A multi-disciplinary exploration of how we can help decision makers to deliberate and make better decisions.

AN INTRODUCTION TO BEHAVIOR ANALYSIS Explore a fascinating introductory treatment of the principles of behavior analysis written by three leading voices in the field An Introduction to Behavior Analysis delivers an engaging and comprehensive introduction to the concepts and applications for graduate students of behavior analysis. Written from the ground up to capture and hold student interest, the book keeps its focus on practical issues. The book offers readers sound analyses of Pavlovian and operant learning, reinforcement and punishment, motivation and stimulus control, language and rule-following, decision-making and clinical behavior analysis. With fully up to date empirical research references and theoretical content, An Introduction to Behavior Analysis thoroughly justifies every principle it describes with empirical support and explicitly points out where more data are required. The text encourages students to analyze their own experiences and some foundational findings in the field in a way that minimizes jargon and maximizes engagement. Readers will also benefit from the inclusion of: A clear articulation and defense of the philosophical assumptions and overarching goals of behavior analysis. A thorough description of objective data collection, experimental methods, and data analysis in the context of psychology An exploration of the core principles of behavior analysis, presented at a level comprehensible to an introductory audience A broad array of principles that cover issues as varied as language, substance-use disorders, and common psychological disorders Perfect for students taking their first course in behavior analysis or behavior modification, An Introduction to Behavior Analysis will also earn a place in the libraries of students pursuing certification through the Behavior Analysis Certification Board or taking courses in the applied psychological sciences.

Decision analysis is a technology designed to help individuals and organizations make wise inferences and decisions. It synthesises ideas from economics, statistics, psychology, operations research, and other disciplines. A great deal of behavioural research is relevant to decision analysis; behavioural scientists have both suggested easy and natural ways to describe and quantify problems and shown the kind of errors to which unaided intuitive judgements can lead. This long-awaited book offers the4first integrative presentation of the principles of decision analysis in a behavioural context. The authors break new ground on a variety of technical topics (sensitivity analysis, the value-utility distinction, multistage inference, attitudes toward risk), and attempt to make intuitive sense out of what have been treated in the literature as endemic biases and other errors of human judgement. Those interested in artificial intelligence will find it the easiest presentation of hierarchical Bayesian inference available.

Making important business decisions is usually a difficult and complicated task. In the modern economy where businesses have to solve increasingly complex decision-making problems, it is important to learn and use methods and techniques including the analysis of behavioral data to support decision-making in practice. This book presents various methods and solutions to problems in modern data acquisition techniques and practical aspects of decision making. In particular, it addresses such important issues as: business decision making, multi-criteria decision analysis (MCDA), multidimensional comparative analysis (MCA), decision games and data acquisition techniques for decision making (declarative techniques and cognitive neuroscience techniques). Important topics such as consumers’ rational behavior, environmental management accounting, operational research methods, neuroscience including epigenetics, DEA analysis etc., as well as case studies related to decision making in management are also included.

This book lays out a foundation and taxonomy for Behavioral Decision Analysis, featuring representative work across various domains. Traditional research in the domain of Decision Analysis has focused on the design and application of logically consistent tools to support decision makers during the process of structuring problem complexity, modeling uncertainty, generating predictions, eliciting preferences, and, ultimately, making better decisions. Two commonly held assumptions are that the decision maker’s cognitive belief system is fully accessible and that this system can be understood and formalized by trained analysts. However, in past years, an active line of research has emerged studying instances in which such assumptions may not hold. This book unites this community under the common theme of Behavioral Decision Analysis. The taxonomy used in this book categorizes research based on task focus (prediction or decision) and behavioral level (individual or group). Two theoretical lenses that lie at the interface between (1) normative and descriptive research, and (2) normative and prescriptive research are introduced. The book then proceeds to highlight representative works across the two lenses focused on individual and group-level decision making. Featuring various methodologies and applications, the book serves as a reference for researchers, students, and professionals across different disciplines with a common interest in Behavioral Decision Analysis.