INFORMATION IN SYSTEMS DECISION ACCEPTANCE TO DO MODELS APPLICATION AND THEIR CONSEQUENCES EVALUATION IMPROVED STRATEGY.
Keywords:
Decision-making models, Analytical Hierarchy Process (AHP), TOPSIS, hierarchical structures, multi-criteria optimization, dynamic weight models, information systems, uncertainty, fuzzy logic, real-time decision-making.Abstract
This study explores the application of advanced decision-making models in information systems, focusing on enhancing efficiency under multi-criteria and uncertain conditions. The research examines methods like the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for determining hierarchical structures and assessing
alternatives based on their proximity to ideal solutions. By integrating these models, the study demonstrates their effectiveness in addressing complex decision-making processes, emphasizing improved accuracy and consistency. Additionally, dynamic,
static, and linear weight models are analyzed to compare their adaptability to realtime data. The findings highlight the superiority of dynamic models in reflecting environmental changes, while also discussing the limitations of static and linear models in dynamic systems. Future research directions include integrating fuzzy logic and probabilistic approaches for further enhancement.
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