Harnessing Complexity: Organizational Implications of a Scientific FrontierSimon and Schuster, 12. maí 2000 - 208 síður Recent advances in the study of complexity have given scientists profound new insights into how natural innovation occurs and how its power can be exploited. Now two pioneers in the field, Robert Axelrod and Michael D. Cohen, provide leaders in business and government with a guide to complexity that will help them make effective decisions in a world of rapid change. Building on evolutionary biology, computer science, and social design, Axelrod and Cohen have constructed a unique framework for improving the way people work together. Their approach to management is based on the concept of the Complex Adaptive System, which can describe everything from rain forests to the human gene pool, and from automated software agents to multinational companies. The authors' framework reveals three qualities that all kinds of managers must cultivate in their organization:
This simple, paradigm-shifting analysis of how people work together will transform the way we think about getting things done in a group. Harnessing Complexity is the essential guide to creating wealth, power, and knowledge in the 21st century. |
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actions activation agents or strategies approach artifacts attributing credit attribution of credit barriers biological Carl Simon chapter Cohen Complex Adaptive Systems complex systems complexity research conceptual space consequences context cooperation copying costs create criteria dynamics economic effective elements example exploitation exploration factors failures forkball framework genetic genetic algorithm Grameen banking HARNESSING COMPLEXITY ideas imitation important improvement increase Information Revolution interaction patterns interventions kind learning Linux measures of success mechanisms ment military natural selection neighborhood networks open source operating system organizational organizations patterns of interaction performance measures physical space policy makers populations of agents possible prediction problem processes proximity random recombining result Riolo risk Robert Axelrod selection self-organized criticality signal simulation situations social capital social systems spread structure tags teraction tion Tit for Tat tive trade-off types University Press users variation variety virus
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Síða 7 - a system is complex when there are strong interactions among its elements, so that current events heavily influence the probabilities of many kinds of later events.