Social network heterogeneity benefits individuals at the expense of groups in the creation of innovation (original) (raw)

The social network side of individual innovation

Organizational Psychology Review, 2015

The current study provides a comprehensive analysis and integration of the literature on the social network correlates of individual innovation. Reviewing the extant literature, we cluster existing network measures into five general properties—size, strength, brokerage, closure, and diversity. Using meta-analysis, we estimate the population effect sizes between these network properties and innovation. Results showed that brokerage had the strongest positive relation to innovation, followed by size, diversity, and strength. Closure, by contrast, had a weak, negative association with innovation. In addition, we offer a path-analytic integration of the literature proposing and testing the direct and indirect effects of the five properties on innovation. We suggest that network size and strength impact innovation through a web of relations with the more proximal features of brokerage, closure, and diversity. Our path-analytic integration considers the two dominant perspectives on the ef...

The social network side of individual innovation: A meta-analysis and path-analytic integration

Organizational Psychology Review, 2015

The current study provides a comprehensive analysis and integration of the literature on the social network correlates of individual innovation. Reviewing the extant literature, we cluster existing network measures into five general properties—size, strength, brokerage, closure, and diversity. Using meta-analysis, we estimate the population effect sizes between these network properties and innovation. Results showed that brokerage had the strongest positive relation to innovation, followed by size, diversity, and strength. Closure, by contrast, had a weak, negative association with innovation. In addition, we offer a path-analytic integration of the literature proposing and testing the direct and indirect effects of the five properties on innovation. We suggest that network size and strength impact innovation through a web of relations with the more proximal features of brokerage, closure, and diversity. Our path-analytic integration considers the two dominant perspectives on the effects of social network —brokerage versus closure—simultaneously allowing us to establish their relative efficacy in predicting innovation. In addition, our model highlights that network strength can have both negative and positive effects (via different direct and indirect pathways) and thus inherently involves a tradeoff. We discuss the implications of these results for future research and practice.

Being a Catalyst of Innovation: the role of knowledge diversity and network closure

Organization Science

Whereas recent research on organizational innovation suggests that there is an ecology of roles supporting the innovative process, the majority of network research has concentrated on the role of inventors. In this paper, we contribute to research on organizational innovation by studying the social structural conditions conducive to individuals supporting, facilitating and promoting the innovativeness of their colleagues – a role we refer to as catalysts of innovation. We consider an individual’s network position and the type of knowledge available to them through their network as key enabling conditions. We argue that the unique configuration of having access to diverse knowledge through a closed network enables individuals to act as innovation catalysts. Based on a study of 276 researchers in the R&D division of a large multinational high-tech company we find strong support for our prediction and demonstrate that catalysts make important contributions to the innovative outputs of other researchers in terms of their colleagues’ patent applications.

Networked innovation and coalition formation: the effect of group-based social preferences

In this paper, we study the production and dissemination of public knowledge goods, such as technological knowledge, generated by a network of voluntarily cooperating innovators. We develop a privatecollective model of public knowledge production in networked innovation systems, where group-based social preferences have an impact on the coalition formation of developers. Our model builds on the large empirical literature on voluntary production of pooled public knowledge goods, including source code in communities of software developers or data provided to open access data repositories. Our analysis shows under which conditions social preferences, such as ‘group belonging’ or ‘peer approval’, influence the stable coalition size, as such rationalising several stylized facts emerging from large-scale surveys of open-source software developers, previously unaccounted for. Furthermore, heterogeneity of social preferences is added to the model to study the formation of stable but mixed coalitions.