Journal of Decision Intelligence and Analytics (DINA) is an international, peer-reviewed, open-access journal devoted to advancing the science, methods, technologies, and applications of intelligent and analytics-driven decision-making. The journal provides an interdisciplinary forum for research on how data, analytical models, artificial intelligence, computational methods, and human expertise can be integrated to understand decision problems, generate decision intelligence, evaluate alternatives, and support effective action.
The central focus of Journal of Decision Intelligence and Analytics (DINA) is the transformation of data into intelligence, intelligence into decisions, and decisions into action. The journal therefore welcomes research that goes beyond the analysis of data alone and contributes to the design, improvement, explanation, automation, or evaluation of decision processes. Particular attention is given to approaches capable of supporting decisions in complex, uncertain, dynamic, multi-objective, and data-rich environments.
DINA brings together perspectives from decision sciences, artificial intelligence, data science, business analytics, operations research, optimization, computational intelligence, information systems, and related disciplines. The journal encourages research that connects predictive knowledge with prescriptive reasoning and decision consequences, including approaches that combine machine intelligence with human judgment, domain knowledge, preferences, constraints, uncertainty, and organizational objectives.
The journal welcomes theoretical, methodological, computational, empirical, and application-oriented contributions. Research should demonstrate scientific originality and methodological rigor and, where applicable, provide transparent and reproducible evidence of computational or empirical validity. Application-oriented studies should offer insights that extend beyond a single implementation or case and contribute to the broader understanding of intelligent decision-making and analytics.
The scope of the journal includes, but is not limited to, the following areas:
The journal also welcomes decision intelligence and analytics applications across a broad range of domains, including:
Journal of Decision Intelligence and Analytics (DINA) particularly encourages contributions that connect multiple stages of the decision lifecycle: identifying and structuring a decision problem, acquiring and interpreting relevant data, generating intelligence, modeling uncertainty and preferences, developing and evaluating alternatives, recommending or selecting actions, and learning from decision outcomes. Research integrating several of these stages is especially relevant to the journal's mission.
The journal is particularly interested in work that advances the relationship between human intelligence and machine intelligence. This includes research on how artificial intelligence can augment rather than merely automate decision-making; how explanations, uncertainty, preferences, values, and domain knowledge can be incorporated into analytical systems; and how decision-makers can interact effectively with intelligent models, algorithms, and autonomous agents.
DINA also recognizes that technically accurate predictions do not necessarily lead to effective decisions. The journal therefore encourages research that explicitly connects predictive performance with decision objectives, constraints, trade-offs, interventions, consequences, and measurable outcomes. Studies addressing the transition from prediction to prescription and from analytical insight to actionable decision intelligence are particularly welcome.
Methodological contributions may introduce new theories, models, algorithms, frameworks, architectures, analytical procedures, or computational approaches. Empirical and application-oriented contributions should demonstrate how decision intelligence or analytics produces meaningful insight into the formulation, evaluation, implementation, or improvement of decisions. Comparative and benchmarking studies are welcome when they provide substantive methodological or decision-relevant conclusions rather than comparisons based solely on performance metrics.
The journal welcomes original research articles, review articles, systematic and bibliometric reviews, methodological papers, computational studies, empirical investigations, comparative studies, case studies, and application-oriented contributions consistent with its aims and scope.
Journal of Decision Intelligence and Analytics (DINA) aims to contribute to a deeper scientific understanding of how decisions can be made more intelligently in an increasingly complex and data-intensive world. By connecting data, intelligence, decisions, and action, the journal seeks to advance methods and systems that are not only analytically powerful, but also explainable, robust, responsible, reproducible, and relevant to real-world decision-making.
