Cao Guohua, Ye Huihui
School of Economics and Business Administration, Chongqing University, Chongqing, China.
PLoS One. 2025 Sep 9;20(9):e0331845. doi: 10.1371/journal.pone.0331845. eCollection 2025.
This study investigates the impact of data assets on enterprise persistent innovation using panel data from Chinese A-share listed firms from 2011 to 2022. The results indicate that data assets significantly enhance both the inputs and outputs of enterprise persistent innovation, with the findings remaining robust under endogeneity tests. Mediation analysis reveals that data assets influence enterprise persistent innovation through three key channels: process innovation, business innovation, and technological innovation. The development of digital finance positively moderates this relationship across three dimensions of coverage, depth, and digitalization, indicating that digital finance amplifies the persistent innovation value of data assets. Heterogeneity analyses reveal that the persistent innovation input improves more in non-state-owned enterprises, digitally advanced firms, and non-manufacturing sectors, whereas output enhancement is most evident in large enterprises, highly digitalized firms, and organizations with strong absorptive capacity. These findings contribute to a deeper understanding of data-driven persistent innovation and provide valuable insights for policymakers developing data markets, and for firms formulating data strategies aligned with their capabilities.
本研究利用2011年至2022年中国A股上市公司的面板数据，考察数据资产对企业持续创新的影响。结果表明，数据资产显著提高了企业持续创新的投入和产出，且在内生性检验下结果依然稳健。中介效应分析表明，数据资产通过流程创新、业务创新和技术创新这三个关键渠道影响企业持续创新。数字金融的发展在覆盖范围、深度和数字化这三个维度上正向调节这种关系，表明数字金融放大了数据资产的持续创新价值。异质性分析表明，非国有企业、数字化先进企业和非制造业部门的持续创新投入改善更多，而大型企业、高度数字化企业和具有强大吸收能力的组织的产出提升最为明显。这些发现有助于更深入地理解数据驱动的持续创新，并为制定数据市场政策的政策制定者以及制定与其能力相匹配的数据战略的企业提供有价值的见解。
