The year 2010 marked a significant turning point for China's economy, witnessing a shift towards a digital economy driven by digital transformation and innovation. While existing research has explored the link between digital transformation and general technological innovation, few studies have focused on its impact on disruptive innovation, particularly considering the role of entrepreneurship. This study aims to fill this gap by developing an analytical framework integrating digital transformation, entrepreneurship, and disruptive innovation. The researchers highlight the importance of digital transformation for corporate survival and growth in China, emphasizing its role in addressing information asymmetry, enhancing collaboration, accelerating innovation, and improving operational efficiency. The study emphasizes the need for empirical evidence at the firm level, considering the unique context of China's economic development and the increasing importance of non-state-owned enterprises (non-SOEs) and entrepreneurship.

The literature review categorizes existing studies on digital transformation and innovation into three groups: those exploring the dynamic capabilities perspective, those focusing on firm lifecycle stages, and those analyzing the impact on financing constraints. While acknowledging these contributions, the authors point out a gap in research on digital transformation's impact on disruptive innovation specifically. Furthermore, the literature review highlights the significance of entrepreneurship as a driving force for economic growth and innovation, emphasizing its role in unleashing creativity and opening new economic possibilities. The authors define entrepreneurship in this study as the innovative conduct of economic actors who are encouraged enough to embrace risks and are open to collaboration. The study argues that entrepreneurship plays a crucial role in achieving disruptive innovation, particularly in the context of China's evolving economic landscape and the rise of the digital economy.

The study uses data from China's A-listed firms from 2010 to 2021, excluding those in the financial sector. Data was sourced from the China Stock Market & Accounting Research (CSMAR) database and Management Discussion & Analysis (MD&A) texts from JUCHAO. The sample was screened to exclude special treatment companies and those with significant data deficiencies, resulting in 22,200 observations. The main variables were winsorized to mitigate the impact of outliers. Python was used for text mining and analysis, while Stata15 was used for data processing. The key variables were measured as follows: 1. **Disruptive Innovation (InCitepatent):** Measured using the number of forward patent citations within five years of patent disclosure, reflecting the influence of the innovation. 2. **Digital Transformation (DT_txt):** Measured using text mining analysis of MD&A texts, counting the frequency of 76 words related to digital transformation across five sub-dimensions: artificial intelligence, big data, cloud computing, blockchain, and digital technology application. A second measure (DT_num) was also used, based on the proportion of digital economy-related assets (software, electronic equipment etc.) to the total net asset value. 3. **Entrepreneurship (ENT):** A composite index created using entropy weighting of three indicators: self-generated capital satisfaction rate, R&D investment intensity, and whether the firm jointly applied for patents. 4. **Control Variables:** Firm age, nature of ownership (SOE/non-SOE), firm size, board size, board independence, top 10 shareholders' shareholding, leverage, liquidity ratio, and return on total assets (ROA). Time and industry fixed effects were also controlled for. Two models were used. Model (1) tested the relationship between digital transformation and disruptive innovation. Model (2) incorporated entrepreneurship as a moderating variable to test its influence on the relationship between digital transformation and disruptive innovation. Robustness checks were conducted by replacing the digital transformation variable and adding additional control variables. Endogeneity tests were performed by lagging the explanatory and control variables.

The regression analysis revealed that digital transformation (DT_txt) significantly and positively impacts disruptive innovation (InCitepatent) at the 1% significance level, supporting Hypothesis 1 (H1). This positive effect remained robust after conducting robustness checks and endogeneity tests. The results suggest that digital transformation strategies facilitate disruptive innovation by optimizing resource allocation, reducing R&D costs, improving efficiency, and creating novel value delivery methods. Furthermore, the analysis incorporating entrepreneurship as a moderating variable (Model 2) showed that entrepreneurship significantly and positively moderates the relationship between digital transformation and disruptive innovation (the interaction term DT_txt*ENT was significant at the 5% level), supporting Hypothesis 2 (H2). This indicates that the positive effect of digital transformation on disruptive innovation is stronger in firms with higher levels of entrepreneurship. Heterogeneity analyses revealed significant differences across various groups: * **Ownership:** The positive relationship between digital transformation, entrepreneurship, and disruptive innovation was more pronounced in non-SOEs compared to SOEs. In SOEs, entrepreneurship alone was significant, whereas digital transformation's effect and the interaction term were not significant. * **Industry:** The positive relationship held true for non-manufacturing firms but not for manufacturing firms. * **Firm Lifecycle:** The positive impact of digital transformation on disruptive innovation was evident for firms in growth, maturity, turbulence, and recession stages, but not for start-up firms. The moderating role of entrepreneurship was significant only for firms in growth and decline stages.

The findings support the hypothesis that digital transformation positively influences disruptive innovation, and that this relationship is strengthened by the presence of entrepreneurial characteristics. The heterogeneity analysis highlights the contextual nature of this relationship, underscoring the importance of considering factors like firm ownership, industry, and lifecycle stage when implementing digital transformation strategies. The stronger effect in non-SOEs could be attributed to their greater market orientation and stronger innovation incentives. The absence of a significant effect in manufacturing firms could be due to the higher rigidity and established processes in this sector. The lifecycle analysis suggests that the benefits of digital transformation are more pronounced in later stages of a firm's development when resources and capabilities are more established.

This study contributes to the literature by demonstrating the significant positive effect of digital transformation on disruptive innovation in Chinese firms, and by highlighting the moderating role of entrepreneurship in this relationship. The findings offer valuable insights for businesses seeking to leverage digital technologies for disruptive innovation. Future research could explore the generalizability of these findings to other national contexts, investigate alternative measures of disruptive innovation and entrepreneurship, and delve deeper into the specific mechanisms through which digital transformation and entrepreneurship interact to promote disruptive innovation.

The study's limitations include the focus on a specific time period (2010-2021) and a specific geographical context (China), limiting the generalizability of the results. The measure of entrepreneurship, based on only three indicators, might not fully capture the complexity of the construct. The reliance on self-reported data from MD&A texts for measuring digital transformation might introduce some bias. Finally, the study's causal inferences are based on correlational analysis, and future studies employing experimental designs or instrumental variables would strengthen the causal link.