Grenoble–GIANT Territorial Innovation Models

Laurent Scaringella () and Jean-Jacques Chanaron ()
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Laurent Scaringella: ESC Rennes School of Business - ESC [Rennes] - ESC Rennes School of Business
Jean-Jacques Chanaron: EESC-GEM Grenoble Ecole de Management, CNRS - Centre National de la Recherche Scientifique

Grenoble Ecole de Management (Post-Print) from HAL

Abstract: Over the past decades, the EU heavily invested in Research Infrastructures (RI). What are the expected returns of such investments? In the present article we address the question of returns on public funds/public infrastructures. We consider the role of RI and universities from an economic, social, and entrepreneurial perspective from various Territorial Innovation Models (TIMs): Italian industrial districts, innovative milieus, regional innovation systems, new industrial spaces, and regional clusters. We conducted our empirical study on Grenoble Isère Alpes Nanotechnologies (GIANT), which is composed of large scientific instruments, universities, and engineering and management schools. Our microeconomic methodology measured the socioeconomic and entrepreneurial effects of GIANT with respect to budget, employment, and spin-off generation. We contribute to the existing body of knowledge on TIMs by comparing the long-term investments to the generation of wealth, the creation of employment, and the development of start-ups; adding new insights to the debate opposing positive and negative impacts empirical studies; and offering recommendations for the use of public resources. In our discussion, we compare the GIANT model as a very localized RI-university club to the Grenoble model as localized cluster.

Keywords: Return on investment; Socioeconomic impact; Start-up; University; Research infrastructure; Territorial Innovation Models (search for similar items in EconPapers)
Date: 2016-05-26
New Economics Papers: this item is included in nep-cse, nep-ent, nep-eur, nep-geo, nep-ino, nep-sbm and nep-ure
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Published in Technological Forecasting and Social Change, 2016, 112, pp. 92-101. ⟨10.1016/j.techfore.2016.05.026⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:gemptp:hal-01472878

DOI: 10.1016/j.techfore.2016.05.026

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