LUCERNA · New light on innovation data, for enhancing regional competitive advantage

Final Activity Report Summary - LUCERNA (New light on innovation data, for enhancing regional competitive advantage)

Ireland achieved significant economic growth over two decades until recently that has been characterised by rising high-tech exports and knowledge-based employment. This growth was driven primarily by the presence of foreign-owned multinational corporations in high-tech sectors and its sustainability has always remained a basis for debate. Despite recession high-tech capabilities were embedded in the Irish industrial system. A deeper understanding of industrial change and the technological capabilities that now underscore the Irish economy at present is essential. The Government has ambitious plans for moving toward the 'smart economy' with high levels of R&D. But does the Government have partners in the private sector in the form of fast growing companies with the organisational and technological capabilities to drive growth and create tens of thousands of jobs? While many Irish government reports describe the post Celtic Tiger growth challenge and set ambitious targets for employment growth in new sectors (such as renewable energy) and increased private sector R&D, they suffer from a common weakness: very little 'coalface' data on business organisation including evolving production and technological capabilities. Industrial policymaking, as well as academic research in Ireland is largely conducted in the dark with respect to disaggregated, internationally comparative, company-level data on indicators of production and technological capabilities. This Marie Curie ToK project, LUCERNA -Latin for 'lamp' - drew on the experience and advice of researchers at the Centre for Industrial Competitiveness (CIC) at UMass Lowell. The project was led by Prof Michael Best of CIC. Essentially, knowledge of how to replicate a study of the Massachusetts industrial region through database creation and novel data mining was transferred to the CISC research team. A consistent methodology was developed so that key high-tech industry clusters did not overlap and were mutually exclusive in terms of data. Each year the data can be updated so that emerging trends can be anticipated and benchmarked internationally. Thus the Lucerna database methodology provides a general framework for investigating and understanding the evolving Irish knowledge economy. There were four principal objectives for the LUCERNA Transfer of Knowledge project. These are: 1. To enhance the awareness of CISC researchers of conceptual frameworks for innovation data analysis. 2. To build up the capacity of CISC researchers to implement coherent data gathering strategies in the challenging domain of product innovation. 3. To generate a new capacity for CISC in using innovative data gathering and dissemination technologies. 4. To enhance the capacity of CISC to undertake innovative analytical and interpretative exercises on the data. The project addressed crucial policy questions such as whether the capabilities are in place in Irish industry to allow a transition to a new business model based on endogenous development; whether there is potential for an enhancement of these capabilities through technological convergence that occurs at the intersection of two or more of the technology-based clusters that presently exist; whether expanded funding of HEI research can be an engine of high-tech growth; and whether new sectors can have large employment impact. The project work was conducted in three principal and mostly sequential phases: (1) construction of the Lucerna databasa of high-tech companies, classification into clusters, and data cleansing; (2) data analysis and (3) dissemination. Training was delivered by the incoming researchers in all three phases and the outgoing researchers were trained at the University of Massachusetts where an equivalent database was constructed.

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