Title: Research on the key core technological innovation of Chinese high-tech enterprises: an empirical analysis using Poisson regression and neural network modelling

Authors: Zaiyang Xie; Steven Jean-Louis Thorin; Yancheng Li

Addresses: School of Management, Zhejiang University of Technology, Hangzhou, Zhejiang, China ' School of Management, Zhejiang University of Technology, Hangzhou, Zhejiang, China ' School of Management, Zhejiang University of Technology, Hangzhou, Zhejiang, China

Abstract: In order to assess and forecast innovation performance in key core technologies, this paper utilises data from Chinese high-tech listed companies between 2016 and 2022. A Poisson regression model is applied to empirically analyse the impact of Sino-US technological decoupling, along with the moderating roles of corporate resource slack and a pro-innovation environment. Additionally, to further validate the reliability of the Poisson regression results, a feedforward neural network model is also developed. Upon evaluation, the model achieves high accuracy in predicting the number of innovation patents and effectively captures complex relationships among key variables, demonstrating strong predictive performance. Based on the above conclusions, this paper aims to provide some empirical enlightenment and prediction tools for how to drive the key core technological innovation.

Keywords: Sino-US technological decoupling; key core technology; Poisson regression; feedforward neural network.

DOI: 10.1504/IJWMC.2026.151591

International Journal of Wireless and Mobile Computing, 2026 Vol.30 No.2, pp.180 - 190

Received: 01 May 2025
Accepted: 06 Jul 2025
Published online: 09 Feb 2026 *

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