Dynamic assessment and pathway optimization of agricultural modernization in China under the sustainability framework: An empirical study based on dynamic QCA analysis

Abstract

Accelerating agricultural modernization is vital for achieving sustainable agricultural development and ensuring food security. This paper uses the comprehensive evaluation model to measure the level of agricultural modernization in 30 provinces of China from 2012 to 2022. It inspects analyzes the spatial-temporal characteristics and regional differences through the Moran Index and Dagum Gini coefficient. Lastly, based on the configuration perspective, the dynamic qualitative comparative analysis method (QCA) is used to clarify the multiple improvement paths of China's agricultural modernization. The results indicate the following. First, China's agricultural modernization level is not high but has the potential for rapid growth. Regarding spatial distribution, the eastern region has the highest agricultural modernization level, followed by the central region, while the western region has the lowest level, showing a “high-high-low-low” clustering characteristic. Second, the overall disparity in China's agricultural modernization level is fluctuating and declining, with regional differences being the primary source of the overall disparity. The largest difference is between the eastern and western regions. Within regions, the western region has the largest internal disparity, but this disparity is gradually decreasing, whereas the gap in agricultural modernization level within the eastern region is continuously expanding. Third, the paths to improve China's agricultural modernization consist of multiple antecedent conditions. From the configuration perspective, there are four paths to enhance China's agricultural modernization level. These include the dual-strategy approach of “technology and policy,” the comprehensive tri-strategy model of “technology, market, and policy,” the synergistic enhancement model combining “technology and market,” and the multi-faceted core-driven approach.