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Evaluating research efficiency within National R&D Programmes

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  • Jiménez-Sáez, Fernando
  • Zabala-Iturriagagoitia, Jon Mikel
  • Zofío, José L.
  • Castro-Martínez, Elena

Abstract

Relying on efficiency analysis, we evaluate to what extent policy makers have been able to promote the establishment of consolidated and comprehensive research groups to contribute to the implementation of a successful innovation system for the Spanish food technology sector, oriented to the production of knowledge based on an application model. Using data envelopment analysis techniques that allow calculation of a generalized version of the traditional distance function model for productive efficiency, we find pervasive levels of inefficiency and a typology of different research strategies. Among these, in contrast to what has been assumed, established groups do not play the pre-eminent benchmarking role; rather, partially oriented, specialized and "shooting star" groups are the most common patterns. These results correspond with an infant innovation system, where the fostering of higher levels of efficiency and the promotion of the desired research patterns are ongoing.

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  • Jiménez-Sáez, Fernando & Zabala-Iturriagagoitia, Jon Mikel & Zofío, José L. & Castro-Martínez, Elena, 2011. "Evaluating research efficiency within National R&D Programmes," Research Policy, Elsevier, vol. 40(2), pages 230-241, March.
    • Handle: RePEc:eee:respol:v:40:y:2011:i:2:p:230-241
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    2. Jiménez-Sáez, Fernando & Zabala, Jon Mikel & Zofío, José L., 2010. "Who leads Research Productivity Change? Guidelines for R&D policy makers," Papers in Innovation Studies 2010/10, Lund University, CIRCLE - Centre for Innovation Research.
    3. Vincent Mangematin & Paul O’Reilly & James Cunningham, 2014. "PIs as boundary spanners, science and market shapers," The Journal of Technology Transfer, Springer, vol. 39(1), pages 1-10, February.
    4. Hung, Chia-Liang, 2017. "Social networks, technology ties, and gatekeeper functionality: Implications for the performance management of R&D projects," Research Policy, Elsevier, vol. 46(1), pages 305-315.
    5. Ibrahim Alnafrah, 2021. "Efficiency evaluation of BRICS’s national innovation systems based on bias-corrected network data envelopment analysis," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-28, December.
    6. Marta Foddi & Stefano Usai, 2013. "Regional Knowledge Performance in Europe," Growth and Change, Wiley Blackwell, vol. 44(2), pages 258-286, June.
    7. Sung-Seok Ko & Namuk Ko & Doyeon Kim & Hyunseok Park & Janghyeok Yoon, 2014. "Analyzing technology impact networks for R&D planning using patents: combined application of network approaches," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 917-936, October.
    8. Fernando Gascón & Jesús Lozano & Borja Ponte & David Fuente, 2017. "Measuring the efficiency of large pharmaceutical companies: an industry analysis," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(5), pages 587-608, June.
    9. Bai, Xue-Jie & Li, Zhen-Yang & Zeng, Jin, 2020. "Performance evaluation of China's innovation during the industry-university-research collaboration process—an analysis basis on the dynamic network slacks-based measurement model," Technology in Society, Elsevier, vol. 62(C).
    10. Fernando Jiménez-Sáez & Jon Mikel Zabala-Iturriagagoitia & Jose Luis Zofío, 2013. "Who leads research productivity growth? Guidelines for R&D policy-makers," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 273-303, January.
    11. M. Foddi & S. Usai, 2012. "Regional innovation performance in Europe," Working Paper CRENoS 201221, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

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