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Managing Emergent Phenomena : Nonlinear Dynamics in Work Organizations

By: Stephen J. Guastello (Author)

Manufacture on Demand

Ksh 34,200.00

Format: Hardback or Cased Book

ISBN-10: 0805831630

ISBN-13: 9780805831634

Publisher: Taylor & Francis Inc

Imprint: Psychology Press

Country of Manufacture: US

Country of Publication: GB

Publication Date: Dec 1st, 2001

Publication Status: Active

Product extent: 406 Pages

Weight: 658.00 grams

Product Classification / Subject(s): Organizational theory & behaviour

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This book about chaos theory or complexity theory is the study of events that change over time and space. This book will present a viable theory of organizations that integrates nonlinear dynamic system principles. It will be of interest to management
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.

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