区共31家集成电路上市企业作为研究对象,运用三阶段DEA模型测算其技术创新效率。研究发现:①DEA-BCC模型结果显示,2016—2020年样本企业的整体技术创新效率较低,而材料和设备行业企业的技术创新效率值相对较高。②SFA模型结果显示,企业技术创新效率受数字化转型程度、经济发展水平、市场竞争强度、对外开放程度和政策支持力度等环境因素的影响。③调整后的DEA-BCC模型结果显示,在剔除环境因素和随机干扰项的影响后,综合效率和纯技术效率水平有所提升,规模效率变化不显著,但整体仍然较低,主要原因是纯技术效率水平不高。④Tobit模型结果显示,资产负债率、营业净利率、独立董事比例与综合效率呈正相关,研发人员占比对综合效率具有负向影响,第一大股东持股比例和企业规模对综合效率无显著影响。Promoting the digital transformation of the integrated circuit industry plays an im-portant role in upgrading national manufacturing,in line with the State Council's"14th Five-Year Plan for Digital Economy Development"strategy of building a strong digital economy.The integrated circuit industry is a crucial component of modern manufacturing and holds strategic significance and competitive advantages globally.Therefore,studying the innovation efficiency of this industry from a digital transformation perspective is essential for achieving high-quality development.However,current research on the technological innovation efficiency of the inte-grated circuit industry is limited,especially from the viewpoint of digital transformation.This study focuses on listed integrated circuit companies in the Yangtze River Delta,utilizing a three-stage DEA model to measure and decompose innovation efficiency and a Tobit regression model to analyze key influencing factors.The research data mainly come from the CSMAR database and various statistical yearbooks.Findings reveal low overall innovation efficiency from 2016 to 2020,with significant positive correlations between innovation efficiency and digital transforma-tion levels and government policy support,while negative correlations exist with economic devel-opment level,market competition intensity,and openness.Adjusted DEA-BCC model results show improvements in comprehensive efficiency,technical efficiency,and scale efficiency.How-ever,overall levels remain low,primarily due to insufficient technical efficiency.According to the Tobit regression,factors such as debt ratio,major shareholder ownership,R&D personnel ra-tio,company size,net profit margin,and independent director ratio have an impact on innovation efficiency.Notably,the R&D personnel ratio is negatively correlated with comprehensive effi-ciency,highlighting the importance of quality over quantity.This study suggests actively advanc-ing digital transformation,optimizing capital structure,and improving management model
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