The Decision

Decision intelligence (DI) has been widely named as a top technology trend for several years, and the Gartner Group reports that more than a third of large organizations are adopting it. Some even say that DI is the next step in the evolution of AI. Many software vendors offer DI solutions today, as they help organizations implement their evidence-based or data-driven decision strategies.

Decision intelligence (DI) has been widely named as a top technology trend for several years, and the Gartner Group reports that more than a third of large organizations are adopting it. Some even say that DI is the next step in the evolution of AI. Many software vendors offer DI solutions today, as they help organizations implement their evidence-based or data-driven decision strategies.

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Decision making is a complex phenomenon which normally is deeply integrated into social life. At the same time the decision making process often gives the decision maker an opportunity for conscious planning and for taking a reflective stance with respect to the action considered. This suggests that decision making allows creative solutions with a potential to change the course of events both on an individual and a collective level. Given these considerations, we argue that in order to more fully understand decision making the perspectives of different disciplines are needed. In this volume we have attempted to draw together contributions that would provide a broad view of decision making. Much work has been carried out in the writing and editing of this volume. First of all we would like to thank the contributors for their efforts in producing interesting and important texts and for their patience in the editorial process. Each chapter was edited by two or three reviewers. These reviewers are listed on a separate page in this book. Our heartfelt thanks go to them for their time and for their incisive and constructive reviews! We are also grateful to the publishing editors at Kluwer Academic Publishers, Christiane Roll and Dorien Francissen, who have been generous with their encouragement and patience throughout the editorial process.

Decision-making in real-world problems, including individual process decisions, requires an appropriate and reliable decision support system. Fuzzy set theory, rough set theory, and neutrosophic set theory, which are MCDM techniques, are useful for modeling complex decision-making problems with imprecise, ambiguous, or vague data.