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Exploring the relationship between university and innovation: evidence from the Italian food industry

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  • Paola Cardamone
  • Valeria Pupo
  • Fernanda Ricotta

Abstract

This study provides empirical evidence on the role of universities’ technological transfer (TT) activities in the Italian manufacturing sector, with particular attention to the food industry. Using the UniCredit-Capitalia database (2008) for firms and data from the Ministry of Education, University and Research (MIUR) to obtain the university TT indicator, we estimate a probit model to assess the effect of universities’ TT activities on a firm’s likelihood to innovate. The role of proximity in knowledge spillovers from TT activities is also investigated. Results show that university TT activities seem to stimulate food industry firms innovation and the impact appears significantly higher than for the manufacturing sector. Moreover, the effect of TT activities on innovation appears to be geographically bounded. As regards policy implications, this study provides two insights which may help promote innovation in the food sector. First, the factors that influence innovative capability in the food sector are different from those in other sectors, suggesting the need for sector specific instruments for promoting innovation. Second, science is important in the food industry and this raises questions about the policy of mainly considering high-tech industries when promoting a closer relationship between firms and universities.

Suggested Citation

  • Paola Cardamone & Valeria Pupo & Fernanda Ricotta, 2018. "Exploring the relationship between university and innovation: evidence from the Italian food industry," International Review of Applied Economics, Taylor & Francis Journals, vol. 32(5), pages 673-696, September.
    • Handle: RePEc:taf:irapec:v:32:y:2018:i:5:p:673-696
    DOI: 10.1080/02692171.2017.1357681
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    Cited by:

    1. Enzo Valentini & Fabiano Compagnucci & Mauro Gallegati & Andrea Gentili, 2023. "Robotization, employment, and income: regional asymmetries and long-run policies in the Euro area," Journal of Evolutionary Economics, Springer, vol. 33(3), pages 737-771, July.
    2. Enrique Acebo & José-Ángel Miguel-Dávila & Mariano Nieto, 2021. "The Impact of University–Industry Relationships on Firms’ Performance: A Meta-Regression Analysis," Science and Public Policy, Oxford University Press, vol. 48(2), pages 276-293.

    More about this item

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis

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