Characteristics and Influencing Factors of Provincial High-End Manufacturing Innovation Clusters in China: A Big Data Analysis of Technology-Based Enterprises

Previous research on industrial agglomeration has been limited by administrative boundaries, leading to biased results. This paper uses the Duranton and Overman Index to assess high-end manufacturing agglomeration and analyses the influencing factors at various distances. This method surpasses traditional administrative limitations by using continuous geographical distance, providing a more accurate reflection of industrial agglomeration patterns. High-end manufacturing industries show spatial clustering with significant provincial differences, exhibiting patterns of ‘interlaced size’ and ‘small and wide’ agglomeration over 0-300 km, and ‘large and narrow’ within 50 km. Electrical machinery and automotive industries display mixed patterns, while others like computer electronics and railway equipment show varied distance agglomeration. The role of influencing factors on industrial agglomeration has a scaling effect. The relevance of agglomeration economies to industry clustering increases gradually with distance. In contrast, the influence of innovation resources is greater in proximity.