Risk prediction and control of strategic operation of e-commerce enterprises based on economic management science
Published Online: Apr 01, 2024
Received: Jan 31, 2024
Accepted: Feb 08, 2024
DOI: https://doi.org/10.2478/amns-2024-0763
Keywords
© 2024 Qingyu Hong et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
The burgeoning realm of Internet technology has ushered e-commerce into a pivotal economic role. However, navigating the myriad risks inherent in e-commerce operations is vital for the sustained growth of businesses in this sector. This study melds economic management principles with a deep dive into e-commerce risk management, focusing on predictive strategies and mitigation measures. We commence by dissecting the principal risk categories within e-commerce operations. Subsequently, we employ Structural Equation Modeling (SEM) and Particle Swarm Optimization-Generalized Regression Neural Network (PSO-GRNN) for quantitatively dissection of these risk factors. Our findings pinpoint internal, technological, and operational management risks as the critical triad influencing e-commerce strategic operations. Remarkably, the PSO-GRNN model’s risk prediction accuracy stands at 93.62%, outstripping conventional models significantly. Through this research, we offer a robust framework for e-commerce entities to enhance their strategic foresight and resilience, aiding in optimizing their strategic maneuvers.