The Role of Data Visualization Tools in Enhancing Decision-Making Quality During High-Stakes Public Service Operations

Maxwell Nortey ()

International Journal of Innovative Science and Research Technology (IJISRT), 2026, vol. 11, issue 04, 2016-2032

Abstract: High-stakes public service operations such as emergency response coordination, disaster management, healthcare triage, and national security monitoring require rapid, data-driven decision-making under conditions of uncertainty, time pressure, and information overload. This paper presents a novel Adaptive Multi-Modal Visualization Optimization Framework (AMVOF) designed to enhance decision-making quality by dynamically integrating heterogeneous data streams into cognitively efficient visual representations. The framework leverages a hybrid architecture combining Graph Neural Networks (GNNs) for relational data structuring, Temporal Convolutional Networks (TCNs) for real-time trend extraction, and a newly proposed Cognitive Load-Aware Visualization Selection Algorithm (CLVSA) that adaptively selects optimal visualization formats (e.g., heatmaps, network graphs, temporal dashboards) based on operator context and task criticality.

Keywords: Data Visualization Optimization; Decision Intelligence Systems; Cognitive Load-Aware Algorithms; Public Service Operations; Real-Time Analytics. (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:cvr:ijisrt:2026:04:ijisrt26apr1888

DOI: 10.38124/ijisrt/26apr1888

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