Title: An integrated marketing model based on online consumer behaviour: a system dynamics stability and classification study

Authors: Kan Lu; Mingting Huang

Addresses: School of Management, Jingzhou University, Jingzhou 434020, Hubei, China ' College of Management, Yangtze University College of Arts and Sciences, Jingzhou, 434020, Hubei, China

Abstract: In the complex realm of modern e-commerce, accurately modelling user interests and delivering personalised recommendations are essential for enhancing platform efficiency, user satisfaction, and business value. Traditional recommendation algorithms often struggle with key challenges such as capturing dynamic behavioural changes, effectively integrating multimodal features, and maintaining system stability during inference. To address these limitations, this study proposes the adaptive transformer and stability-enhanced network (ATRMST-Net). ATRMST-Net integrates a transformer-based sequential modelling backbone with a system dynamics-inspired stability control mechanism. A multimodal attention fusion module is designed to effectively aggregate heterogeneous user interaction data, enabling a richer understanding of user preferences. Furthermore, the model incorporates a temporal smoothness regularisation term and a Jacobian response control component to enhance robustness and mitigate the impact of noisy or volatile behaviours. Extensive experiments on multiple real-world e-commerce datasets demonstrate that ATRMST-Net consistently outperforms a range of competitive baselines across standard recommendation metrics. Ablation studies further confirm the individual contributions of each model component. Overall, this work provides a theoretically grounded and practically effective solution for building more stable, interpretable, and accurate recommendation systems in dynamic commercial environments.

Keywords: personalised recommendation; multi-modal behaviour modelling; transformer with stability regularisation.

DOI: 10.1504/IJDSDE.2025.149964

International Journal of Dynamical Systems and Differential Equations, 2025 Vol.14 No.4, pp.344 - 371

Received: 13 May 2025
Accepted: 15 Jul 2025
Published online: 19 Nov 2025 *

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