Original scientific paper

https://doi.org/10.17559/TV-20240913001988

Prediction of Cities' Digital International Trade Competitiveness based on Neural Network

Xinyu Zhang ; Department of Logis-tics and Management Engineering, Yunnan University of Finance and Economics, China
Penghui Luo ; Department of Logis-tics and Management Engineering, Yunnan University of Finance and Economics, China *

* Corresponding author.

Abstract

This paper adopts K-means neural network to analyze and study the direction, path and scope of influence of digitalization on the international competitiveness of 298 cities. The study shows that the degree of digitalization is positively correlated with the city's trade competitiveness. The breadth of digital development as a mediating variable will inhibit the promotion of digitized degree for the city's trade competitiveness. When the degree of financial development and the productive efficiency of the product are added as regulated variable, the inhibitory effect of the breadth of digital development on promoting competitiveness for digitized degree can be partially offset; and the digitized degree itself will weaken its positive promotion effect with the city's international trade competitiveness if it is overdeveloped. The study theoretically adopts K-means neural network to predict the impact mechanism of the digital economy on the city's international trade, and in practical application, it helps the city to formulate the future development planning direction and focus.

Keywords

city's trade competitiveness; digital depth; digital international trade; K-means neural network

Hrčak ID:

330525

URI

https://hrcak.srce.hr/330525

Publication date:

1.5.2025.

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