Applied Mathematics and Nonlinear Sciences (Jan 2024)

Risk prediction and control of strategic operation of e-commerce enterprises based on economic management science

  • Hong Qingyu,
  • Luo Lei,
  • Zhang Yanting

DOI
https://doi.org/10.2478/amns-2024-0763
Journal volume & issue
Vol. 9, no. 1

Abstract

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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.

Keywords