Large Group Decision Making: Creating Decision Support Approaches at

In this review of Large Group Decision Making: Creating Decision Support Approaches at Scale, the book is recommended for researchers and practitioners who need a comprehensive, research-grounded guide to coordinating decisions across many participants. The single biggest reason to buy is its clear synthesis of techniques bridging traditional decision support with modern disciplines like Data Science and Opinion Dynamics, which makes it a practical reference for designing systems that operate at scale.

Key Features

• Comprehensive scope: Covers consensus support, fusion and weighting of decision information, and subgroup clustering to address the full workflow of large-group decisions.
• Interdisciplinary links: Connects Large-Group Decision Making to Artificial Intelligence, Social Network Analysis and behavioral sciences to inform system design.
• Practical orientation: Discusses implementation of decision support systems and behavior management so readers can translate concepts into real-world tools.
• Research and applications: Highlights real-world applications and future research directions to help readers plan projects and experiments.
• Problem-driven analysis: Starts from challenges in classical approaches and proposes principles and families of techniques tailored for large decision groups.

Who It's For

This brief is aimed at computer scientists, data scientists, and systems designers working on group decision problems who need a single reference that brings together relevant methods from Computer Science and the behavioral sciences. It is also useful for graduate students and academics who want a concise overview of current trends and future research directions.

Those who should look elsewhere include casual readers without a technical background and managers seeking step-by-step commercial project plans; the text is research-oriented and best used by readers comfortable with technical and theoretical discussions.

Pros & Cons

Pros

• Provides a focused synthesis of techniques for large-group decision making that is hard to find in one place.
• Bridges multiple disciplines, offering practical insight for system implementation and research planning.
• Includes discussion of real-world applications, which helps contextualize methods for practitioners.

Cons

• Its research-oriented presentation may be dense for readers without technical or academic background.

Specifications

Title	Large Group Decision Making: Creating Decision Support Approaches at Scale
Series	SpringerBriefs in Computer Science
Author	Ivan Palomares Carrascosa
Primary topics	Consensus support, fusion and weighting, subgroup clustering, behavior management
Related disciplines	Data Science, Artificial Intelligence, Social Network Analysis, Behavioral Sciences
Includes	Real-world applications and future research directions

Our Verdict

Overall, this brief is a compact, valuable reference for researchers and practitioners tackling decision support at scale; its interdisciplinary framing and focus on implementation make it good value for those building or studying large-group decision systems.

Frequently Asked Questions

Is this book practical for system implementation?
Yes. It discusses implementation of decision support systems and behavior management alongside theoretical principles to help bridge research and practice.

Who authored the book?
The brief is authored by Ivan Palomares Carrascosa and published in the SpringerBriefs in Computer Science series.

Does it cover modern techniques?
Yes. It explicitly links Large-Group Decision Making to Data Science, Artificial Intelligence, and Social Network Analysis.