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The Promotion Effect of Data Factor Allocation Level on Cross-Border E-commerce Development: Evidence from China

In: Proceedings of the 2026 2nd International Conference on Data Mining and Project Management (DMPM 2026)

Author

Listed:
  • Zijing He

    (Guangdong University of Science and Technology)

  • Wenjie Yao

    (Guangdong Ocean University)

  • Shizhu Dong

    (Guangdong University of Science and Technology)

Abstract

This study examines how data factor allocation promotes cross-border e-commerce development in China. Based on provincial panel data (2012–2022), we employ a two-way fixed effects model to analyze this relationship. Results show that enhancing data factor allocation significantly boosts cross-border e-commerce, a finding robust to alternative measures, lagged variables, and winsorization. The promotion operates through two indirect channels: industrial structure upgrading and increased R&D intensity. Heterogeneity analyses reveal stronger effects in regions with higher data allocation levels and a regional gradient (Eastern > Western > Northeastern > Central). The findings underscore data factors as a key driver for high-quality e-commerce growth and offer targeted policy implications.

Suggested Citation

  • Zijing He & Wenjie Yao & Shizhu Dong, 2026. "The Promotion Effect of Data Factor Allocation Level on Cross-Border E-commerce Development: Evidence from China," Advances in Economics, Business and Management Research, in: Ljiljana Trajkovic & José Alfredo F. Costa & Zaher Al Aghbari & Nor Azman Ismail & Dariusz Jacek Jak (ed.), Proceedings of the 2026 2nd International Conference on Data Mining and Project Management (DMPM 2026), pages 115-126, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6239-689-0_11
    DOI: 10.2991/978-94-6239-689-0_11
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