Research on the interaction between energy consumption pattern transformation and international trade in the digital economy era based on gig data analysis

With the rapid development of the digital economy, energy consumption patterns are transforming. However, problems remain, such as low energy efficiency and heavy dependence on traditional energy. By addressing data privacy compliance, enhancing model generalization, expanding to practical cases like the BRI, integrating system dynamics concepts, grounding machine learning techniques in theory, linking numerical results to theory, and highlighting research novelty through comparisons, we have provided a robust and insightful analysis. With the development of the digital economy, the transformation of energy consumption patterns is accelerating. In terms of improving energy consumption efficiency, energy consumption per unit of GDP decreased by 0.74%. Technological innovation and the widespread application of digital tools have significantly improved energy efficiency. In international trade, the proportion of exports of high energy-consuming products decreased from 44.7 to 35.67%. In comparison, the proportion of exports of new energy technology products increased from 35.8 to 40.0%. The trade volume of high-tech products accounted for 91.0%, showing that international trade is gradually transforming in a green, low-carbon, and high-value-added direction.