Research on the evaluation and configuration path of China's rural common Prosperity—NCA and fsQCA based on provincial panel data

Abstract

Based on 2013–2019 panel data covering 31 provinces and cities in China, this paper uses the entropy weight technique for order of preference by similarity to ideal solution (TOPSIS) method to measure rural common prosperity (CP). Based on the global and local Moran's I methods, we analyze the dynamic evolutionary characteristics of China's rural CP and the regional differences. Additionally, we use the necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA) methods to explore how six antecedents at the technology-organization-environment (TOE) level interact to affect CP. This research finds that, first, China's rural CP showed a fluctuating upward trend, with the highest level of CP in rural areas in the eastern region, followed by the central and western regions. Additionally, the gap between the three gradually narrowed. Second, China's rural CP had "high-high" and "low-low" agglomeration characteristics, with positive spatial autocorrelation, no transition changes, and strong spatial stability. Third, individual digital economic elements and organizational and environmental elements were not necessary conditions for promoting rural CP. Fourth, the multiple concurrent factors of the digital economy, organizations and the environment constituted three diversified configurations of rural CP, showing that the driving path of rural CP was characterized by "different paths that lead to the same goal”. Moreover, "perfect digital facilities" and "high entrepreneurial activity" had a universal role in promoting rural CP. The conclusions of this research hold important theoretical and practical significance for improving China's rural CP.