Towards Sustainable Development: Spatial Correlation Network Research on Food Security

ABSTRACT Identifying the spatial correlation and driving factors of food security between countries or regions has become an important aspect to promote sustainable development. This paper takes China, a major food trading nation, as a research sample, utilizing provincial panel data from 2001 to 2020. It employs methods such as entropy weighting, radar chart area model calculation method, modified gravity model, social network analysis (SNA), and quadratic assignment procedure (QAP) to identify and examine the spatial correlation structure and driving factors of food security in China. The main research conclusions are as follows. First, regional food security does not exist in isolation. Spatial linkages between regions have gradually strengthened. The spatial correlation network shows a relatively high network density (network density > 0.2). Second, core nodes exist in the food security spatial correlation network (degree centrality > 30). A clear “core–periphery” structure has formed. At the same time, four distinct clustering blocks emerge in the food security spatial correlation network based on differences in input and output relationships. These blocks are main benefit, net benefit, broker and net overflow. Third, the spatial correlation network of food security is a complex structure shaped by both endogenous capability factors and exogenous conditional factors. The research conclusions not only deepen the understanding of China's spatial correlation network of food security, but also provide an important case reference for identifying key elements in the global food security network, optimizing regional collaborative governance, and preventing systemic risks.