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      Structural Dynamics and Intentional Governance in Strategic Interorganizational Network Evolution: A Multilevel Approach

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          Abstract

          This article aims to shed light on the drivers underlying the role and scope of intentional governance of the structural dynamics of whole interorganizational networks. Prior research has distinguished networks that are emergent from networks that are orchestrated. While empirical studies have shown situations in which the role and scope of intentional governance of whole interorganizational networks has changed in time, and there is a growing interest regarding the endogenous drivers of network dynamics, the dimensions that influence intentional governance of network structure dynamics and the way this is carried out remain still to be elucidated. In order to pinpoint these drivers, we leverage the models of network structure dynamics elaborated within studies conducted at the intersection between network research and complexity science to propose a multilevel interpretive framework that clarifies the role and scope of intentional agency at different structural levels of interorganizational networks. Our framework advances a twofold conceptual contribution: on one hand, we tackle the change in the role and scope of intentional governance of network structures in both the early stages and the later stages of network evolution. On the other, we interpret the network of formal ties as resembling the accelerating network model, with the network of informal ties being akin to the scale-free (or truncated scale-free) network model of complex networks theory.

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          Collective dynamics of 'small-world' networks.

          Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.
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            The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organizational Fields

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              The Strength of Weak Ties

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                Author and article information

                Journal
                Organization Studies
                Organization Studies
                SAGE Publications
                0170-8406
                1741-3044
                March 2016
                January 10 2016
                March 2016
                : 37
                : 3
                : 349-373
                Affiliations
                [1 ]University of Catania, Italy
                [2 ]University of Palermo, Italy
                Article
                10.1177/0170840615625706
                5328a182-aa68-44e5-8aec-eb4c3afa059f
                © 2016

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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