Intercity Scientific Research Cooperation,Network Structure Embedding,and Knowledge Innovation Convergence
Establishing regional scientific and technological innovation networks is essential for coordinating innovation-driven and regional development strategies.Unlike prior studies that focused mainly on patent data and neglected intercity scientific cooperation and the relationship between network structure and knowledge innovation convergence,this paper explores the pathways through which scientific collaboration networks influence knowledge convergence.Based on economic convergence and social network theory,it identifies the cooperative accumulation effect,knowledge diffusion effect,and network structure effect as key factors accelerating knowledge convergence.Using panel data from 283 Chinese cities from 2000 to 2020 and manually collected scientific publications and cooperation data,the paper examines the impact of cooperation networks on knowledge innovation convergence.Key findings include:Both the scale and quality of knowledge innovation in China exhibit σ convergence,absolute β convergence,and conditional β convergence,with quality converging faster than quantity,and the highly cited papers show an annual decline in variation of 1.7 percentage points greater than usualpapers.Considering network characteristics such as centrality and structural holes,the convergence rate of overall knowledge innovation is further improved,scientific collaboration networks shorten the time to eliminate gaps between lagging and leading regions by 2.23 years compared to baseline results.For most cities,increasing centrality and enriching structural holes accelerate regional convergence.The conclusions suggest that,non-scientific center cities should integrate into national scientific networks to narrow the knowledge gap and reduce regional imbalances,while the scientific center cities can use their network positions to build information platforms,fostering collaboration for regions without direct connections,thus achieving high-level regional knowledge convergence.
NETL
NSTL
万方数据
