The impact of socio-technical communication styles on the diversity and innovation potential of global science collaboratories

Özgür Özmen (), Levent Yilmaz () and Jeffrey Smith ()
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Özgür Özmen: Oak Ridge National Laboratory
Levent Yilmaz: Auburn University
Jeffrey Smith: Auburn University

Computational and Mathematical Organization Theory, 2016, vol. 22, issue 4, No 6, 548 pages

Abstract: Abstract Emerging cyber-infrastructure tools are enabling scientists to transparently co-develop, share, and communicate about real-time diverse forms of knowledge artifacts. In these environments, communication preferences of scientists are posited as an important factor affecting innovation capacity and robustness of social and knowledge network structures. Scientific knowledge creation in such communities is called global participatory science (GPS). Recently, using agent-based modeling and collective action theory as a basis, a complex adaptive social communication network model (CollectiveInnoSim) is implemented. This work leverages CollectiveInnoSim implementing communication preferences of scientists. Social network metrics and knowledge production patterns are used as proxy metrics to infer innovation potential of emergent knowledge and collaboration networks. The objective is to present the underlying communication dynamics of GPS in a form of computational model and delineate the impacts of various communication preferences of scientists on innovation potential of the collaboration network. Gained insight can ultimately help policy-makers to design GPS environments and promote innovation.

Keywords: Complex adaptive systems; Agent-based modeling; Communication network; Collective action; Innovation; Diversity; Social network (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10588-016-9213-5

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