This paper presents the results of research to develop new data sources and methods that can be combined with existing information for real-time intelligence to understand and map enterprise development and commercialisation in a rapidly emerging and growing new technology.As a demonstration case, the study examines enterprise development and commercialisation strategies in graphene, focusing on a set of 65 graphene-based small and medium-sized enterprises located in 16 different countries.We draw on available secondary sources and bibliometric methods to profile developments in graphene. We then use computerised data mining methods and analytical techniques, including cluster and regression modelling, to identify patterns from publicly available online information on enterprise web sites. We identify groups of graphene small and medium-sized enterprises differentiated by how they became involved with graphene, the materials they target, whether they make equipment, and their orientation towards science and intellectual property.In general, access to finance and the firms’ location are significant factors that are associated with graphene product introductions. We also find that patents and scientific publications are not statistically significant predictors of product development in our sample of graphene SMEs. We show that the UK has a cohort of graphene-oriented SMEs that is signalling plans to develop intermediate graphene products that should have higher value in the marketplace.Our findings suggest that UK policy needs to ensure attention to the introduction and scale-up of downstream intermediate and final graphene products and associated financial, intermediary, and market identification support.
|Number of pages||51|
|Publication status||Published - Aug 2015|
- emerging technology
- small and medium-sized enterprise
- data mining