Harnessing Complexity: Organizational Implications of a Scientific FrontierSimon and Schuster, 12/05/2000 - 208 من الصفحات 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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الصفحة xv
... intervention . Our approach is not just an extended “ evolutionary metaphor , ” nor is it part of Social Darwinism ( Hofstadter , 1955 ) or sociobiology ( Wilson , 1975 ) . We view processes of biological change as wonder- ful examples ...
... intervention . Our approach is not just an extended “ evolutionary metaphor , ” nor is it part of Social Darwinism ( Hofstadter , 1955 ) or sociobiology ( Wilson , 1975 ) . We view processes of biological change as wonder- ful examples ...
الصفحة xvi
... intervention . The Complex Adaptive System approach is a way of looking at the world . It provides a set of concepts , a set of questions , and a set of design issues . By itself , it is not a falsifiable theory . Such a theory would ...
... intervention . The Complex Adaptive System approach is a way of looking at the world . It provides a set of concepts , a set of questions , and a set of design issues . By itself , it is not a falsifiable theory . Such a theory would ...
الصفحة 7
... interventions in a system . But what might make a sys- tem we are interested in complex ? This is a question to which we will be returning , but let us begin by saying that a system is complex when there are strong interactions among ...
... interventions in a system . But what might make a sys- tem we are interested in complex ? This is a question to which we will be returning , but let us begin by saying that a system is complex when there are strong interactions among ...
الصفحة 12
... intervention grind to a halt if we acknowledge that we do not know what might happen as a conse- quence of our actions . When experts are asked to forecast the future and its require- ments in complex settings , their customary response ...
... intervention grind to a halt if we acknowledge that we do not know what might happen as a conse- quence of our actions . When experts are asked to forecast the future and its require- ments in complex settings , their customary response ...
الصفحة 17
... interventions in a world that is hard to predict because it is complex. In contrast, a world that is hard to predict merely because it is complicated can be attacked in quite a different way. For example, nearly additive contributions ...
... interventions in a world that is hard to predict because it is complex. In contrast, a world that is hard to predict merely because it is complicated can be attacked in quite a different way. For example, nearly additive contributions ...
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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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الصفحة 65 - These communities did not become civic simply because they were rich. The historical record strongly suggests precisely the opposite: they have become rich because they were civic. The social capital embodied in norms and networks of civic engagement seems to be a
الصفحة 65 - First, networks of civic engagement foster sturdy norms of generalized reciprocity: I'll do this for you now in the expectation that down the road you or someone else will return the favor.
الصفحة 64 - social capital," the features of social organization, such as networks, norms, and trust, that facilitate coordination and cooperation.
الصفحة 64 - are engaged by public issues, not by patronage. They trust one another to act fairly and obey the law. Social and political networks are organized horizontally, not hierarchically. These "civic communities" value solidarity, civic participation, and integrity.
الصفحة 26 - among their elements. This, of course, is exactly what the Information Revolution is doing: reducing the barriers to interaction among processes that were previously isolated from each other in time or space. Information can be understood as a mediator of interaction. Decreasing the costs of its propagation and storage inherently increases possibilities for interaction effects. An Information Revolution is therefore likely to beget a complexity revolution.
الصفحة 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.
الصفحة 15 - complexity" does not simply denote "many moving parts." Instead, complexity indicates that the system consists of parts which interact in ways that heavily influence the probabilities of later events.
الصفحة 26 - If complexity is often rooted in patterns of interaction among agents, then we might expect systems to exhibit increasingly complex dynamics when changes occur that intensify
الصفحة 65 - levels of economic and institutional performance generally much higher than in the South, where social and political
الصفحة 14 - What makes prediction especially difficult in these settings is that the forces shaping the future do not add up in a simple, systemwide manner. Instead, their effects include nonlinear interactions among the components of the