developing a data-driven graphical platform for assessing and advancing industry cluster development and entrepreneurship opportunities in urban regions : USDOT Region V Regional University Transportation Center final report.
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developing a data-driven graphical platform for assessing and advancing industry cluster development and entrepreneurship opportunities in urban regions : USDOT Region V Regional University Transportation Center final report.

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    • Alternative Title:
      USDOT Region V Regional University Transportation Center final report : technical summary.
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      Across regional economic development leaders and policy makers, the concept of clustering has grown in importance as a framework for structuring economic growth and resurgence (Muro & Katz, 2010). Cluster identification is most often treated as a comparative evaluation through juxtaposition of existing conditions within a boundary area relative to other competing areas (Porter, 1998). A central aim of this project is to develop visualization methods and tools that can inform decision making regarding the nurturing of emerging clusters, and more specifically, to develop visual tools for identifying which components and factors are present or lacking in a region, and which could be developed in order to reengineer, catalyze, or grow a cluster. The project aims to produce visualizations to assist decision-makers is assessing what elements associated with potential New Mobility economic cluster formation are present within a region and which might be absent, constitute an opportunity space for development, and could be assembled around specific initiatives given the right investment and support. To undertake this, the project uses the conceptual framework of scenario planning to position the work as a way to open up new vistas to the future of a region’s economic development from the existing conditions of the region, not merely to diagnose and evaluate existing conditions. Visualization techniques developed through this project include geospatial mapping, historical mapping, relational mapping and combinatory mapping. Potential scenarios associated with the New Mobility economy in Southeast Michigan are utilized to test and explore the application of techniques developed through this project.
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