The Journal of Data Analytics and Intelligent Decision-Making (JDAID) is dedicated to advancing cutting-edge research at the intersection of data science, artificial intelligence, and decision-making processes. The journal aims to provide a platform for high-quality, original research that explores innovative theories, methodologies, and applications that enhance intelligent and data-driven decision-making. JDAID seeks to promote the development of intelligent systems that improve decision quality and outcomes across diverse sectors. By fostering collaboration among academics, industry professionals, and policymakers, the journal facilitates the exchange of knowledge, methodologies, and best practices that drive the evolution of data analytics and intelligent decision-making. By publishing innovative research and practical case studies, JDAID aims to bridge the gap between theory and real-world applications, driving the next generation of intelligent decision-making solutions. The journal covers a broad range of topics, including but not limited to:

1. Data Analytics and Decision Science (Statistics, Machine Learning, Predictive Modeling, Time Series Analysis, Data Mining and Visualization, Decision Analysis and Optimization, Forecasting, Data Envelopment Analysis and Performance Evaluation, Mathematical Modeling and Simulation)

2. Applications of Data Analytics and Intelligent Decision-Making across various fields such as Healthcare, Economics and Finance, Manufacturing and Operations, Logistics, and Services

3. Big Data Analytics and Big Data–Driven Technologies in Decision-Making

4. Artificial Intelligence in Decision-Making (AI-based Decision Support Systems, Reinforcement Learning, Natural Language Processing, Intelligent Automation, and Robotics)

5. Behavioral and Cognitive Sciences in Intelligent Decision-Making (Human-Computer Interaction, Cognitive Biases, Behavioral Economics, Behavioral Finance, Leadership Neuroscience, Marketing Neuroscience, Strategic Neuroscience, and Bio-inspired Decision Models)

6. Business Intelligence, Strategic Intelligence, Competitive Intelligence, and Strategic Decision-Making (Market Analysis, Customer Segmentation, Performance Optimization, and Risk Analysis)

7. Artificial Intelligence and Modeling in Decision-Making and Problem Solving (Predictive Models, Simulation, Optimization, and Prescriptive Methods)

8. Healthcare and Biomedical Decision Support (Disease Diagnosis, Clinical Decision Support, Personalized Medicine, and Medical Image Analysis)

9. Financial and Economic Analytics (Portfolio Management, Economic Forecasting, Fraud Detection, and AI-Driven Investment Strategies)

10. Data-Driven Governance and Policy-Making: Data Management in Government, Smart Cities, Cybersecurity, and AI Ethics

11. Decision Support Systems and Autonomous Systems: DSS, Multi-Agent Architectures, and Autonomous Systems

12. Ethics, Governance, and Accountability in Intelligent Decision-Making: Transparency, Fairness, Bias Mitigation, and Legal Frameworks

13. Interdisciplinary Approaches: Integration of Cognitive Science, Psychology, Neuroscience, and Artificial Intelligence in Decision-Making