The dynamic evolution of agricultural trade network structures and its influencing factors: evidence from global soybean trade

Under the rapid advancements in information technology, the complex network characteristics of agricultural product trade relationships among global economies have exhibited increasing prominence. This study takes the soybean trade market as an empirical case, employing a combination of social network analysis to investigate the dynamic evolution of agricultural trade network structures; then, the Temporal Exponential Random Graph Model (TERGM) is adopted to analyse the factors influencing the soybean trade network. Based on comprehensive empirical data encompassing soybean trade data among 126 economies from 2000 to 2022, this research demonstrates several key findings: Firstly, the soybean trade network is characterised by pronounced trade agglomeration effects and “small-world” properties, accompanied by heightened trade substitutability. Secondly, the network’s structural configuration has undergone a distinct transformation, shifting from a traditional single-core–periphery structure to a more complex multi-core–periphery architecture. Thirdly, in response to external shocks impacting network topology, the core structure exhibits greater resilience and stability, whereas the periphery displays heterogeneous responses. Finally, the evolution of soybean trade relations is governed by a dual mechanism involving both endogenous dynamics and exogenous influences.