Abstract Taking non-financial Shanghai and Shenzhen A-share listed companies from 2009 to 2020 as samples, this study empirically investigates the impact of big data applications on financial market stability, with the risk of stock price crashes as an entry point. The results reveal that big data applications can reduce the risk of stock price crashes, thereby enhancing financial market stability. Moreover, this relationship becomes more pronounced when companies hire executives with an information technology background and are located in big data comprehensive pilot zones. Mechanism studies reveal that big data applications primarily mitigate crash risks through two paths: increasing regulatory intensity and optimizing decision-making efficiency. Besides, this study dynamically analyzes the crash risk suppression effect of big data applications based on the enterprise life cycle. It finds that the suppression effect is most pronounced in the mature stage, followed by the growth stage, and absent in the decline stage.
PAN Zicheng,BAI Shuyuan,YI Zhigao等. Research on the Impact of Enterprise Big Data Application on Stock Price Crash Risk[J]. Chinese Journal of Management, 2025, 22(5): 948-.
