About the Journal

Applied Decision Analytics is an international, peer-reviewed journal that serves as a platform for advancing decision sciences at the intersection of data science, artificial intelligence, and applied mathematics. The journal seeks to publish cutting-edge research that not only develops novel decision methodologies but also demonstrates their effectiveness in solving complex, high-impact real-world problems.

The primary aims of the journal are to:

• Provide a forum for theory-driven and data-driven decision analytics, emphasizing the integration of mathematical models with modern data science techniques.

• Advance the next generation of decision support systems that combine big data analytics, machine learning, optimization, and simulation for actionable insights.

• Encourage research that addresses uncertainty, vagueness, and dynamic complexity through approaches such as fuzzy sets, probabilistic reasoning, rough sets, and hybrid soft computing.

• Promote cross-disciplinary collaboration among operations research, computer science, statistics, management, engineering, and social sciences.

• Highlight the societal and managerial impact of decision analytics in areas such as healthcare, energy, sustainability, climate change, supply chain resilience, smart cities, and digital transformation.

The scope of Applied Decision Analytics covers both methodological advances and application-driven studies. Contributions may include but are not limited to:

• Decision Models and Frameworks: Multi-criteria decision-making (MCDM), multi-objective optimization, Bayesian decision theory, stochastic and dynamic programming, and game-theoretic models.

• Data Science in Decision Analytics: Integration of machine learning, deep learning, natural language processing, and network analysis for decision support and predictive analytics.

• Uncertainty and Risk: Modeling imprecision, ambiguity, and incomplete information through fuzzy systems, intuitionistic fuzzy sets, probabilistic graphical models, and scenario analysis.

• Human-Centered and Cognitive Decision Analytics: Behavioral decision-making, explainable AI in decision processes, and human–machine collaboration in analytics.

• Applications: Real-world decision problems in healthcare systems, energy management, finance and banking, logistics and transportation, environmental management, policy analysis, digital epidemiology, and Industry 4.0.

• Unique Contributions:

  • Combining algorithmic advances in data science with decision theory to move beyond descriptive analytics toward prescriptive and cognitive analytics.

  • Bridging the gap between predictive machine learning models and decision optimization frameworks.

  • Demonstrating scalability of decision analytics in big data and real-time environments, with emphasis on computational efficiency and interpretability.

What makes Applied Decision Analytics unique is its commitment to showcasing research that not only advances methodology but also provides demonstrable practical value through case studies, decision-support tools, and data-driven applications. The journal positions itself at the frontier of decision intelligence, where data science meets decision theory to inform complex choices under uncertainty.

General Journal guidelines for authors

Applied Decision Analytics publishes research articles, reviews, short communications, and case studies. Research articles must include: motivation for the work, an adequate overview of the representative work in the field including up-to-date references, a clear statement of the novelty in the presented research, suitable theoretical background, one or more examples to demonstrate and discuss the presented ideas and, finally, conclusions. Short communications are usually 4-7 pages long, research articles and case studies 8-14 pages, while reviews can be longer. Page number limits are not strict and, with appropriate reasoning, the submitted articles can also be longer or shorter. Authors are requested to follow the ADA guidelines and strictly format their manuscripts as per the article template that is available here.

If extensions of previously published conference papers are submitted, Editors will check if sufficient new material has been added to fulfill the journal standards and qualify the submission for the review process. The added material must not have been previously published. New results are desired but not necessarily required; however, the submission should contain expansions of key ideas, examples, elaborations, etc., of the conference submission.

ADA’s acceptance rate is 24%. In 2025, the median time from submission to acceptance for all articles was 67 days, and 12 days from acceptance to online publication in the ONLINE FIRST section. The ONLINE FIRST section of ADA lists the papers accepted for publication and copy-edited but not yet assigned to an issue.

Aims and Scope: The principal aim of the journal is to bring together the latest research and development in various fields of decision science. We would like to highlight that papers should refer to Aims and scope, but they are not limited to.

Publication Frequency: One issue per year is published online, but processed and accepted papers, with full bibliographic data, are added to the issue continuously over the whole year.

Open Access: This is an open-access journal which means that all content is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles in this journal without asking prior permission from the publisher or the author.

Publication fee: There is no submission charge or publication fee. Publication in ADA is free of charge for the authors.

The Applied Decision Analytics is annually classified by the Ministry of Education, Science and Technological Development of the Republic of Serbia.