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

Zijing He (), Wenjie Yao () and Shizhu Dong ()
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Zijing He: Guangdong University of Science and Technology
Wenjie Yao: Guangdong Ocean University
Shizhu Dong: Guangdong University of Science and Technology

A chapter in Proceedings of the 2026 2nd International Conference on Data Mining and Project Management (DMPM 2026), 2026, pp 115-126 from Springer

Abstract: 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.

Keywords: Data Factor Allocation; Cross-Border E-Commerce Development; Industrial Structure Upgrading; R&D Intensity; Fixed Effects Model (search for similar items in EconPapers)
Date: 2026
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DOI: 10.2991/978-94-6239-689-0_11

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