Regional Disparities in the Level of Rural Industrial Revitalization in Jiangsu Province
Wei Wang
Huai'an University, Huai’an, China.
Yiyao Chen
*
Hunan Institute of Science and Technology, Hunan, China.
Xiangyang Li
Huai'an University, Huai’an, China.
Xiaoya Zhou
Huai'an University, Huai’an, China.
*Author to whom correspondence should be addressed.
Abstract
Background: Rural industrial revitalization has become a key pathway for agricultural modernization and rural development, particularly in advanced agricultural regions such as Jiangsu Province in China. Existing research emphasizes industrial integration, technological empowerment, and multifunctional agriculture as core drivers of rural transformation.
Aims: This study investigates the spatiotemporal evolution and regional disparities of rural industrial revitalization in Jiangsu Province, aiming to provide empirical evidence for coordinated agricultural policies and balanced rural development in economically advanced agricultural regions.
Study Design: A quantitative longitudinal analysis using panel data.
Place and Duration of Study: Thirteen prefecture-level cities in Jiangsu Province, divided into southern, central, and northern regions, from 2013 to 2024.
Methodology: A three-dimensional evaluation framework was established, covering agricultural competitiveness, green support capacity, and livelihood prosperity. The Entropy‑TOPSIS method was applied to quantify the level of rural industrial revitalization. Dagum Gini coefficient decomposition was used to identify the sources of regional disparities, and kernel density estimation was adopted to trace its dynamic evolutionary characteristics.
Results: (1) The provincial revitalization index increased from 0.2680 to 0.5435 (cumulative +102.80%), with the driving force shifting from policy stimulus to endogenous growth. (2) A persistent “high in the south, low in the north” spatial pattern was observed, but regional gaps narrowed markedly, and northern Jiangsu showed strong late‑development advantages. (3) Among subsystems, agricultural competitiveness grew the fastest, green support capacity maintained the highest overall level, and livelihood prosperity improved steadily. (4) The overall Gini coefficient declined from 0.1682 to 0.0897, with inter‑regional disparity becoming the dominant source. (5) Kernel density estimation revealed a gradual evolution toward high‑level equilibrium without multi‑polar polarization.
Conclusion: The findings offer robust evidence for narrowing the north‑south agricultural development gap and advancing coordinated rural revitalization. Policy implications include strengthening provincial coordination, promoting region‑specific strategies, and enhancing green agriculture, industrial competitiveness, and livelihood security to achieve long‑term balanced growth.
Keywords: Rural Industrial Revitalization, Entropy-TOPSIS method, Dagum Gini coefficient, kernel density estimation, regional disparity, Jiangsu Province