Industrial clusters help firms and workers become more productive, so are of great interest to researchers and policymakers. However, exploring and analyzing such clusters is challenging. Big data and data-driven approaches can help. We study the emerging digital sector using big data obtained from administrative datasets but also from data science routines to develop modelled firm variables and firms’ activities. These matched datasets allow us to have new insights on the importance of digital technology sectors in the United Kingdom, their structure and their co-location patterns.

Exploring digital technology industry clusters using administrative and frontier data / M. Nathan, A. Rosso (ROUTLEDGE ADVANCES IN REGIONAL ECONOMICS, SCIENCE AND POLICY). - In: Big Data for Regional Science / [a cura di] L.A Schintler, Z. Chen. - Prima edizione. - [s.l] : Routledge, 2017. - ISBN 9781351983266. - pp. 143-152

Exploring digital technology industry clusters using administrative and frontier data

A. Rosso
2017

Abstract

Industrial clusters help firms and workers become more productive, so are of great interest to researchers and policymakers. However, exploring and analyzing such clusters is challenging. Big data and data-driven approaches can help. We study the emerging digital sector using big data obtained from administrative datasets but also from data science routines to develop modelled firm variables and firms’ activities. These matched datasets allow us to have new insights on the importance of digital technology sectors in the United Kingdom, their structure and their co-location patterns.
ICT; clusters; agglomeration; innovation; big data; data science
Settore SECS-P/01 - Economia Politica
Settore SECS-P/02 - Politica Economica
Settore SECS-P/06 - Economia Applicata
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/613903
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