Summary information

Study title

Sustaining growth for innovative new enterprises: UK firm data

Creator

Sensier, M, University of Manchester
Gök , A, University of Manchester
Shapira, P, University of Manchester

Study number / PID

851779 (UKDA)

10.5255/UKDA-SN-851779 (DOI)

Data access

Restricted

Series

Not available

Abstract

To select the group of UK firms we initially searched in the FAME database (available from the University of Manchester Library) with keywords relating to the green goods sector, please see the publication Shapira, et al (2014, in Technological Forecasting & Social Change, vol. 85, pp. 93-104) for further details on the keywords. This database contains anonymized firm data from a sample of UK firms in the green goods production industry. We combine data from structured sources (the FAME database, patents and publications) with unstructured data mined from firm's web-sites by saving key words in text and summing up counts of these to create additional explanatory variables for firm growth. The data is in a panel from 2003-2012 with some observations missing for firms. We collect historical data from firm's web-sites available in an archive from the Wayback machine.This project probes the growth strategies of innovative small and medium-size enterprises (SMEs). Our research focuses on emerging green goods industries that manufacture outputs which benefit the environment or conserve natural resources, with an international comparative element involving the UK, the US, and China. The project investigates the contributions of strategy, resources and relationships to how innovative British, American, and Chinese SMEs achieve significant growth. The targeted technology-oriented green goods sectors are strategically important to environmental rebalancing and have significant potential (in the UK) for export growth. The research examines the diverse pathways to innovation and growth across different regions. We use a mix of methodologies, including analyses of structured and unstructured data on SME business and technology performance and strategies, case studies, and modelling. Novel approaches using web mining are pioneered to gain timely information about enterprise developmental pathways. Findings from the project will be used to inform management and policy...
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Methodology

Data collection period

01/01/2012 - 31/12/2014

Country

United Kingdom

Time dimension

Not available

Analysis unit

Organization

Universe

Not available

Sampling procedure

Not available

Kind of data

Numeric
Text

Data collection mode

We collected the financial information on the UK firms by downloading Companies House data from the FAME database available through the University of Manchester Library (see http://www.library.manchester.ac.uk/searchresources/databases/f/). Grant information on companies came from the Technology Strategy Board. Patent information was from the Derwent database and publication information was from the Web of Science. The Consumer Price index was from the Office for National Statistics (http://www.ons.gov.uk/ons/rel/cpi/consumer-price-indices/index.html). The Human Resources in Science and Technology variable was from the Eurostat database (http://ec.europa.eu/eurostat/data/database).Unstructured data was mined from firm's web-sites. The UK Intellectual Property Office has clarified that the data mining we are doing and the way we are doing it is permissible. See: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/375954/Research.pdf

Funding information

Grant number

ES/J008303/1

Access

Publisher

UK Data Service

Publication year

2015

Terms of data access

Not available

Related publications

Not available