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 development at enterprise, regional and national levels. The project is led by the Manchester Institute of Innovation Research at the University of Manchester, in collaboration with Georgia Institute of Technology, US; Beijing Institute of Technology, China, and Experian, UK.

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