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Managing Emergent Phenomena
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Managing Emergent Phenomena : Nonlinear Dynamics in Work Organizations

Book Details

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
Print length 406 Pages
Weight 658 grams
Product Classification: Organizational theory & behaviour
Ksh 26,100.00
Werezi Extended Catalogue 0 in stock

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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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