The role of collective intelligence networks in innovation

Abstract

Literature indicates that a number of studies have explored collective intelligence and innovation separately. However, analysis of the links between the two seems to be missing. This study explores the role of collective intelligence networks in innovation. This is done by analysing four firms that use collective intelligence to generate innovative outcomes. The primary analytical methodology is a content analysis of sources that have referenced, discussed or presented research on the firms. In support to this, is a set of quantitative longitudinal statistics related to the firms and triangulated by existing studies in collective intelligence and innovation. Both fields are highly complex grounds and their combination may seem chaotic. However, while it might be impossible to control all the parameters of these multifaceted phenomena, there is support for the fact that key attributes are decisive for obtaining predefined specific outcomes from such complex networks. This study shows that the external input to the network is indeed imperative, as in the case of the external dynamics and influences generated by the firms in the study. The main contribution of this dissertation is in identifying nine key factors that influence the innovation outcome due to collective intelligence. The research also indicates that both the increase as well as the decrease of communication, in specific collective intelligence settings, may facilitate the augmentation of the intelligence factor within an innovation process. This empirically deduced outcome has both pure and applied use within the research and innovation discourse.