Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/202674 
Erscheinungsjahr: 
2017
Schriftenreihe/Nr.: 
Birmingham Business School Discussion Paper Series No. 2017-01
Verlag: 
University of Birmingham, Birmingham Business School, Birmingham
Zusammenfassung: 
Innovative, high-technology activities are seen as motors of development, with knock-on effects throughout their local economies. Such activities tend to organise networks that span beyond atomized firms, creating 'ecosystems' of mutual dependence as well as competition. However, such ecosystems remain poorly understood, which in turn constrains the effectiveness of any policy response. This first-steps paper uses the unique, user-generated Crunchbase dataset to fill some of these gaps. With rich information on founders, workers, products and early stage investment activity, Crunchbase has great potential for ecosystem understanding. Like many 'big data' resources, however, Crunchbase requires cleaning and validation to make it suitable for robust analysis. We develop a novel approach to gapfill location data in Crunchbase, exploiting DNS/IP address information, and run a series of tests on a raw sample of 225,000 company-level observations covering the US, UK and Canada. We provide initial descriptive results, and set out steps for further research.
Schlagwörter: 
cities
clusters
technology
innovation ecosystems
big data
Crunchbase
URL der Erstveröffentlichung: 
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Dokumentart: 
Working Paper

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