Gaps remain in our understanding of how different combinations of business, technology and relationship strategies influence the growth of small and medium-size enterprises (SMEs), especially in the context of networked interactions by SMEs at regional, extra-regional, and sectoral levels. In each new round of economic and technological development, these strategies evolve, highlighting the importance of tracking in close to real-time the nuances of emerging enterprise strategies. In this project, we will probe differential strategies for SME growth and the role of regional clustering in the growth of innovative companies, building on new and unobtrusive methods of web mining to gain timely information about enterprise developmental pathways. Three key research questions will be addressed: (1) What differentiates the business strategies, technology pathways, and relationships of innovative companies that stay in business and grow? (2) How does regional clustering influence the business strategies, technology pathways, and relationships of innovative companies that stay in business and grow? (3) What are the contributions of policy-induced resources in supporting innovative companies that stay in business and grow? These questions will be probed through a mixed-methods approach using both quantitative and qualitative data. We focus our research on the emerging green goods sector (GGS) - comprising firms producing outputs that benefit the environment or conserve natural resources, with an international comparative element involving the UK, the US, and China. We will identify 300 GGS companies in each country established during the time period 2004-2007, for a total study sample of 900 companies. We will apply a stratified sample selection procedure, to match the distribution of the UK GGS sector by broad product classes with the US and Chinese GGS sectors. We will then combine structured and unstructured data sources to track the origins, business, technology, and relationship strategies, and performance outcomes of these firms through to 2011. Structured data will include corporate databases, corporate patents and publication records. Unstructured data will be derived from new methods of web-scraping and data mining the current and archived web-sites of the sample enterprises. Survival analysis will indicate the pathway of firms from the founding period through to the current period. Hierarchical cluster analysis will be applied to explore differential business strategies by the three countries and by types of metropolitan location and product class. Multivariate regression will relationships between high growth (and other) outcomes and business strategies, technological approach, and the role of regional relationships and policy instruments, controlling for country and other factors. Insights from US and Chinese enterprise growth strategies will be compared with those of UK firms. In the subsequent phase, we will undertake case studies with selected UK enterprises, to test and refine propositions about differential strategies, regional and policy interactions, and outcomes. Interviews (60) will be conducted with high growth firms, stable firms, and other key informants in five UK metropolitan areas. The interviews will examine what differentiates the most successful firms, trace the use and benefit of technology-related and other programmes, and probe for wider policy-related locational attractiveness. The project will be led by the University Manchester in partnership with Experian UK, Georgia Institute of Technology (US), and Beijing Institute of Technology (China). An active dissemination and engagement programme will be pursued with the academic and non-academic worlds, including mechanisms for advanced training and outreach to users in the business sector, including start-up firms and business support programmes, to university and other technology transfer managers, and to local and national policymakers.