HOW FIRM’S DIGITAL TRANSFORMATION INFLUENCE ITS INNOVATION PERFORMANCE: EMPIRICAL EVIDENCE FROM CHINA
Keywords:
Digital transformation, innovation performance, government subsidy, manufacturing firms, China manufacturing firms, fixed effect model, empirical analysisAbstract
In recent years, firms across industries have increasingly adopted digital technologies to boost their competitive edge and innovation. Despite this growing focus, there is a lack of empirical studies examining the impact of digital transformation on innovation performance in Chinese manufacturing firms. This study uses a fixed effect model investigates the impact of digital transformation on the innovation performance of 3,678 Chinese manufacturing firms from 2016 to 2023. Our findings indicate that digital transformation significantly enhances innovation performance, with a regression coefficient of 4.146 (p < 0.01), suggesting a 41.5% improvement in innovation output for firms adopting digital technologies. Consistent results were observed across control variables such as firm size, total assets, and firm age. Furthermore, the research explores the role of government subsidies, indicating that while these subsidies may hinder digital transformation efforts, they significantly affect innovation performance when controlling for other variables. This dual focus on digital transformation and government subsidies is novel, as it provides a comprehensive understanding of how both factors interact and affect innovation in the context of Chinese manufacturing. Overall, this research highlights the crucial role of digital transformation in fostering innovation and calls for policymakers to strategically refine subsidy programs to better support firms’ innovation objectives. For firms undergoing digital transformation, it is recommended that they strategically invest in digital
technologies that align with their innovation goals to achieve a competitive edge in an increasingly dynamic technological landscape. However, this study is limited by its focus on Chinese ...
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