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Research on the Empirical Measurement, Spatiotemporal Distribution, and Convergence of the Development Level of Digital New Quality Productive Forces in China |
Fan Linjie1, He Juntao1, Zhang Qian2 |
1.School of Public Affairs, Zhejiang University, Hangzhou 310058, China 2.College of Wealth Management, Ningbo University of Finance and Economics, Ningbo 315175, China |
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Abstract The theory of new and high-quality productive forces is a profound summary of the laws of human social development, and also represents the evolution of Marxist productive forces theory in the context of China’s practice. Digital new and high-quality productive forces are an advanced form of production nurtured in the era of the digital economy. It is of great significance to explore the dynamic evolution, spatial differences, and convergence characteristics of new and high-quality productive forces in China’s cities from the spatio-temporal dimension for a better understanding. The existing research on digital new and high-quality productive forces mainly focuses on aspects such as connotation characteristics, generation logic, and effect. There are three aspects that urgently need to be enriched: first, a scientific and comprehensive indicator system has not been constructed to actually measure the development level of digital new and high-quality productive forces; second, few literatures explore the dynamic evolution and spatial difference characteristics of digital new and high-quality productive forces at the urban level from the spatio-temporal dimension, making it difficult to depict the full picture of the development of digital new and high-quality productive forces; third, there is insufficient exploration of the convergence characteristics of digital new and high-quality productive forces, making it difficult to understand the regional differences and sources of digital new and high-quality productive forces in China. To make up for the deficiencies of existing researches, this study focuses on the core proposition of the development of new and high-quality productive forces in China in the era of the digital economy. Based on the panel data of 286 prefecture-level cities across the country from 2011 to 2021, an evaluation system is constructed, which includes 17 indicators in four dimensions: digital laborers, digital objects of labor, digital means of labor, and production relations. By using the entropy weight TOPSIS method, Dagum Gini coefficient decomposition, spatial autocorrelation analysis, and convergence model, this study systematically reveals the spatio-temporal evolution laws and regional difference mechanisms of digital new and high-quality productive forces.This study finds that,first, in terms of temporal evolution, the level of digital new and high-quality productive forces nationwide shows a significant upward trend. The eastern region has always maintained a leading position, forming a gradient pattern of “the east leading-the central region catching up-the west improving-the northeast recovering”. From the perspective of different dimensions, the dimension of means of production has the fastest growth rate, mainly due to the penetration of industrial robots and the leapfrog development of digital infrastructure; the growth rate of the dimension of production relations is relatively lagging, reflecting that there is a certain time lag effect in institutional innovation. Second, the spatial distribution shows a significant characteristic of “dense in the east and sparse in the west”. High-value areas are concentrated in the urban agglomerations of the Yangtze River Delta , the Pearl River Delta , and the Beijing-Tianjin-Hebei region, forming a spatial pattern of “two cores and one belt”. The Dagum Gini coefficient decomposition shows that the overall regional differences in the development level of digital new and high-quality productive forces are narrowing. The differences between regions are the main source of overall spatial differences, and the contribution rate of differences between regions is continuously increasing while the contribution rate of transvariation density is continuously decreasing. The spatial autocorrelation analysis shows that the global Moran’s I index is rising, presenting a significant spatial agglomeration pattern. Locally, there is a pattern of coexistence of “low-low agglomeration” and “low-high agglomeration”, and the urban agglomeration in the Yangtze River Delta shows a significant positive spillover effect. Third, the convergence test finds that there are significant characteristics of σ![]() convergence and conditional β convergence nationwide and in the four major regions. Among them, the western region has the fastest convergence speed, and fiscal support and financial development are the main driving factors; the northeast region presents a unique negative effect of industrial structure, reflecting that the digital transformation of traditional industrial bases faces structural constraints. The spatial Durbin model shows that the knowledge spillover effect is significant in the eastern region, while there is an obvious competition effect in the western region. Based on this, this study puts forward four policy suggestions: promoting the coordinated development of regional digital new and high-quality productive forces, constructing a regional collaborative linkage mechanism, strengthening the spatial benefits of the development of digital new and high-quality productive forces, and developing digital new and high-quality productive forces according to local conditions.
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Received: 16 October 2024
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