大数据发展对企业数字技术创新的影响研究——基于国家大数据综合试验区的准自然实验
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Research on the Impact of Big-data Development on Enterprise Digital Technology Innovation: Quasi-natural Experiment Based on the National Big Data Comprehensive Pilot Zone
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    摘要:

    数字技术的发展和应用使数据成为数字经济的核心生产要素,而大数据的发展又会推动数字技术的进一步发展。将国家大数据综合试验区的设立作为一项准自然实验,用数字技术专利来衡量企业数字技术创新水平,采用多期双重差分模型对2007—2020年沪深两市A股上市公司的分析发现:设立国家大数据综合试验区显著促进了试验区内企业数字技术创新水平的提升,该结论在控制宏观经济因素及其他政策干扰、替换被解释变量、安慰剂检验、PSM-DID检验、工具变量法等稳健性检验中均成立;设立国家大数据综合试验区对试验区内企业产生了显著的信息改善效应、治理改进效应和资源获取效应,从而有效促进了企业数字技术创新;设立国家大数据综合试验区对风险承担能力较强企业、非衰退期企业、与ICT关联度较高行业企业的数字技术创新促进作用较大。各地区应积极推动大数据发展,并充分发挥大数据综合试验区的示范引领作用与辐射带动作用,形成以数字技术进步推动大数据发展、以大数据发展促进数字技术创新的良性循环。

    Abstract:

    As a new factor of production in the era of the digital economy, the data factor is different from the traditional factors of production such as labor, capital, and technology. It is not only the basic strategic resources but also the driving force of factors occupying new advantages in the international digital competition in the new era. In the context of the development of the digital economy, formulating relevant policies and measures, effectively promoting industrial innovation changes, and enterprises increasing their investment in digital technology innovation projects have important theoretical and practical significance. How to effectively promote enterprise digital technology innovation? The construction and improvement of the data factor market may be a breakthrough. However, the empirical analysis of the effect of big data development on the innovation of digital technology of enterprises is relatively scarce. In this paper, Python software is used to identify enterprise digital innovation patents, and based on the quasi-natural experiment of the national big data comprehensive pilot zone, the A-share listed companies in Shanghai and Shenzhen from 2007 to 2020 are taken as research samples, and the multi-period differential method is used to investigate the impact of big data on enterprise digital innovation and its mechanism. The analysis results show that the construction of the big data pilot area significantly improves the digital innovation performance of enterprises, and this conclusion is still valid on the basis of parallel trends, PSM-DID, placebo tests, and a series of robustness tests. In the big data pilot areas, the information effect, governance effect, resource effect, and other mechanisms have contributed significantly to the digital innovation of enterprises. In addition, the construction of a data factor market reduces the degree of information constraints, internal and external governance costs, and financing costs of enterprises, and helps improve enterprises’ digital innovation ability. Last but not least, heterogeneity analysis shows that the digital technology innovation effect of building enabling enterprises in big data pilot zones is not obvious in declining enterprises, enterprises with low risk-bearing capacity, and industries with low ICT intensity. Compared with the existing literature, from the perspective of research, this paper puts the macro-economic policies supporting the development of big data and micro-enterprise digital innovation activities in the same analytical framework, explores the dividend effect of big data development on enterprise digital innovation, and enriches the research literature of big data development policy evaluation. In terms of the research content, taking the establishment of the national big data comprehensive pilot zone as the exogenous impact, the paper discusses that the digital innovation of enterprises empowered by the development strategy of big data mainly depends on the “information effect”, “governance effect” and “resource effect”, and identifies the regional, industrial and enterprise heterogeneity influencing characteristics in the process of digital innovation of enterprises empowered by big data, deepening the existing research. In terms of research data, Python software is used to identify the text content of digital economy-related policies, and the obtained keyword frequency information is matched with the patent classification number to obtain the IPC classification number of digital innovation patents, so as to identify the enterprise digital innovation evaluation index more accurately. On this basis, the digital innovation effect of the big data pilot zone policy is further investigated to provide micro evidence for the policy evaluation of the big data comprehensive pilot zone. This study not only reveals the micro policy dividends of big data pilot zone construction, but also has important experience and enlightenment for formulating relevant policies of data factor market construction and promoting high-quality development of the real economy.

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戴艳娟,沈伟鹏,谭伟杰.大数据发展对企业数字技术创新的影响研究——基于国家大数据综合试验区的准自然实验[J].西部论坛,2023,33(2):16-28

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  • 在线发布日期: 2023-06-17