Dynamic evolution of the global copper trade dependency network structure and influence mechanism in the context of energy transition: An industrial chain perspective

As a critical metal for the development of renewable energy fields, copper plays an irreplaceable role in energy transition, and its stable and sustainable supply is vital for clean energy development. Studying copper trade dependence networks helps identify potential resource supply bottlenecks, offering valuable insights for sustainable energy supply and global partnerships. This study, from an industry chain perspective, constructs global copper trade dependency networks (GCTDNs) from 2010 to 2022 based on trade dependence relationships. Using complex network analysis and temporal exponential random graph models (TERGM), it explores the spatiotemporal evolution and dynamic mechanisms of GCTDNs. The results show: (1) The GCTDNs of the entire industry chain are becoming increasingly complex, showing obvious reciprocity, transitivity, and degree centrality. (2) At the 1 % significance level, network reciprocity structure drives trade dependency across the chain, while the triangle structure mainly promotes upstream copper ore and concentrate trade, and the star structure negatively inhibits dependency formation throughout the industry chain. (3) Temporal stability and delayed reciprocity both play a positive role. (4) Renewable energy technologies promote upstream and downstream copper exports, while smelting technology advancements boost midstream imports. (5) At the 1 % significance level, upstream trade is affected by the midstream and downstream to 0.9657 and 0.1828, respectively. Midstream trade shows a smaller gap in influence from upstream and downstream, differing by 0.1, while downstream trade is primarily influenced by midstream with a coefficient of 0.9871. These findings provide strong support for supply chain optimization, renewable energy technology promotion, and sustainable development goals.