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The authors analyze the optimal network structure of two types of terrorist organizations. In the centralized network, the leadership selects the level of individual effort and the level of group connectivity so as to maximize the expected net welfare of the organization's membership. Leaders in loosely connected networks will also seek to balance the trade-off between security and communications. However, with decentralized decision making, the individual nodes may not make optimal decisions from the group's perspective. As a consequence, the decentralized decision-making process is suboptimal from the overall perspective of the network. In particular, the leadership in a centralized network is able to coordinate the activities of all network members and to take advantage of important network externalities.

The authors analyze the optimal network structure of two types of terrorist organizations. In the centralized network, the leadership selects the level of individual effort and the level of group connectivity so as to maximize the expected net welfare of the organization's membership. Leaders in loosely connected networks will also seek to balance the trade-off between security and communications. However, with decentralized decision making, the individual nodes may not make optimal decisions from the group's perspective. As a consequence, the decentralized decision-making process is suboptimal from the overall perspective of the network. In particular, the leadership in a centralized network is able to coordinate the activities of all network members and to take advantage of important network externalities. [Reprinted by permission of Sage Publications Inc., copyright holder.]

PurposeDespite the systemic nature of circular economy (CE), theorisation that draws from a supply network perspective is only incipient. Moreover, the operations and supply chain management (OSCM) field has engaged in little dialogue with circularity. This study explores social network analysis (SNA) to depict how the shift from linear to circular not only leads to higher rates of resource economy, repair and recycle but also reshapes governance dynamics and network structure of supply networks.Design/methodology/approachThe study departs from a systematic review of the literature and draws from core concepts in OSCM, CE and SNA to offer theoretical propositions that articulate how social network metrics can depict supply network circularity. The framework is illustrated with examples from fashion and electronics industries.FindingsFour theoretical propositions enlighten how betweenness centrality, eigenvector centrality and network density can explain the shift from linear to circular supply networks across the three CE strategies of narrowing, slowing and closing.Originality/valueThe combination of biomimicry, CE, the push–pull dichotomy and social network metrics offer a theory-driven framework for supply network circularity.

Abstract
This paper brings two major research lines in current sociology together. Research on social networks has long focused primarily on network effects but meanwhile also addresses the emergence and dynamics of networks. Research on trust in social and economic relations shows that networks have effects on trust. Using game theory, we provide a simple model that allows for an integrated and simultaneous analysis of network effects on trust and for the endogenous emergence of the network. The model also allows for characterizing the value of the network. We use standard assumptions on full strategic rationality. Testable implications of the model as well as model extensions are sketched.

How do we think beyond the dominant images and imaginaries of connectivity? Undoing Networks enables a different connectivity: "digital detox" is a luxury for stressed urbanites wishing to lead a mindful life. Self-help books advocate "digital minimalism" to recover authentic experiences of the offline. Artists envision a world without the internet. Activists mobilize against the expansion of the 5G network. If connectivity brought us virtual communities, information superhighways, and participatory culture, disconnection comes with privacy tools, Faraday shields, and figures of the shy. This book explores non-usage and the "right to disconnect" from work and from the excessive demands of digital capitalism.

Disrupting dark networks focuses on how social network analysis can be used to craft strategies to track, destabilize and disrupt covert and illegal networks. The book begins with an overview of the key terms and assumptions of social network analysis and various counterinsurgency strategies. The next several chapters introduce readers to algorithms and metrics commonly used by social network analysts. They provide worked examples from four different social network analysis software packages (UCINET, NetDraw, Pajek and ORA) using standard network data sets as well as data from an actual terrorist network that serves as a running example throughout the book. The book concludes by considering the ethics of and various ways that social network analysis can inform counterinsurgency strategizing. By contextualizing these methods in a larger counterinsurgency framework, this book offers scholars and analysts an array of approaches for disrupting dark networks

Complex Social Networks is a newly emerging (hot) topic with applications in a variety of domains, such as communication networks, engineering networks, social networks, and biological networks. In the last decade, there has been an explosive growth of research on complex real-world networks, a theme that is becoming pervasive in many disciplines, ranging from mathematics and computer science to the social and biological sciences. Optimization of complex communication networks requires a deep understanding of the interplay between the dynamics of the physical network and the information dynami

Inventors embed themselves in knowledge networks consisting of links between knowledge elements and collaboration networks with other inventors. These two networks are decoupled: Their structural features are distinct, and they jointly influence inventors' local searches for knowledge. Using a longitudinal patent dataset comprising 12,174 observations, this study investigates the effects of two structural features of inventors in these networks—degree centrality and structural holes—on their local search behaviors. Our findings reveal that the degree centrality of inventors' knowledge elements in the intra-organizational knowledge network contributes to the depth and breadth of their local search behaviors, while structural holes hinder such behaviors. Furthermore, the effect of degree centrality in the intra-organizational knowledge network for local searches increases when inventors hold central positions and span more structural holes in the intra-organizational collaboration network. The negative effect of structural holes in the knowledge network for local searches weakens when inventors hold central positions in the collaboration network. These findings contribute to the literature on knowledge searches by decoupling the knowledge and collaboration networks and analyzing their effects on the depth and breadth of local searches and offer practical implications to organizational managers and researchers.