Unraveling the complexity of the global biodiesel trade network: Topological structure and multidimensional drivers

As a key enabler of the low-carbon transition in transportation, global biodiesel trade has expanded rapidly in recent years. However, existing literature has not systematically unraveled the evolutionary patterns and driving mechanisms of global biodiesel trade. To fill this gap, this study aims to construct global biodiesel trade networks (GBTNs) for the period 2012–2022, systematically analyze the evolutionary characteristics of biodiesel trade from a complex network perspective, and explore its multidimensional driving mechanisms using the temporal exponential random graph model (TERGM). The results show: (1) GBTNs display small-world, reciprocal, and disassortative characteristics, with clustering and bilateral reciprocity as dominant trade patterns. (2) GBTNs exhibit a polarized “silent majority—active minority” structure. The Netherlands serves as a superhub within GBTNs, while the majority of countries are on the periphery of the network. (3) The evolution of GBTNs is jointly shaped by endogenous and exogenous mechanisms. Reciprocity is a key endogenous driver (odds ratio = 2.76), while economic development shows a major exogenous effect (exporter PGDP: odds ratio = 1.218; importer PGDP: odds ratio = 1.138). Technological innovation, climate risk, geographic distance, trade policies, and cultural proximity also play significant roles. (4) Heterogeneity analysis reveals that the maintenance of trade relations relies more on endogenous mechanisms. Compared to developed countries, developing countries are more sensitive to trade policies and cultural proximity. This study contributes to a better understanding of the evolution of global biodiesel trade and provides valuable insights for more targeted trade policies.