Empowering innovation in small and medium-sized enterprises through public data openness: Mechanism exploration and empirical evidence based on “specialized, refined, distinctive, and innovative” enterprises

This study draws on public data openness policies of local governments and micro-level data from A-share listed enterprises across 30 provinces in China from 2011 to 2022. Thus, the study examines the mechanisms through which public data openness affects the innovation quality of “specialized, refined, distinctive, and innovative” (SRDI) enterprises. Furthermore, it analyzes the mediating effects of artificial intelligence (AI) development and enterprise research and development (R&D) costs, as well as the moderating effects of government subsidies, information infrastructure, and industrial agglomeration. The results indicate that public data openness significantly enhances the innovation quality of SRDI enterprises. However, this impact varies across regions, industries, and types of enterprises: inland cities, areas with lower education levels, and regions with underdeveloped digital infrastructure exhibit stronger effects. Non-state-owned enterprises are more responsive to public data openness compared to state-owned ones, and non-manufacturing enterprises benefit more than manufacturing ones. Mediation analysis indicates that public data openness enhances innovation capability, primarily by increasing local AI development and reducing R&D costs. Moreover, government subsidies and information infrastructure strengthen this positive effect, while industrial agglomeration may suppress it.