本文基于2015—2019年中关村海淀科技园企业数据集，探究数字技术提升企业业绩的效应与机制。研究发现：数字技术的应用显著提升了企业业绩，并且多项数字技术融合应用的乘数效应显著，尤其是大数据与云计算平台的深度融合对企业业绩的提升效果最佳。该结论在经过倾向匹配得分、工具变量等内生性处理后依然成立。机制研究表明，优化人才结构、提高创新能力、改善成本结构以及提升资源配置效率是数字技术提升企业业绩的重要机制。异质性分析发现，数字技术对企业业绩的提升效果在大型企业、中国港澳台及外商控股企业表现更好，并且行业异质性使处于不同生命周期阶段的企业的数字化转型效果存在明显差异，因此企业应根据自身特点合理规划数字化转型路径。本文为数字化赋能企业高质量发展提供了微观证据。
Abstract
Promoting the deep integration of the Internet, big data, artificial intelligence, and other traditional industries is the new driving force for the development of the digital economy and a new engine to bring into play the innovation of data elements. However, Accenture (2020) shows that digital technology has only brought about business performance growth in 11% of Chinese companies, with the majority of companies not translating digital momentum into benefits. This is in line with the "IT productivity paradox" proposed by Roach (1987). The fundamental issue in strengthening the digital economy is to give full play to the role of digital technology as an engine for business growth, especially for traditional enterprises, which need to find new growth momentum through digital transformation. Nevertheless, in the face of the new round of technological and industrial revolution, enterprises often blindly deploy digitalization in silos, resulting in a lack of matching between digitalization strategies and business models, process reorganization, management models, and information construction, making the implementation path blurred. At the same time, many enterprises in the real economy are less aware that the data resources generated during the business life cycle of an enterprise can be used to improve production and operation efficiency and reduce production costs, and some enterprises that have already invested have doubts about continuing to invest due to the "painful period". The dilemma of "not transforming and waiting for death, transforming and looking for death". This paper systematically studies the impact of digital technology on corporate performance and intermediate mechanisms at the micro-level, which has important research and practical implications for the precise launch of digital transformation and the release of dividends from the digital economy.
There has been a range of academic exploration around the digital economy. Broadly speaking, research on the digital economy, with digital technology as the core driver, has been conducted from two perspectives: macroeconomic impact and micro-enterprise impact. The first category of literature focuses on national economies and analyses the macroeconomic impact of digital technologies from the perspectives of economic development, consumer behavior, technological advancement, and import/export trade, arguing that the application of digital technologies promotes consumer spending and regional entrepreneurship, effectively increases the resilience and productivity of urban economies, and enhances the division of labor in a country′s global value chain and the scale of international trade, thus gradually releasing the impact of digital technologies on high-quality economic development. The second strand of the literature focuses on enterprises. The second type of literature takes enterprises as the main subject of research, and analyses the effects of digital technology and the underlying mechanisms from the perspectives of enterprise innovation performance and enterprise value. Data, as the core of the digital transformation and upgrading of enterprises, has led to the concentration of technology, capital, and talent in more efficient areas, and the deep integration in the business, production model, and organizational structure of enterprises have achieved a balance between cost reduction, quality improvement, efficiency enhancement, and resource allocation, resulting in innovation and value enhancement. However, over-investment in digitalization is not conducive to the enhancement of enterprise value. Zhou Qing (2020) and Han Xianfeng (2019) found that the level of digitization showed non-linear characteristics with innovation performance. The majority of existing studies are based on macro data or survey data, the former failing to dig deeper into the micro-mechanics of the digital economy, the latter having certain shortcomings in terms of data authority and sample size, while the few that use data from listed companies do not yet reflect the digital transformation characteristics of micro and small enterprises.
This paper explores the effects and mechanisms of digital technologies to enhance enterprise performance based on the dataset of enterprises in Haidian S&T Park in Zhongguancun from 2015 to 2019. The following conclusions are drawn from this paper: Firstly, the application of digital technologies significantly improves enterprise performance, and the multiplier effect of the integration of multiple digital technologies is more significant, reaching an effect of 1+1>2, especially the deep integration of big data and cloud computing platform has the best effect on performance improvement. This conclusion still holds after endogeneity treatments such as propensity matching scores and instrumental variables. Secondly, the mechanism study shows that talent optimization, innovation empowerment, cost structure, and resource allocation efficiency are important mechanisms for digital technology to enhance business performance. Finally, Heterogeneity analysis reveals that the performance-enhancing effects of digital technology are better in large enterprises, Hong Kong, Macau, Taiwan of China and foreign-controlled enterprises, and that industry heterogeneity leads to significant differences in the transformation effects of enterprises at different lifecycle stages, so enterprises should plan their digital transformation paths according to their characteristics. This paper provides micro-evidence for digital-enabled enterprise growth and digital economy-enabled quality development.
关键词
数字技术 /
企业业绩 /
工具变量 /
企业创新 /
中关村海淀科技园
Key words
digital technology /
enterprise performance /
tool variable /
enterprise innovation /
Haidian S&T Park in Zhongguancun
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基金
国家社会科学基金重大项目：“多重复杂背景下中国经济‘双循环’接驳及其协同性、有效性的统计研究”（21&ZD151）；全国统计科学研究：“大数据背景下企业创新网络结构关系的统计解析”（2020LY072）；北京市教委社会科学计划一般项目：“孵化器助力中关村创业发展的成效与机理研究”（SM202010011011）。
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