Managing Complexity: Insights, Concepts, ApplicationsDirk Helbing Springer, 13/10/2007 - 393 páginas Each chapter in Managing Complexity focuses on analyzing real-world complex systems and transferring knowledge from the complex-systems sciences to applications in business, industry and society. The interdisciplinary contributions range from markets and production through logistics, traffic control, and critical infrastructures, up to network design, information systems, social conflicts and building consensus. They serve to raise readers' awareness concerning the often counter-intuitive behavior of complex systems and to help them integrate insights gained in complexity research into everyday planning, decision making, strategic optimization, and policy. Intended for a broad readership, the contributions have been kept largely non-technical and address a general, scientifically literate audience involved in corporate, academic, and public institutions. |
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... cluster analysis [7, 8] of the bidding behavior of almost one million users. Groups of eBay users with common interest or demand are found exploiting only the information of which users competed in the same auction. The classification ...
... cluster analysis of eBay categories [4]. Clustering customers directly, however, reveals information about people and their diverse and maybe very special interests. In order to perform targeted marketing on a particular customer milieu ...
... cluster analysis in this bidder network, we study its general statistical properties looking for indications of cluster structure [19]. We compare the results to a randomized null model (RNM) obtained from reshuffling the original data ...
... cluster analysis containing only those bidders having taken part in more than one auction data RNM reduced number of ... clustering coefficient as a function of the degree of a node. The clustering coefficient c(k) denotes the average ...
... cluster index to each bidder as to maximize a well established quality function known as network modularity Q defined by Girvan and Newman (GN) [23]. The definition of Q can also be written as [24]: Q = M1 q∑ s(m} ss − {{γ[mss])} c ss ...
Índice
1 | |
18 | |
Managing Autonomy and Control in Economic Systems | 37 |
The Illusion of Control | 57 |
Benefits and Drawbacks of Simple Models for Complex | 89 |
Coping with Nonlinearity and Complexity | 119 |
Repeated Auction Games and Learning Dynamics | 137 |
Decentralized Approaches to Adaptive Traffic Control | 177 |
Stefano Battiston Domenico Delli Gatti Mauro Gallegati 219 | 241 |
Bootstrapping the Long Tail in Peer to Peer Systems | 262 |
Complexity in Human Conflict | 303 |
Fostering Consensus in Multidimensional Continuous Opinion | 321 |
MultiStakeholder Governance Emergence | 335 |
Evolutionary Engineering of Complex Functional Networks | 350 |
Julian Sienkiewicz Agata Fronczak Piotr Fronczak Krzysztof | 369 |
Index | 389 |
Arne Kesting Martin Schönhof Stefan Lämmer Martin Treiber | 201 |
Trade Credit Networks and Systemic Risk | 218 |
Outras edições - Ver tudo
Managing Complexity: Insights, Concepts, Applications Dirk Helbing Pré-visualização indisponível - 2007 |
Managing Complexity: Insights, Concepts, Applications Dirk Helbing Pré-visualização indisponível - 2010 |