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See detailModular organizations and informal structures: Modularity, performance and the alignment of organizational networks
Jonard, Nicolas UL; Cowan, Robin

in Industrial and Corporate Change (2023), 32(1), 181-207

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See detailDesperately Seeking Small Worlds in Corporate Boards: International Evidence from Listed Firms
Hamadi, Malika; Heinen, Andreas; Jonard, Nicolas UL et al

E-print/Working paper (2015)

Detailed reference viewed: 192 (14 UL)
See detailOrganization, Affect and Performance: Interactions between Formal and Informal Structure
Cowan, Robin; Jonard, Nicolas UL; Weehuizen, Rifka

Scientific Conference (2014, November)

Detailed reference viewed: 107 (1 UL)
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See detailImitation and Efficient Contagion
Boyer, Tristan; Jonard, Nicolas UL

in Journal of Economic Behavior and Organization (2014), 100

Detailed reference viewed: 238 (21 UL)
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See detailOrganizations and Emotions: Design, Contagion and Performance
Cowan, Nicolas; Jonard, Nicolas UL; Wehuizen, Rifka

Scientific Conference (2013, June)

Detailed reference viewed: 61 (6 UL)
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See detailFits and Misfits: Technological Matching and R&D Networks
Cowan, Robin; Jonard, Nicolas UL; Sanditov, Bulat

in Burger-Helmchen, Thierry (Ed.) The Economics of Creativity: Ideas, Firms and Markets (2013)

Detailed reference viewed: 179 (121 UL)
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See detailPrescriptions for Network Strategy: Does Evidence of Network Effects in Cross-Section Support them?
Baum, Joel; Cowan, Robin; Jonard, Nicolas UL

in Strategic Management Journal (2013)

Detailed reference viewed: 326 (138 UL)
See detailThe Small World of Corporate Boards: International Evidence from Listed Firms
Hamadi, Malika; Heinen, Andreas; Jonard, Nicolas UL et al

Scientific Conference (2012, August)

Detailed reference viewed: 45 (0 UL)
See detailOrganizational Structure, Organizational Performance and Emotional Contagion
Cowan, Robin; Jonard, Nicolas UL; Weehuizen, Rifka

Presentation (2012, May)

Detailed reference viewed: 55 (2 UL)
See detailPrescriptions for Network Strategy: Does Evidence in Cross-Section Effects Support Them?
Baum, Joel; Cowan, Robin; Jonard, Nicolas UL

Scientific Conference (2011)

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See detailNetwork-Independent Partner Selection and the Evolution of Innovation Networks
Baum, Joel; Cowan, Robin; Jonard, Nicolas UL

in Management Science (2010), 56

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See detailKnowledge Portfolios and the Organization of Innovation Networks
Cowan, Robin; Jonard, Nicolas UL

in Academy of Management Review (2009), 34

Detailed reference viewed: 169 (4 UL)
See detailKnowledge Structures
Müller, Moritz; COWAN, Robin; Duysters, Geert et al

Report (2009)

This paper investigates how technological distance between firms affects their network of R\&D alliances. Our theoretic model assumes that the benefit of an alliance between two firms is given by their ... [more ▼]

This paper investigates how technological distance between firms affects their network of R\&D alliances. Our theoretic model assumes that the benefit of an alliance between two firms is given by their technological distance. This benefit-distance relationship determines the ego-network of each firm as well as the overall network structure. Empirical relevance is confirmed for the bio-pharmaceutical industry. Although we find that the network structure is largely explained by firm size, technological distance determines the positioning of firms in the network. [less ▲]

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See detailIf the Alliance fits...: Innovation and Network Dynamics
Cowan, Robin; Jonard, Nicolas UL

in Advances in Strategic Management (2008), 25

Detailed reference viewed: 76 (11 UL)
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See detailStructural Holes, Innovation and the Distribution of Ideas
Jonard, Nicolas UL; Cowan, Robin

in Journal of Economic Interaction and Coordination (2007), 2(2), 93-110

We model knowledge diffusion in a population of agents situated on a network, interacting only over direct ties. Some agents are by nature traders, others are by nature "givers": traders demand a quid pro ... [more ▼]

We model knowledge diffusion in a population of agents situated on a network, interacting only over direct ties. Some agents are by nature traders, others are by nature "givers": traders demand a quid pro quo for information transfer; givers do not. We are interested in efficiency of diffusion and explore the interplay between the structure of the population (proportion of traders), the network structure (clustering, path length and degree distribution), and the scarcity of knowledge. We find that at the global level, trading (as opposed to giving) reduces efficiency. At the individual level, highly connected agents do well when knowledge is scarce, agents in clustered neighbourhoods do well when it is abundant. The latter finding is connected to the debate on structural holes and social capital. [less ▲]

Detailed reference viewed: 138 (18 UL)
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See detailMerit, Approbation and the Evolution of Social Structure
Jonard, Nicolas UL; Cowan, Robin

in Journal of Economic Behavior and Organization (2007), 64(3-4), 295-315

In this paper we study a society in which individuals gain utility from income and from social approbation. Income is correlated with class. Approbation is given to an unobservable trait, which must be ... [more ▼]

In this paper we study a society in which individuals gain utility from income and from social approbation. Income is correlated with class. Approbation is given to an unobservable trait, which must be signalled through the agent’s social mobility, i.e. class change. Mobility is driven by a simple mechanism involving inheritance, effort and ability. Thus social structure (class composition) is affected by individuals’ quest for approbation, and we study how that affects the emergence and multiplicity of long run social organizations, including hybrid forms of dynasties and meritocracies. Specifically we observe that even though social mobility is driven purely by a meritocratic mechanism, pure dynasties can emerge. We then introduce a feedback between the size of the upper class and its income value, so that effort levels and social structure are jointly endogenous. We derive results on equilibrium effort levels and stationary (when they exist) social structures. Social organization can converge to a unique steady state, multiple long run equilibria or cycles. [less ▲]

Detailed reference viewed: 120 (11 UL)
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See detailNetwork Architecture, Barter Exchange and the Diffusion of Ideas
Jonard, Nicolas UL; Cowan, Robin

in International Journal of Agricultural Resources, Governance & Ecology (2007), 6(2), 165-178

We model knowledge diffusion as agents exchanging ideas through a barter process. The model builds on empirical observations of informal knowledge trading among competing agents. The process takes place ... [more ▼]

We model knowledge diffusion as agents exchanging ideas through a barter process. The model builds on empirical observations of informal knowledge trading among competing agents. The process takes place on a network substrate in which agents are nodes, and can trade only with those to whom they have direct links (edges). When two agents meet, they make a mutually profitable trade. This process repeats, and is the foundation on which knowledge diffuses through the economy. Our interest is in how the structure of the network affects diffusion performance. The extent of idea diffusion is affected both by the circumference of the graph and by local coherence: diffusion is most efficient when the network is a small world. The distribution of knowledge over agents is also most equal when networks are small worlds. [less ▲]

Detailed reference viewed: 117 (1 UL)
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See detailBilateral Collaboration and the Emergence of Networks
Jonard, Nicolas UL; Cowan, Robin; Zimmermann, Jean-Benoît

in Management Science (2007), 53(7), 1051-1067

In this paper, we model the formation of innovation networks as they emerge from bilateral decisions. In contrast to much of the literature, here firms only consider knowledge production, and not network ... [more ▼]

In this paper, we model the formation of innovation networks as they emerge from bilateral decisions. In contrast to much of the literature, here firms only consider knowledge production, and not network issues, when deciding on partners. Thus, we focus attention on the effects of the knowledge and information regime on network formation. The effectiveness of a bilateral collaboration is determined by cognitive, relational, and structural embeddedness. Innovation results from the recombination of knowledge held by the partners to the collaboration, and its success is determined in part by the extent to which firms’ knowledge complement each other. Previous collaborations (relational embeddedness) increase the probability of a successful collaboration, as does information gained from common third parties (structural embeddedness). Repeated alliance formation creates a network. Two features are central to the innovation process: how firms pool their knowledge resources, and how firms derive information about potential partners. When innovation is decomposable into separate subtasks, networks tend to be dense; when structural embeddedness is important, networks become cliquish. For some regions in this parameter space, small worlds emerge. Key Words: networks; innovation; knowledge; collaborative R&D; embeddedness [less ▲]

Detailed reference viewed: 294 (8 UL)
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See detailEvolving Networks of Inventors
Cowan, Robin; Jonard, Nicolas UL; Zimmermann, Jean-Benoît

in Journal of Evolutionary Economics (2006), 16

Detailed reference viewed: 90 (2 UL)
See detailNetwork Formation, Innovation and the Use of Information Technologies
Cowan, Robin; Jonard, Nicolas UL

in Soete, Luc; Ter Weel, Bas (Eds.) The Economics of the Digital Society (2005)

Detailed reference viewed: 41 (0 UL)