Impact of Factor Mobility on Corporate Innovation in the Yangtze Delta Region
This study utilizes Baidu Migration,Baidu Index big data,and deep learning algorithms to measure the level of factor mobility between cities in the Yangtze River Delta region.Combining this data with panel data from A-share listed companies,we conduct an in-depth analysis of the relationship between the scale and structure of factor mo-bility in the region and corporate innovation.The regression results of fixed effects model indicate that the scale of factor inflows in the Yangtze River Delta region has a significant positive impact on corporate innovation,and the diversity of the sources of these inflows is also positively correlated with corporate innovation.The conclusion remains valid after endo-geneity identification and robustness tests.Heterogeneity analysis reveals the mechanisms of the relationship between factor inflow structure and corporate innovation:on one hand,factor inflows from peripheral areas generate long-tail effects and sufficient diversity,making them more conducive to local corporate innovation compared to inflows from central areas.On the other hand,factors with greater cultural differences provide higher complementary value to enrich the"innovation gene pool",which makes them more capable of promoting local corporate innovation than inflows with lower cultural differences.Based on these findings,this paper proposes policy recommendations to further promote high-quality development in the Yangtze River Delta region,such as fostering broader integration,promoting the sharing of innovation factors,and main-taining diversity in innovation resources.
Yangtze River Deltaregional integrationcorporate innovationfactor inflowbig data
万方数据
