Decision Science Applications and Models (DSAM)

Dear Colleagues,

The theme “Decision Science Applications and Models” aims at providing cutting-edge methodologies, models, and case studies in the area of applied decision science, thus contributing to economic, technological, environmental, and social progress. This theme seeks to explore innovative advancements and practical applications that bridge theory and practice in decision-making methodologies across various domains.

Decision Science is an interdisciplinary field that merges principles from mathematics, statistics, computer science, artificial intelligence, economics, and behavioral science to enhance decision-making processes. The topics of interest include, but are not limited to, the following ones:

• Decision-making methodologies in the digital era: Exploring novel methodologies and frameworks for effective decision-making using technological advancements.
• Mathematical models for complex decision problems: Developing and applying mathematical models to address multifaceted decision challenges across diverse domains.
• Machine learning applications in decision science: Utilizing machine learning techniques to extract insights and optimize decision-making processes.
• Data analytics and statistics for informed decision-making: Exploring the use of data analytics and statistical methods to support informed and robust decision-making.
• AI-driven decision-making advancements: Investigating the role of artificial intelligence in shaping decision strategies and outcomes.
• Economical and behavioral aspects in decision science: Understanding customers’ behavior and biases to improve decision-making models and strategies.

We welcome original research articles, reviews, case studies, and methodological papers that provide innovative applications, theoretical advancements, and practical implementations in the field of decision science. Submissions should contribute to the thematic focus of this theme and present new insights or methodologies. We also welcome original and high-quality full papers derived from extended abstracts selected in peer-review international conferences on decision science, such as the 2024 DSA Int. Summer Conference: https://decisionsciencealliance.org/ISC-2024/ 

Prof. Dr. Daniel Riera Terrén
Prof. Dr. Angel A. Juan
Dr. Majsa Ammuriova
Dr. Laura Calvet
Topic Editors