Digital transformation as a catalyst for resilience in stock price crisis: evidence from a ‘New Quality Productivity’ perspective

Abstract

This study explores the impact of digital transformation on stock price crash risk using Chinese A-share listed enterprises from 2011 to 2022. Leveraging the TF-IDF algorithm and deep learning models, it contextualizes digital transformation within China's “new quality productivity” framework, which prioritizes technological innovation over traditional productivity drivers. The findings reveal that digital transformation significantly reduces stock price crash risk, particularly in labor and capital-intensive sectors, by enhancing market transparency and decreasing information asymmetry. Furthermore, the integration of digital transformation with the “new quality productivity” framework amplifies this protective effect, with pronounced benefits for large firms and those covered by analysts or research reports. Conversely, smaller firms or those without such coverage experience a smaller impact. By demonstrating how advanced digital technologies bolster operational agility and investor confidence, this study highlights the critical role of digital transformation in fostering resilience and stabilizing stock prices during crises.