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

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 networks—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. Paper received 5 June 2014; revised version accepted 15 November 2014. Corresponding author: Greg R. Oldham, A. B. Freeman School of Business, Tulane University, 7 McAlister Dr., New Orleans, LA 70118, USA. Email: [email protected] Organizational Psychology Review 2015, Vol. 5(3) 191–223 a The Author(s) 2015 Reprints and permission: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/2041386614564105 opr.sagepub.com Organizational Psychology Review at DUQUESNE UNIV on August 26, 2015 opr.sagepub.com Downloaded from