1.1 Motivation

Decision making processes take place just anywhere around us, with our own daily life situations being of course no exception. From the choice of the most suitable house to move in to the selection of the ideal candidate for a job position, or the adoption of the safest decision to evacuate a village after a natural disaster, there exist myriad situations where we encounter a number of options or decision alternatives, and we need to select the “best” one(s) or rank them from best to worst one according to our judgments and experience. When a single decision is to be made jointly by a group of people, we have a so-called Group Decision Making problem, in which usually each participant has their own individual opinions, concerns or interests towards the existing alternatives, but their opinions must be somehow combined into a representative opinion for the group that leads to the best (and ideally most accepted) solution by its members. Over the last decades, many researchers in the areas of group decision making and consensus building have widely investigated models, methods and decision support systems aimed at assisting decision groups in these situations, with numerous satisfactory results.

There is undeniably a wealth of published research, handbooks and monographs on different aspects of group decision making and consensus, most of which concentrate on small group decision problems. However, owing to the nowadays rise of technological paradigms capable of accommodating decision making across much larger groups of participants, much of the research efforts and scholars’ attention have recently and increasingly shifted towards decision problems involving such large groups. Many of the classical approaches to support small group decisions are often limited and unsuitable to handle the various added difficulties stemming from the participation of large decision groups. For this reason, a considerable number of research efforts have instead been devoted to defining models and methodologies specifically for supporting group decisions at large scale. The present book aims at providing the reader with a broad and complete yet concise vision of these works, outlining the main trends, models, methods and practical applications developed for supporting Large Group Decision Making processes to date, in an ample variety of real-life scenarios and domains.

In short, this book constitutes—to the best of the author’s knowledge—the first central point of reference for the interested reader in the young but rapidly evolving field of large group decision making and consensus building in large groups. The book firstly provides an introduction to the broad research area of group decision making and consensus, after which the main characteristics and challenges of large group decision making (compared to conventional small-group decision making) are presented. Subsequently, the text focuses on providing a comprehensive literature review of related research in the topic, classified into six main trends. Related disciplines and notable application domains of large group decision making research are also highlighted throughout the book, along with final notes on proposed directions for future research.

1.2 Who Should Read This Book and Why?

The text provided in this book is primarily envisaged as a key point of reference for scholars, academics and research students across the communities of Group and Multi-Criteria Decision Making under Uncertainty, Decision and Management Sciences, and Decision Support Systems, along with scientists and practitioners from any of the numerous application areas of Group/Multi-Criteria Decision Aid approaches. For the acquainted reader with these areas, the book is aimed at providing a valuable reference point to a wealth of state-of-the-art work on large-group decision making, enabling a proper insight into:

  • The existing literature with associated publications,

  • active authors and research groups in the area(s),

  • main trends and problems addressed,

  • its most widely considered real-world applications, and

  • potentially promising ideas for future investigation.

Research students and early career researchers may also benefit from having such a point of reference. For the unfamiliar but interested reader with the topic, we have considered the inclusion of a detailed introduction to Group Decision Making, Consensus Building Approaches and a brief summary of popular methods and principles for Multi-Criteria Decision Making. These preliminary contents are presented in the second chapter of the book, before moving into Large Group Decision Making. In addition, although not essential it would be highly recommended for the reader to have (or acquire) some basic knowledge about fuzzy set theory and its extensions, fuzzy preference modeling and aggregation/fusion of information in order to optimally understand the detailed discussions provided in the book. Bibliographical details of suggested readings on these topics can be found throughout the second chapter.

Since some of the newest approaches, trends and real-life applications covered in the following chapters involve the use of Data Science, Analytics, Operational Research and other Soft Computing and Intelligent Techniques, the book can be likewise of potential interest to a variety of scientists across these broader fields (e.g. computer science, operations research, management, social and political sciences, statistics, psychology), whose relationship with decision making research is becoming increasingly stronger and will be repeatedly pointed out throughout the text.

1.3 Chapter Overview

To accommodate both the familiar reader and a relatively new audience to the research problems being addressed, as discussed above, the structure of this book has been carefully planned and set out as follows:

  • Chapter 2 : Group Decision Making and Consensual Processes. This foundation-oriented chapter introduces the basic concepts, ideas and classical approaches proposed in the literature to support group and consensual decision making process. It also includes a basic overview of some important underlying steps to such processes, e.g. (1) the modeling of uncertain preferences, (2) the aggregation of individual preferences to yield representative preferential information at collective level, used for making group decisions, and (3) an overview of two popular methods for handling multi-criteria decision making problems, which often intersect with group and consensus decision making problems.

  • Chapter 3 : Scaling Things Up: Large Group Decision Making (LGDM). The paradigm shift from classical small group decisions to large-scale decisions is reflected in this chapter. It enumerates the main difficulties and challenges exhibited by conventional approaches to effectively and efficiently managing large group decisions, identifies the research trends recently adopted to cope with such difficulties, and briefly describes the potential relationship between LGDM and other disciplines.

  • Chapter 4 : LGDM Approaches and Models: A Literature Review. Based on the research trends introduced in Chap. 3, this chapter provides the reader with a detailed survey of the extant LGDM models and methodologies in the literature, subdivided into six trends, identifying within each trend different themes and specific aspects investigated by researchers in the field.

  • Chapter 5 : Implementations and Real-World Applications of LGDM Research. This chapter overviews a number of model implementations into decision support systems for large groups, and enumerates the key real-life application areas where the existing literature has been applied.

  • Chapter 6 : Conclusions and Future Directions of Research. The book finalizes drawing some conclusions and pointing out several promising directions for research in this domain.