Visualization is key in big data analytics.
Financial network maps are network visualizations of the financial system of emerging industry systems and clusters. The underlying premise is that industries change as the result of regulations, economic dynamics and technological innovation. The result is that new industry segments become integrated in ‘traditional value chains’, particularly as ‘resilience and adaptive investing’ is becoming a trend in economic development.
Our research seeks to understand how network theory can be used to explain bottlenecks in functional cross-sectoral industry ecosystems at high levels of granularity.
- Left: Financial network relationships (nodes and edges) between industry segments engaged in smart mobility. The edges reflect the frequency of financial interactions between the industry segments (nodes) in the industry.
- Right: Identification of anchor (red) and catalyst (blue) industry segments using network theory (centrality and connectivity). Anchor nodes are characterized by limited, high density networks, where catalyst nodes reflect extensive low density networks between various anchors and other catalysts.
(Source: Adriaens and Tahvanainen, 2016; Data: Bloomberg; Visualization: Gephi)
We have focused on transportation/mobility, transactive energy grids, steel industry networks on the Great Lakes to uncover financial relations.
Recent Students and Collaborators
- Dimitris Assanis, PhD, Mechanical Engineering;
- Ryan Moya, SEAS and Ross School of Business
- Antti Tahvanainen, PhD, Finnish Forestry Industry Association, Helsinki, Finland;
- Susan Zielinski, Smart Mobility, UM;
- Robert Hampshire, Professor, Ford School for Public Policy;
- Siqian Chen, Professor, IOE.
- Dennis Sugrue, Ph.D Student (EWRE) and LtCol. US Army