Understanding the Impact of Spatial Externalities on Two-Stage R&D Efficiency: Empirical Evidence from 285 Chinese Prefecture-Level Cities

This study applies a spatial Durbin model to empirically investigate the impacts of local agglomeration, regional adjacency, and inter-regional network externalities on research and development (R&D) efficiency employing datasets of 285 Chinese prefecture-level cities covering the period of 2004 to 2020. This highlights the importance of understanding the different types of spatial externalities from a two-stage R&D perspective. The sequential stages of R&D process were identified as knowledge creation and technology transfer with each stage displaying significant spatial heterogeneity in the prefecture-level cities that were assessed. Inter-regional network externalities were shown to be more advantageous for knowledge creation efficiency, whereas local agglomeration externalities exerted a stronger positive influence on technology transfer efficiency. Furthermore, regional adjacency externalities were shown to significantly enhance R&D efficiency, particularly in relation to technology transfer rather than knowledge creation. The findings demonstrate that the significance of local agglomeration, regional adjacency, and inter-regional network externalities varies significantly throughout distinct R&D stages.