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 Friday, 05 November 2010 – Written by Giovanni Bert   

PICK ME Project (Extended Abstract)


The ongoing global economic crisis is seriously challenging advanced capitalistic economies. In the last year the Gross Domestic Product (GDP) has fallen at dramatic rates, creating the conditions for the upsurge of unemployment, above all in areas characterized by specialization in mature industries. In the Keynesian tradition, short run policies to cope with this kind of cyclical fluctuations consists in a generic sustain to aggregate demand, both through direct government procurement and through measures aimed at increasing available income for private customers. Such measures are by definition mainly designed to help economic systems to cope with short run shocks and do not allow to undertake a long run sustained path of growth.


According to recent growth models and empirical evidence, innovation and knowledge creation represent the main factors able to affect the competitiveness and the long run perspective of growth of countries. However, innovation and technology policies have mainly been designed by relying on a supply side perspective. One may imagine the creation of technological knowledge as an outcome of a peculiar production process in which knowledge already available, stemming from past R&D activities, and R&D personnel represent the main inputs. In view of this, technology policies have mainly focused in contributing the creation of knowledge by providing funds to carry out R&D activities and by enhancing education and training for researchers.


However, a recent debate has recently emerged, about the need for grafting innovation and technology policies in a demand-oriented framework. The aim of this project is to provide an original contribution to the ongoing debate, advancing the understanding of the mechanisms through which demand-based innovation policies may stimulate effective knowledge creation process, and eventually trigger competitiveness and productivity growth.


To this purpose, the research activity will consist of both theoretical models and empirical analyses, the results of which should be able to inform the policy design process. We shall distinguish between public and private demand for both final and intermediate goods and services and will analyze their effects on the generation, diffusion and exploitation of technological knowledge. The research will be articulated on different dimension. Particular emphasis will be given to the geographical dimension of innovation activities, and therefore of innovation policies. The dynamics of local demand for particular technologies may have indeed sound effects on local competitiveness and influence firms' location choices, generating positive feedbacks stemming from increasing clustering of innovation activities. Moreover, innovations is likely to come out of an interactive process involving a number of connected actors operating in local contexts. In this direction, the dynamics originated by demand-side policies are likely to affect the architecture of the structure of local networks of innovators. Besides this, the link with industrial and technology lifecycle should be able to emphasize the positive effects that channelling demand may have on areas locked into mature industries-technologies. The evolution of demand will eventually be linked to the evolution of technologies and to the evolution of the structure of the knowledge base in different knowledge intensive sectors. However, we will not claim that the boosting of demand for particular technologies is a sufficient condition for such technologies to be improved and diffused. A number of context conditions need to be realized, like the focus of education and training on the complementary skills (universities and labor market), the development of upstream industries able to provide complementary goods, technologies and knowledge (specialized suppliers, research labs) the creation of support services, as well as a balance between market power and competition in the different development stages of technologies.


The research activity will be conducted by pursuing a great deal of multidisciplinarity, derived by the need to gain a deep understanding of the different contexts and sectors that will be analyzed, as well as by the different dimensions in which the project is articulated. The data used to analyze the relationships between demand, innovation and growth, will be partly drawn by existing databases and partly collected by the different partners operating in the different partners by means of surveys explicitly designed to gather together information susceptible of comparative analysis. Given the wide scope of the project, a number of diverse methodologies will be used to carry out empirical investigation and to implement theoretical models, ranging from traditional econometric techniques, to social network analysis and content analysis based on linguistic engineering softwares applied to patents and publications, as well as simulation techniques.


The results of the analyses conducted at different levels, and through different methodologies, will in turn provide the basis upon which taxonomy of demand-oriented technology policies may be elaborated, whereby public procurement and sustain to private demand are strictly intertwined with sectoral, regional and institutional specificities of innovation activities, as well as with their inherent cyclical behaviour.


Keywords: demand-driven innovation policy, knowledge structure, agglomeration, networks, education, university-industry links, technology lifecycle.

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Last Updated on Wednesday, 08 June 2011 09:59