Book Cover

Emergence: Complexity & Organization 2004 Annual - Volume 6

Written/Edited by: Kurt A. Richardson, Jeffrey A. Goldstein, Peter M. Allen and David Snowden
2006, ISBN 9780976681489 (552 pages + index), ISCE Publishing

Available Formats:

HARDBACK: $75.99
SOFTBACK: $45.99

Organizations of all kinds struggle to understand, adapt, respond and manipulate changing conditions in their internal and external environments. Approaches based on the causal, linear logic of mechanistic sciences and engineering continue to play an important role, given people’s ability to create order. But such approaches are valid only within carefully circumscribed boundaries. They become counterproductive when the same organizations display the highly reflexive, context-dependent, dynamic nature of systems in which agents learn and adapt and new patterns emerge. The rapidly expanding discussion about complex systems offers important contributions to the integration of diverse perspectives and ultimately new insights into organizational effectiveness. There is increasing interest in complexity in mainstream business education, as well as in specialist business disciplines such as knowledge management. Real world systems can’t be completely designed, controlled, understood or predicted, even by the so-called sciences of complexity, but they can be more effective when understood as complex systems. While many scientific disciplines explore complexity through mathematical models and simulations, Emergence: Complexity & Organization explores the emerging understanding of human systems that is informed by this research. Engineered and emergent views of human systems can coexist, creating a useful tension that drives organizational evolution. However, neither academics nor practitioners can leverage complexity alone. Academic discussions about complexity are often biased towards quantitative research and mathematical models that are inappropriately prescriptive for systems comprised of actors endowed with free will, who are simultaneously part of and aware of the system. The metaphors of complexity have a usefulness of their own as well, but too often they are applied without adequate reference to the mechanisms, models and mathematics behind them. This 2004 Annual includes articles from Isabelle Stengers, Julie K

Click here to download detailed contents (PDF format)