How do Innovators Network? – The Innovation Capacity of Potentially Strong Ties in Individuals’ Social Networks

Abstract

In a world of rapid change and global competition, innovation is the key to success – for individual professionals as much as for organisations. At the same time, social network platforms enable professionals to develop and maintain large social networks.

However, extant social network research provides inconsistent views on innovators' social networks. Furthermore, the main research stream assumes network structure as a predictor of innovativeness, in contrast to this study's research aim – to understand how innovators network, and why so. Still, extant research allows the deduction of ten hypotheses and two theoretical models – the first addressing innovativeness and the second innovator's social networks.

Accordingly, the first of two case studies investigates how an individual's social network topology predicts innovativeness. The second case study examines how an innovator's social network topology differs from that of an adaptor, a person low in innovativeness. In addition, interviews of the ten most innovative persons per case study reveal relational networking preferences of innovators, and how those preferences are related to an innovator's human agency.

In contrast to extant research, the data suggest that, within a given social network, adaptors have access to more structural holes than innovators. In addition, innovators thrive in dense networks and actively connect different parts of their social networks, thus eliminating structural holes. Those findings contrast research assuming that brokerage across structural holes is based on gatekeeping and information flow control. However, the findings resonate with recent research on firms, innovation facilitators and entrepreneurs, who are most innovative when having access to diverse, dense network clusters.

In order to make sense of the innovators' social network topologies and their relational preferences, I propose the potentially strong tie concept. Although innovators' large networks are dense, most of their ties are weak and thus require little maintenance effort. However, due to the combination of local density, social network platform based transparency, and the innovators' preference for real-life relationships, most of their ties are potentially strong. Such ties can be strengthened quickly and efficiently, which constitutes a capacity for innovation.

Among this study's theoretical contributions are a dynamic model of innovators' social networking, a description of innovators' human agency, predictors of innovativeness, and the potentially strong tie concept. The study also suggests that innovators create the social networks that constrain adaptors.