Search

Although technology innovation management has been extensively studied, little research has been conducted in nanotechnology-focused innovation management. No model currently exists on nanotechnology innovation management and the related critical success factors. Based on a literature review of nanotechnology characteristics and reported successful nanotechnology research, six essential factors of success were identified. These factors are consumer acceptance of nanotechnology, hybridisation of nanotechnology innovations into existing industries and markets, multidisciplinary project teams, agglomeration and clustering of nanotechnology research projects, research and development (R&D) and commercialisation skills and capabilities, and working within a conducive innovation environment. These six factors were crystallised into the "Nanotechnology Innovation Diamond", a model for successful nanoscience research and development. The proposed model was then validated using confirmatory factor analysis (CFA) from a survey of 167 nanotechnology experts from South Africa. The results indicate that at 95% confidence level, the proposed model satisfied the minimum CFA model fit requirements, and the six proposed critical success factors are significant for successful nanotechnology R&D. The presented model can be used to increase the rate of success of nanotechnology R&D projects, nanotechnology project portfolio selection, and nanotechnology foresight exercises. [ABSTRACT FROM AUTHOR]

Where firms cluster together, there are efficiency gains from outsourcing, labour pooling and knowledge spillovers. Earlier research into agglomeration in South Africa focussed on sub-national regions and found that capital stock, human capital, access to markets and exports are significant determinants of output growth. This paper examines whether location explains differences in efficiency at firm level. Data from the 2003 and 2007 World Bank Enterprise Surveys allow one to examine firms in the four major South African cities. This paper reports estimates of a firm-level production function that incorporates location-specific explanatory variables to examine the scope of agglomeration economies. The place-specific size of the home market, level of education and share of exports are found to be positively related to output per worker at firm level. A description of the survey data identifies possible indicators of the sources of agglomeration economies. The size and significance of the inland Gauteng Province's economy is reflected in its firms' use of intermediate inputs and skilled labour. [ABSTRACT FROM AUTHOR]