Are small world networks always best for innovation?
Tim Kastelle
School of Business, University of Queensland, St Lucia QLD
John Steen
UQ Business School, University of Queensland, St Lucia QLD
PP: 75 - 87
Abstract
It is becoming increasingly apparent that a firm's communication network structure has a significant impact on its innovative capability. We know that in many cases, small world network structures in particular lead to improved innovation output. This paper is the first to test whether or not this finding is also true inside of large project-based firms. We study a project team with 130 members using complex network analysis. The team's project includes several innovations, and the knowledge sharing networks do have small world structures. However, these networks have much more hierarchical structures than those measured in other innovation networks. We conclude that identifying a small world structure is only the first necessary step in analysing such networks. We identify a hierarchical generative mechanism for these structures, which demonstrates that gaining a better understanding of the history and evolution of particular networks is a critical step in analysing them.
Keywords
Innovation output; networks, small world structures; communication networks; complex network analysis; knowledge sharing; network evolution
Article Text
One way of understanding innovation processes is to view innovation as the result of connections. Such connections can be between people, technologies and knowledge and they create the capacity to produce different products and capabilities, as well as create new knowledge. Studying these connections empirically implies a central role for social network analysis. Indeed, advances in network modeling with statistical mechanics and random-graph simulations have created opportunities for innovation researchers to study innovation in novel ways.
Network researchers are fundamentally interested in how the underlying structure of the network affects the successfulness of innovation. Although progress is being made in this area, theory is perhaps moving faster than empirical testing. Intuitively, some network structures such as weak-ties, structural holes should enable actors to find new solutions to problems more easily. While existing work on tie-strength and structural holes, and their relationship with innovation has been somewhat inconclusive, this has not deterred researchers from looking for other structural determinants of innovation.
Since the famous letter experiments of Stanley Milgram, which suggested that anyone in society was linked by a handful of other people, we have had the notion of 'six degrees of separation'. More recently, social scientists have been able to express this phenomenon in terms of a network structure that is quite sparse in connections, yet highly connected in terms of few steps between anyone in the network. Intriguingly, these small world networks appear to be a natural state for most dynamic systems, including neural networks, interlocking boards of directors, and the world trade web.
Logically, small world networks should be supportive of innovation. If there are few steps between actors in the network then it should be possible to transmit knowledge quickly to where it can be most valuable. Also, searching for novel solutions to problems should be relatively easier compared to the situation where very many search steps are required to find an answer. However, while the structure of a network might suggest possibilities for the transmission of knowledge, the governance of interactions and the behavior of actors may complicate the simple relationship between small worlds and innovation. In this paper we examine the small world proposition in the context of an organisation working on a large industrial project. This setting for the research is a test for the small world proposition, and its relationship to innovation, because these expensive and complex projects have highly controlled loci of decision making and tightly governed information flows.
While much research has been focused on the description of small world networks in various organizational settings (e.g. Verspagen and Duysters, 2004) the more difficult task of relating these network structures to innovation performance has received less attention (Schilling and Phelps, 2007). There is some evidence that the relationship between small worlds and innovation may in fact be curvilinear due to some small worldedness enhancing information flows, but too much small worldedness creates information redundancy and reduced novelty (Uzzi and Spiro, 2005). Another study has suggested that the hubs in small world networks may result in information overload for those actors occupying these central positions and thus diminish the capacity of the network to foster new connections between people and ideas (Braha and Bar-Yam, 2007). What these studies tell us is that not all small world networks are good for innovation and it is important to understand how the network is actually functioning before making assumptions about optimal structures.
Our study is the first network characterization of problem-solving and advice networks in a large industrial project. Given the size of the network, we used statistical mechanics to examine dimensions such as path-length, clustering, density and hierarchy. In particular, we examine how organizational structure and governance of the project affects the function of small worlds and problem solving processes.
The paper begins with a brief overview of the small world networks literature and its implications for understanding innovation. We then describe the data collection processes using online surveys of project members. Results from the data analysis are presenting, including degree distribution functions. Discussion of the results and conclusions follow the analysis.
Small world networks - an overview ... continues ...
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