从“规模扩张”转向“质量提升”，跨境电商步入关键一跃｜“十五五”产业前瞻
Di Yi Cai Jing·2026-01-23 11:26

Core Insights - The introduction of the "14th Five-Year Plan" marks a transition for China's cross-border e-commerce from a focus on scale expansion driven by traffic dividends to an emphasis on quality improvement and compliance [1] - The plan aims to expand high-level opening up, promote trade innovation, and support the development of new business models like cross-border e-commerce [1] Group 1: Industry Growth and Trends - By 2025, China's cross-border e-commerce imports and exports are projected to reach 2.75 trillion yuan, representing a 69.7% increase from 2020 [1] - Cross-border e-commerce is playing a significant role in driving new growth in foreign trade, promoting domestic industrial upgrades, and balancing regional economies [1] - Platforms like Temu and Alibaba International Station are rapidly expanding overseas, with Temu achieving significant market scale in most countries within three years [2] Group 2: Challenges and Strategic Shifts - The cross-border e-commerce industry faces multiple challenges, including increased policy risks in markets like the US and EU, rising compliance costs, and issues of fragmentation and intense competition [4] - The industry is encouraged to shift from passive compliance to proactive strategies, including establishing sound financial and tax systems and enhancing management efficiency [4] - The focus is on cultivating cross-border e-commerce talent, digital transformation for merchants, and improving the ecological service systems of platforms [4] Group 3: Future Opportunities - The transition in cross-border e-commerce is seen as an opportunity for brand upgrades, moving away from low-price competition to high-value brand exports [5] - The optimization of domestic supply chains through mergers, restructuring, or digital upgrades is expected to enhance international supply chain control [5] - The industry is anticipated to evolve from "traffic operation" to "data empowerment," leveraging platform data for market analysis and product design [5]