MODEL OF DEVELOPING AN ADAPTIVE MANAGEMENT SYSTEM FOR E-COMMERCE ENTERPRISES

Abstract

The article substantiates that effective financial management of enterprises under dynamic market conditions requires a comprehensive adaptive system combining advanced forecasting technologies, automation, integration of business processes, cybersecurity, and personalized pricing. The initial model, which included analytical data processing methods, automated management, cross-functional integration, cybersecurity measures, and adaptation to changing consumer trends, has been improved by introducing more innovative technologies and approaches. It is demonstrated that hybrid forecasting based on LSTM neural networks and ARIMA-GARCH models significantly enhances demand prediction accuracy and reduces the impact of stochastic market fluctuations, which is critical for informed managerial decisions. The introduction of digital twins is argued to significantly enhance management efficiency by allowing strategy testing within a virtual environment, thereby minimizing risks and accelerating adaptation to changes. Additionally, end-to-end streaming analytics ensures instant responses to changes in customer behavior and market conditions, enabling businesses to automate real-time decision-making processes. The level of cybersecurity is greatly strengthened through the integration of AI-based threat analytics, which can detect fraudulent activities and predict potential attacks, thus increasing the overall resilience of information systems. Implementation of dynamic AI-driven pricing with hyper-personalization creates optimal pricing conditions, improving sales conversion rates and customer satisfaction through individualized approaches. Consequently, the enhanced adaptive financial management model demonstrates substantial advantages over the original one, ensuring more accurate forecasting, automated adaptation of business processes, rapid integration of information flows, increased security, and effective pricing. This enables e-commerce enterprises not only to enhance operational efficiency but also to maintain long-term competitiveness in the digital economy.