Does the Government’s Attention to Digital Talent Foster Digital Transformation Among Enterprises in China? Evidence from a Data-Driven Tripartite Institutional Policy, Technology, and Spatial Framework

Digital transformation (DT) has become a core strategic priority for major economies, with global investments exceeding $2 trillion worldwide and $0.55 trillion in China alone in 2025. As DT reshapes the norms of international competitiveness and sustainable development, experts frequently emphasize the need for innovative cross-domain frameworks to decode the mechanisms of DT success. Even though public economists view government attention to digital talent (GADT) as a key driver of DT, there is an acute shortage of empirical models that explain how it affects firm-level DT directly or indirectly through intermediary mechanisms, e.g., talent agglomeration, absorptive capacity, and subsidies. Thus, exploring this relationship empirically holds significant theoretical and practical value. Based on the latest keyword frequency data from government policies and annual reports from 2008 to 2022 for 3952 A-share listed companies across 243 cities in 31 provinces, this study constructs an interactive two-way fixed-effects panel regression model with 35,058 valid observations. The empirical results show that GADT significantly promotes the digital transformation of enterprises (EDT), supported by enterprise talent agglomeration, absorptive capacity, and government digital talent subsidies. Notably, the effects of GADT on EDT were heterogeneous, with a significant positive impact observed in labor-intensive enterprises, peripheral cities, and enterprises in non-digital-economy pilot areas. Moreover, the effects of GADT on EDT were less pronounced among technology-intensive enterprises (e.g., automotive, pharmaceutical, and manufacturing), central cities (e.g., Chengdu, Fuzhou), and those in digital economy pilot areas (e.g., Xinjiang, Ningxia). This study aims to examine the impact mechanism of GADT on EDT, thereby providing theoretical support and practical implications for more targeted and effective digital talent policies.