A Study on the Regional Heterogeneity of AI Technology-Driven New Productivity Empowering High-Quality Development of China’s Foreign Trade: An Empirical Test Based on Provincial Panel Data

DOI

10.2991/978-94-6463-886-8_5How to use a DOI?

Keywords

New Quality Productive Forces; High-Quality Development of Foreign Trade; AI technology; Machine learning algorithms; Regional Heterogeneity

Abstract

Against the backdrop of the technological revolution reshaping the global trade and economic landscape, China’s foreign trade urgently needs to transition from traditional factor-driven growth to high-quality development. This paper constructs a comprehensive evaluation system for provincial AI Technology-Driven New Quality Productive Forces and high-quality foreign trade development based on the theoretical framework of AI technological innovation and regional heterogeneity. It employs a two-way fixed effects model to conduct empirical tests on panel data from 30 provinces spanning the years 2011–2022. The findings reveal that AI-driven New Quality Productive Forces have a significant positive impact on the high-quality development of foreign trade, exhibiting gradient-based regional heterogeneity. Specifically, this is manifested in the application of technologies such as machine learning algorithms to optimize supply chain scheduling, natural language processing to improve cross-border communication efficiency, and computer vision to accelerate intelligent quality inspection. Among them, the eastern region has achieved efficient empowerment through technological advantages such as machine learning algorithms to optimize supply chains and computer vision to improve quality inspection efficiency. The central region has lagged behind in penetration due to insufficient application of predictive maintenance algorithms in the industrial Internet. The western region has been constrained by shortcomings in digital infrastructure, such as a lack of edge computing nodes, which have hindered the implementation of technology. Among the control variables, R&D intensity contributes the most, government intervention exhibits a divergent effect, and transportation infrastructure faces regional structural mismatches. Based on these findings, a three-dimensional differentiated policy system of “macro-level technological systems, meso-level digital industries, and micro-level enterprise technological innovation” is proposed to provide a path for promoting the development of New Productive Forces through AI technology and driving the coordinated development of quality, efficiency, and sustainability in China’s foreign trade.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Huimin Zhou
AU  - Zhenxia Liu
PY  - 2025
DA  - 2025/11/06
TI  - A Study on the Regional Heterogeneity of AI Technology-Driven New Productivity Empowering High-Quality Development of China’s Foreign Trade: An Empirical Test Based on Provincial Panel Data
BT  - Proceedings of the 5th International Conference on Internet Finance and Digital Economy (ICIFDE 2025)
PB  - Atlantis Press
SP  - 31
EP  - 43
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-886-8_5
DO  - 10.2991/978-94-6463-886-8_5
ID  - Zhou2025
ER  -