Measurement and spatio-temporal evolution of high-quality industrial development level in China - XinMei Yang; RuiHui Zhou (Scientific Reports)
Abstract The scientific measurement of high-quality industries development (Abbreviated as HQID) level is crucial for promoting their advancement in China. This measurement holds significant importance in reducing regional differences in HQID among cities and fostering coordinated urban industry development. This study utilizes panel data encompassing 286 cities in China from 2003 to 2022. It comprehensively examines the essence of HQID, focusing on factor output efficiency and the industrialization process. To achieve this, an evaluation index system encompassing seven key aspects is constructed: technological innovation intensity, factor productivity, resource utilization intensity, pollution emission intensity, open competition intensity, industrialization level, and industrialization quality. Subsequently, the HQID level of China is measured, and the spatial–temporal evolution characteristics are revealed through various methods, including spatial correlation analysis, hot spot analysis, and Dagum Gini coefficient decomposition. The findings indicate the following: (1) China’s urban industry is experiencing slow but steady improvement in its overall high-quality development level. The number of regions with medium and high levels has notably increased. Furthermore, the spatial distribution is predominantly concentrated in the Eastern coastal areas. (2) The spatial distribution of HQID index in Chinese cities reveals positive correlation between the H–H type spatial agglomeration pattern and the L–L type spatial agglomeration pattern. (3) The highest level of HQID and the most pronounced growth trend are observed in Eastern coast and Northern coastal. Since 2018, the trend of HQID in the northeast and northwest areas has shown a decline. From 2003 to 2022 inter-regional differences were primary source of overall regional disparities, with significant variation in the contribution rates among the three factors.