西部论坛2024，Vol.34Issue(3)：54-73,20.DOI:10.3969/j.issn.1674-8131.2024.03.005
数据资产如何赋能企业高质量发展
Empowering High-quality Development of Enterprises with Data Assets:Optimization Mechanism of Traditional Production Factors
摘要
Abstract
In the era of the digital economy,accelerating the construction of Digital China and promoting high-quality development of the real economy are important engines for advancing Chinese modernization.Against this background,data is experiencing exponential growth,driving profound changes in social production and lifestyles.Enterprise data assets have also become a focal topic in academia.As a new factor of production in the digital economy era,data assets are embedded in various fields of the real economy,relying on data industrialization and industrial data-oriented businesses,serving as a key factor in talent upgrading,technological innovation,optimal capital allocation,and management efficiency improvement,thereby promoting high-quality development of enterprises. Based on the data of A-share listed companies in Shanghai and Shenzhen Stock Markets from 2007 to 2022,this paper describes the data assets using text analysis,tests its influence on the high-quality development of enterprises and its mechanism of action,and identifies the regulatory effects in different external environments.It is found that data assets are the effective driving force of high-quality development.This conclusion is still valid after the robustness test and the endogeneity test.The mechanism test shows that the application of data assets can improve the development quality of enterprises through four channels:human resource optimization mechanism,capital allocation improvement mechanism,technology resource accumulation mechanism,and management resource efficiency mechanism.Further analysis shows that,for the areas with high environmental uncertainty,information level,marketization degree,and government's concern about the digital economy,data assets have a more significant role in promoting the high-quality development of enterprises.The conclusion of this paper provides a micro-theoretical basis and policy enlightenment for enterprises to use data assets to promote the optimization and upgrading of traditional production factors and achieve high-quality development. The marginal contributions of this paper are as follows:firstly,in terms of research content,this paper examines the impact of data assets on the high-quality development of enterprises,not only providing a"new perspective"for high-quality development but also expanding the economic consequences of data assets from the dual attributes of"data"and"assets".Secondly,in terms of variable measurement,this paper selects seed words based on the underlying logic of data asset"acquisition-processing-application",uses the Autophrase method to construct a"data asset"text dictionary,and then mines textual information from annual reports through sentiment analysis to measure the level of enterprise data assets.Furthermore,the validity of this indicator is verified through feature word spectrum tests and comparative tests,providing useful references for innovating the measurement of enterprise data asset levels.Thirdly,in terms of analysis perspective and mechanism testing,this paper takes data assets as a new factor of digital economic development and the basic fact that they can substitute inputs and optimize resources for traditional production factors as a research starting point,providing evidence for the impact of enterprise data asset mechanisms on high-quality development through four channels:human resources optimization mechanism,capital allocation improvement mechanism,technological resource accumulation mechanism,and management resource efficiency enhancement mechanism,and further discusses the regulatory effects of regional and industry environments,providing theoretical support and empirical evidence for differentiated strategies for high-quality development of enterprises.关键词
数据资产/高质量发展/传统生产要素/劳动力结构/资本配置效率/技术水平/管理效率Key words
data assets/high-quality development/traditional production factors/labor structure/capital allocation efficiency/technical level/management efficiency分类
管理科学引用本文复制引用
苑泽明,尹琪,于翔..数据资产如何赋能企业高质量发展[J].西部论坛,2024,34(3):54-73,20.基金项目
国家社会科学基金一般项目(23BGL109) （23BGL109）
