Global agricultural trade network characteristics and its influencing factors - Junwen Cao; Qingya Lei (Humanities & Social Sciences Communications)
Abstract This study investigates the evolutionary process of the global agricultural trade network and identifies key influencing factors. Utilizing social network analysis, a trade network model was constructed based on international trade data for six categories of agricultural products from 2013 to 2022. Comparative analyses were conducted from three perspectives: individual node characteristics, network pattern evolution and network community structure. Additionally, an Exponential Random Graph Model was employed to discern the critical determinants of agricultural trade networks. The study also discussed the differentiated performances observed in regions with varying levels of development. The findings indicate that: (1) In terms of individual node characteristics, core countries in agricultural trade are relatively stable, predominantly located in European, American, and a few Asian countries, with an expanding gap among nations. (2) Regarding network topology, all agricultural product trade networks exhibit small-world properties, with distinct geographical characteristics in major communities. (3) As for the influencing factors of the trade network, reciprocity, geographical proximity, cultural differences, and trade agreements significantly enhance trade connections across various agricultural products. The similarity effect of GDP per capita exerts a negative impact on agricultural trade, except for textile raw materials. Agricultural endowment and governance efficiency play a significant role in a country’s agricultural exports.