KEY INFLUENCING FACTORS AND TREND PREDICTION OF SHANDONG’S FOREIGN TRADE NEW PRODUCTIVITY DRIVEN BY DIGITAL TRADE

Résumé fourni par la source

Taking the development of foreign trade new productivity driven by digital trade as the main line, this study constructs a multi-dimensional evaluation system based on the panel data of 16 prefecture-level cities in Shandong Province from 2018 to 2023. The entropy weight method is adopted to calculate the comprehensive index of foreign trade new productivity. A random forest model is introduced to identify key influencing factors and quantify their contribution rates. The results show that cross-border e-commerce penetration, digital talent density, and data element circulation efficiency are the core driving factors, with a cumulative contribution rate of 82.3%, highlighting the critical supporting role of digital elements and talents. Furthermore, a ridge regression model is constructed to eliminate multicollinearity. The fitting results are robust with a coefficient of determination of 0.909. The trend prediction indicates that under the current development trend, the comprehensive index of Shandong’s foreign trade new productivity will increase by 19.7% compared with the baseline period, and the regional gap will show a converging trend. The research findings provide quantitative evidence and decision-making reference for formulating differentiated foreign trade upgrading policies and optimizing the digital trade ecosystem.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.