Integration into the industrial chain and enterprise innovation : a novel approach of industrial chain measurement using firm data

"The deep integration of the innovation chain, industry chain, capital chain, and talent chain" is a major national strategy at present, and how to achieve deep integration among these different chains has important theoretical and practical value. However, empirical frameworks and measurement methods for quantitatively analyzing the industrial chain are still lacking. Building on the approach of Acemoglu et al . (2012), this study uses artificial intelligence to gather related transaction and equity investment data from AiQiCha, ShangShangCha, regional tendering and bidding public service platforms, and the annual reports of listed enterprises, and then employs a depth-first search algorithm to analyze the industrial chain positions of enterprises. On this basis, combining data from input-output tables and the theory of directed graphs, this study calculates the industrial chain linkage, and further integrates the industrial chain centroid degree to measure the degree of industrial chain integration. The empirical results demonstrate that enterprises' integration into the industrial chain significantly improves their innovation performance via knowledge spillover and scale effects, and this improvement exhibits significant heterogeneity due to enterprise characteristics. Our analytical process and measurement results offer a relatively scientific quantitative analysis model to construct a modern industrial system and advance industrial chain development.