LAUSR

This paper introduces a novel spatial angle index method for evaluating industrial spatial structure upgrading, drawing on a review and critique of existing approaches, including the traditional proportional method, industrial structure hierarchy coefficient, the production efficiency method and the cosine angle method. The proposed method integrates both local and projected spatial angle indices, accounting for the actual industry proportions of specific regions and assessing the deviation of these indices from extreme states. This approach effectively captures spatial spillover effects between regions and the combined influence of local and projected points on industrial spatial structure upgrading. Utilizing firm survival big data from 96 sub-industries across 284 cities in China from 1978 to 2022, the paper evaluates the upgrading levels of industrial spatial structure in these cities and examines their spatiotemporal evolution patterns using kernel density estimation. The study reveals that although different spatial weight matrices (commuting distance, latitude–longitude distance, and commuting time) produce slightly different results, the differences are not substantial. Notably, the analysis shows that the tertiary sector consistently demonstrates superior upgrading levels, while the secondary sector has underperformed, particularly since 1992. The primary sector, however, has experienced significant improvements, at times even surpassing the tertiary sector. The findings further suggest that while significant changes in industrial spatial structure upgrading occurred before 1987, the pace of change has stabilized since 1988.