Governments around the world want to develop their ICT industries. Researchers and policymakers thus need a clear picture of digital businesses, but conventional datasets and typologies tend to lag real-world change. We use innovative 'big data' resources to perform an alternative analysis for all active companies in the UK, focusing on ICT-producing firms. Exploiting a combination of observed and modelled variables, we develop a novel 'sector-product' approach and use text mining to provide further detail on key sector-product cells. We find that the ICT production space is around 42% larger than SIC-based estimates, with around 70,000 more companies. We also find ICT employment shares over double the conventional estimates, although this result is more speculative. Our findings are robust to various scope, selection and sample construction challenges. We use our experiences to reflect on the broader pros and cons of frontier data use.

Mapping digital businesses with big data: Some early findings from the UK / M. Nathan, A.C. Rosso. - In: RESEARCH POLICY. - ISSN 0048-7333. - 44:9(2015 Nov), pp. 1714-1733. [10.1016/j.respol.2015.01.008]

Mapping digital businesses with big data: Some early findings from the UK

A.C. Rosso
Ultimo
2015

Abstract

Governments around the world want to develop their ICT industries. Researchers and policymakers thus need a clear picture of digital businesses, but conventional datasets and typologies tend to lag real-world change. We use innovative 'big data' resources to perform an alternative analysis for all active companies in the UK, focusing on ICT-producing firms. Exploiting a combination of observed and modelled variables, we develop a novel 'sector-product' approach and use text mining to provide further detail on key sector-product cells. We find that the ICT production space is around 42% larger than SIC-based estimates, with around 70,000 more companies. We also find ICT employment shares over double the conventional estimates, although this result is more speculative. Our findings are robust to various scope, selection and sample construction challenges. We use our experiences to reflect on the broader pros and cons of frontier data use.
Big Data; Digital economy; Firm-level analysis; ICTs; Industrial policy; Text mining; Strategy and Management1409 Tourism, Leisure and Hospitality Management; Management Science and Operations Research; Management of Technology and Innovation
Settore SECS-P/01 - Economia Politica
Settore SECS-P/02 - Politica Economica
Settore SECS-P/06 - Economia Applicata
nov-2015
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/613856
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