数据要素与绿色创新:基于新质生产力视角

Data Factors and Green Innovation:A Perspective of New Quality Productive Forces

数据要素是形成新质生产力的动力引擎,而绿色发展是衡量新质生产力发展水平的重要标尺,探究数字化与绿色化之间的内在逻辑成为当前备受关注的重要议题。本文利用2010-2022年中国A股制造业上市企业数据,实证研究了在新质生产力背景下,数据要素对企业绿色创新质量的影响机制与实现条件。研究发现,数据要素对企业绿色创新质量的提升具有积极影响;数据要素的绿色赋能作用在国有企业、高新技术企业、资本与技术密集型企业及低金融约束程度的企业中更明显;机制分析表明,数据要素能够通过提高企业创新投入和帮助企业获得政府支持的方式提升企业绿色创新质量;大数据技术水平和人力资本质量是数据要素驱动企业绿色创新的有效条件。本文的研究结论有助于实现新质生产力的数字化与绿色化“双化协同”,也为推动经济高质量发展提供有益借鉴。

With the accelerated advancement of the global technological revolution and industrial transformation,digitalization and greenization have become the most distinctive features of the new quality productive forces,and the deep integration and collaborative development between the two has become the core issue of current scientific exploration.As the core factor of new quality productive forces,data factors are the key engine driving the leapfrog development and transformation and upgrading of productive forces.Green development,as the inherent requirement and background of high‑quality development,is an important yardstick for measuring new quality productive forces.However,existing literature is limited to theoretical explanations and lacks empirical analysis based on enterprise data.There is still a lack of systematic and in‑depth research on how data factors can empower green innovation from the perspective of new quality productive forces.This paper uses the annual report data of listed companies,the China Stock Market&Accounting Research(CSMAR)database,and the Chinese Research Data Service Platform(CNRDS)database.It draws on the keyword mapping of Wu et al.(2021)and the measurement method of Shi et al.(2023)for the utilization of enterprise data factors.It assesses the application of data factors by enterprises by quantifying the disclosure frequency of keywords in the annual reports of manufacturing companies.Empirical research shows that data factors have a positive impact on the improvement of the quality of corporate green innovation.After considering endogeneity problems,replacing core variables,and changing estimation methods,the regression results remain robust.Further analysis shows that data factors have a more significant effect on the quality of green innovation in state‑owned enterprises,high‑tech enterprises,capital‑and technology‑intensive enterprises,and enterprises with low financial constraints.Its mechanisms cover multiple paths such as innovation investment and government support.At the same time,the progressiveness of data mining technology and the optimal allocation of human capital have become key conditions for the realization of data‑driven green innovation.This paper expands on existing literature in the following three aspects.First,it deepens the theory of new quality productive forces and expands the boundaries of green development theory.Secondly,considering the dynamics of Chinese industries and the socioeconomic background,it provides micro‑evidence of the positive impact of data factors on the quality of green innovation.Thirdly,from the perspective of the theory of productive forces,it comprehensively analyzes the mechanism and conditions for realizing data‑driven green innovation.