This textbook comprehensively covers the basic principles and most recent advances regarding visual displays, auditory and tactile displays and controls; psychophysics; cognitive processes; human-computer interaction, artificial intelligence and artificial life; stress and human performance; occupational accidents and prevention; human group dynamics and complex systems; and anthropometry, workspace and environmental design. The systems perspective emphasizes nonlinear dynamics for system performance changes and emergent behaviours of complex person-machine systems. This book- • Surveys principles of conventional and computer-based machine interaction. • Assesses the relative effectiveness of accident analysis and prevention strategies. • Highlights nonlinear dynamics for system performance changes. • Examines artificial intelligence and complex systems. • Investigates sources of cognitive workload and fatigue. The textbook will be a valuable resource for advanced undergraduates and graduate students in diverse fields including ergonomics, human factors, cognitive science, computer science, operations management, and psychology. The textbook brings together core principles of person-machine interaction, accident analysis and prevention strategies, risk analysis and resilience, artificial intelligence, group dynamics, and nonlinear dynamics for an enhanced understanding of complex person-machine systems.

Whether talking about steering a wheelbarrow over rugged terrain or plotting the course of international relations, human performance systems involve change. Sometimes changes are subtle or evolutionary, sometimes they are catastrophic or revolutionary, and sometimes the changes are from periods of relative calm to periods of vibrant oscillations to periods of chaos. As a general rule, more complex systems are likely to produce more complex forms of change. Although social scientists have long acknowledged that change occurs and have considered ways to effect desirable change, the dynamical processes of change have been poorly understood in the past. This volume combines recent advances in mathematics and experimental design with the best available social science theories to produce a new, integrated, and compact theory of work, organizations, and social evolution. The domains of application extend from human decision-making processes to personnel selection and work motivation, work performance under conditions of stress, accident and health risk analysis, the development of social institutions and economic systems, creativity and innovation, organizational development and group dynamics, and political revolutions and war. Relative to other literature on nonlinear dynamical systems theory (NDS), this book is unique in that it integrates new developments in NDS with substantive psychological theory. It builds on many recent developments in organizational theory to show that nonlinear dynamics were often implicit in those works all along. The result is an entirely new way of viewing social events, understanding change processes, and asking questions about social systems. This book also contains much new empirical work and explains the newly developed methods for testing these new hypotheses.

This book presents new theory and empirical studies on the roles of cognitive workload and fatigue on repeated financial decisions. The mathematical models that are developed here utilize two cusp catastrophe functions for discontinuous changes in performance and integrate objective measures of workload, subjective experiences, and individual differences among the decision makers. Additional nonlinear dynamical processes are examined with regard to persistence and antipersistence in decisions, entropy, further explanations of overall performance, and the identification of risk-optimization profiles for long sequences of decisions.

Whether talking about steering a wheelbarrow over rugged terrain or plotting the course of international relations, human performance systems involve change. Sometimes changes are subtle or evolutionary, sometimes they are catastrophic or revolutionary, and sometimes the changes are from periods of relative calm to periods of vibrant oscillations to periods of chaos. As a general rule, more complex systems are likely to produce more complex forms of change.
Although social scientists have long acknowledged that change occurs and have considered ways to effect desirable change, the dynamical processes of change have been poorly understood in the past. This volume combines recent advances in mathematics and experimental design with the best available social science theories to produce a new, integrated, and compact theory of work, organizations, and social evolution. The domains of application extend from human decision-making processes to personnel selection and work motivation, work performance under conditions of stress, accident and health risk analysis, the development of social institutions and economic systems, creativity and innovation, organizational development and group dynamics, and political revolutions and war.
Relative to other literature on nonlinear dynamical systems theory (NDS), this book is unique in that it integrates new developments in NDS with substantive psychological theory. It builds on many recent developments in organizational theory to show that nonlinear dynamics were often implicit in those works all along. The result is an entirely new way of viewing social events, understanding change processes, and asking questions about social systems. This book also contains much new empirical work and explains the newly developed methods for testing these new hypotheses.

Chaos, catastrophe, self-organization, and complexity theories (nonlinear dynamics) now have practical and measurable roles in the functioning of work organizations. Managing Emergent Phenomena begins by describing how the concept of an organization has changed from a bureaucracy, to a humanistic and organic system, to a complex adaptive system. The dynamics concepts are then explained along with the most recent research methods for analyzing real data. Applications include: work motivation, personnel selection and turnover, creative thinking by individuals and groups, the development of social networks, coordination in work groups, the emergence of leaders, work performance in organizational hierarchies, economic problems that are relevant to organizations, techniques for predicting the future, and emergency management. Each application begins with a tight summary of standard thinking on a subject, followed by the new insights that are afforded by nonlinear dynamics and the empirical data supporting those ideas. Unusual concepts are also encountered, such as the organizational unconscious, collective intelligence, and the revolt of the slaved variables. The net results are a new perspective on what is really important in organizational life, original insights on familiar experiences, and some clear signposts for the next generation of nonlinear social scientists.

Although its roots can be traced to the 19th century, progress in the study of nonlinear dynamical systems has taken off in the last 30 years. While pertinent source material exists, it is strewn about the literature in mathematics, physics, biology, economics, and psychology at varying levels of accessibility. A compendium research methods reflecting the expertise of major contributors to NDS psychology, Nonlinear Dynamical Systems Analysis for the Behavioral Sciences Using Real Data examines the techniques proven to be the most useful in the behavioral sciences. The editors have brought together constructive work on new practical examples of methods and application built on nonlinear dynamics. They cover dynamics such as attractors, bifurcations, chaos, fractals, catastrophes, self-organization, and related issues in time series analysis, stationarity, modeling and hypothesis testing, probability, and experimental design. The analytic techniques discussed include several variants of the fractal dimension, several types of entropy, phase-space and state-space diagrams, recurrence analysis, spatial fractal analysis, oscillation functions, polynomial and Marquardt nonlinear regression, Markov chains, and symbolic dynamics. The book outlines the analytic requirements faced by social scientists and how they differ from those of mathematicians and natural scientists. It includes chapters centered on theory and procedural explanations for running the analyses with pertinent examples and others that illustrate applications where a particular form of analysis is seen in the context of a research problem. This combination of approaches conveys theoretical and practical knowledge that helps you develop skill and expertise in framing hypotheses dynamically and building viable analytic models to test them.

This textbook comprehensively covers the basic principles and most recent advances regarding visual displays, auditory and tactile displays and controls; psychophysics; cognitive processes; human-computer interaction, artificial intelligence and artificial life; stress and human performance; occupational accidents and prevention; human group dynamics and complex systems; and anthropometry, workspace and environmental design. The systems perspective emphasizes nonlinear dynamics for system performance changes and emergent behaviours of complex person-machine systems. This book- • Surveys principles of conventional and computer-based machine interaction. • Assesses the relative effectiveness of accident analysis and prevention strategies. • Highlights nonlinear dynamics for system performance changes. • Examines artificial intelligence and complex systems. • Investigates sources of cognitive workload and fatigue. The textbook will be a valuable resource for advanced undergraduates and graduate students in diverse fields including ergonomics, human factors, cognitive science, computer science, operations management, and psychology. The textbook brings together core principles of person-machine interaction, accident analysis and prevention strategies, risk analysis and resilience, artificial intelligence, group dynamics, and nonlinear dynamics for an enhanced understanding of complex person-machine systems.

Chaos, catastrophe, self-organization, and complexity theories (nonlinear dynamics) now have practical and measurable roles in the functioning of work organizations. "Managing Emergent Phenomena" begins by describing how the concept of an organization has changed from a bureaucracy, to a humanistic and organic system, to a complex adaptive system. The dynamics concepts are then explained along with the most recent research methods for analyzing real data. Applications include: work motivation, personnel selection and turnover, creative thinking by individuals and groups, the development of social networks, coordination in work groups, the emergence of leaders, work performance in organizational hierarchies, economic problems that are relevant to organizations, techniques for predicting the future, and emergency management.
Each application begins with a tight summary of standard thinking on a subject, followed by the new insights that are afforded by nonlinear dynamics and the empirical data supporting those ideas. Unusual concepts are also encountered, such as the organizational unconscious, collective intelligence, and the revolt of the slaved variables. The net results are a new perspective on what is really important in organizational life, original insights on familiar experiences, and some clear signposts for the next generation of nonlinear social scientists.

This book presents new theory and empirical studies on the roles of cognitive workload and fatigue on repeated financial decisions. The mathematical models that are developed here utilize two cusp catastrophe functions for discontinuous changes in performance and integrate objective measures of workload, subjective experiences, and individual differences among the decision makers. Additional nonlinear dynamical processes are examined with regard to persistence and antipersistence in decisions, entropy, further explanations of overall performance, and the identification of risk-optimization profiles for long sequences of decisions.

While many books have discussed methodological advances in nonlinear dynamical systems theory (NDS), this volume is unique in its focus on NDS s role in the development of psychological theory. After an introductory chapter covering the fundamentals of chaos, complexity, and other nonlinear dynamics, subsequent chapters provide in-depth coverage of each of the specific topic areas in psychology. A concluding chapter takes stock of the field as a whole, evaluating important challenges for the immediate future. The chapters are written by experts in the use of NDS in each of their respective areas, including biological, cognitive, developmental, social, organizational, and clinical psychology. Each chapter provides an in-depth examination of theoretical foundations and specific applications and a review of relevant methods. This edited collection represents the state of the art in NDS science across the disciplines of psychology."

While many books have discussed methodological advances in nonlinear dynamical systems theory (NDS), this volume is unique in its focus on NDS's role in the development of psychological theory. After an introductory chapter covering the fundamentals of chaos, complexity and other nonlinear dynamics, subsequent chapters provide in-depth coverage of each of the specific topic areas in psychology. A concluding chapter takes stock of the field as a whole, evaluating important challenges for the immediate future. The chapters are written by experts in the use of NDS in each of their respective areas, including biological, cognitive, developmental, social, organizational and clinical psychology. Each chapter provides an in-depth examination of theoretical foundations and specific applications and a review of relevant methods. This edited collection represents the state of the art in NDS science across the disciplines of psychology.