数据资产化对“专精特新”企业创新产出的影响研究

Research on the Impact of Data Assetization on the Innovation Output of “Specialized, Refinement, Differential and Innovation” (SRDI) Enterprises

摘要:

在数字经济与实体经济深度融合、新质生产力加速培育的时代背景下,数据要素已成为驱动产业升级与经济高质量发展的核心生产要素。 数据资产化作为数据资源向生产要素转化、实现价值闭环的关键路径,是推动数字经济纵深发展、赋能企业创新升级与新质生产力培育的核心战略支撑。 基于 2011—2021 年沪深 A 股上市公司数据,以“专精特新”企业为研究对象,定量分析了企业数据资产化对其创新产出的影响及作用机制。 结果表明,数据资产化显著提升了“专精特新”企业的创新产出水平,该结论在内生性处理、替换核心变量等一系列稳健性检验后依然成立。 机制检验显示,数据资产化可通过缓解企业融资约束与技术赋能两条渠道提升专精特新企业创新产出。 进一步异质性分析发现,该创新激励效应在非国有企业及金融科技发展水平较高地区的企业中更为显著。 研究结论丰富了数据要素经济效应与企业创新领域的相关文献,为政府推进数据要素市场化改革、企业激活数据资产价值以培育新质生产力提供了扎实的经验证据与决策参考。

Abstract:

Against the backdrop of the deep integration of the digital economy and the real economy, new quality productive forces are being cultivated at an accelerated pace. The data factor has become a core factor of production driving industrial upgrading and high-quality economic development. Data assetization is regarded as a critical pathway for transforming data resources into factors of production and for realizing a closed value loop. It serves as core strategic support for advancing the in-depth development of the digital economy, empowering enterprise innovation and upgrading, and fostering new quality productive forces. Based on data from A-share listed companies in Shanghai and Shenzhen from 2011 to 2021, “specialized, refined, distinctive and innovative” enterprises were taken as the research subjects. A quantitative analysis was conducted on the impact of corporate data assetization on innovation output and its underlying mechanisms. A significant enhancement of innovation output was observed as a result of data assetization. This conclusion remained valid after a series of robustness checks, including endogeneity treatment and core variable replacement. Two channels were identified through which data assetization improves innovation output: the alleviation of financing constraints and technological empowerment. A significant boundary difference was found in this innovation incentive effect through further heterogeneity analysis. The effect was more pronounced in non-state-owned enterprises and in regions with higher levels of fintech development. The relevant literature on the economic effects of data factors and enterprise innovation was enriched by these findings. Solid empirical evidence and decision-making references were provided for the government to advance the market-oriented reform of data factors,as well as for enterprises to unlock the value of data assets to foster new quality productive forces.