This presentation from the EURO 2016 conference in Poznan, Poland, and from the GDN conference in Bellingham, WA, USA, joint work with Leroy White of Warwick Business School, shows how combining formal and informal organizational networks enables decisions to flow more freely around organizations, but at a cost, leading to an optimal size of informal organizational networks. If organizations can control these, this leads to implications for optimal information flows in companies.
This paper with François Collet of ESADE and Daniela Lup of the LSE analyzes the emergence of the strategic management filed showing the benefits of network brokerage are stronger during the early phase of development and diminish over time.
Through exposure to heterogeneous sources of knowledge, actors who broker between unconnected contacts are more likely to generate valuable output. We contribute to the theory of social capital of brokerage by considering the impact of field maturity. Using longitudinal data from the field of strategic management we find that the benefits of network brokerage are stronger during the early stages of field development and diminish as the field matures. The results of our study call for further research on the interplay between network structures and processes of field emergence.
This paper, published with colleagues from Warwick University and Cambridge University: Petra Vertes, Ruth Nicol, Sandra Chapman, Nicholas Watkins, and Edward Bullmore was the result of inter-disciplinary work funded by the EPSRC – the Engineering and Physical Sciences Research Council (Grant number EP/H02395X/1). We investigated the similarities in the network structure financial markets and brain networks.
Although metaphorical and conceptual connections between the human brain and the financial markets have often been drawn, rigorous physical or mathematical underpinnings of this analogy remain largely unexplored. Here, we apply a statistical and graph theoretic approach to the study of two datasets – the time series of 90 stocks from the New York stock exchange over a 3-year period, and the fMRI-derived time series acquired from 90 brain regions over the course of a 10-min-long functional MRI scan of resting brain function in healthy volunteers. Despite the many obvious substantive differences between these two datasets, graphical analysis demonstrated striking commonalities in terms of global network topological properties.