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A robust nonparametric approach to the analysis of scientific productivity

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  • Andrea Bonaccorsi
  • Cinzia Daraio

Abstract

Data on scientific productivity at institutes of the French INSERM and at biomedical research institutes of the Italian CNR for 1997 were analysed. Available data on human capital input and geographical agglomeration allowed the estimation and comparison of efficiency measures. Nonparametric envelopment techniques were used, and robust nonparametric techniques were applied in this work for the first time for evaluating scientific productivity. They are shown to be useful tools to compute scientific productivity indicators and make institutional comparative analyses. Taking into account a large number of methodological problems, a meaningful and rigorous indirect comparison is made possible. Several possible explanations of the observed differences in productivity are commented on. Copyright , Beech Tree Publishing.

Suggested Citation

  • Andrea Bonaccorsi & Cinzia Daraio, 2003. "A robust nonparametric approach to the analysis of scientific productivity," Research Evaluation, Oxford University Press, vol. 12(1), pages 47-69, April.
    • Handle: RePEc:oup:rseval:v:12:y:2003:i:1:p:47-69
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    Cited by:

    1. Wen-Chi Hung & Ling-Chu Lee & Min-Hua Tsai, 2009. "An international comparison of relative contributions to academic productivity," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 703-718, December.
    2. Daraio, Cinzia & Bonaccorsi, Andrea & Simar, Léopold, 2015. "Efficiency and economies of scale and specialization in European universities: A directional distance approach," Journal of Informetrics, Elsevier, vol. 9(3), pages 430-448.
    3. Crespi, Gustavo A. & Geuna, Aldo, 2008. "An empirical study of scientific production: A cross country analysis, 1981-2002," Research Policy, Elsevier, vol. 37(4), pages 565-579, May.
    4. Chen, Ping-Chuan & Hung, Shiu-Wan, 2016. "An actor-network perspective on evaluating the R&D linking efficiency of innovation ecosystems," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 303-312.
    5. Daniel Chudnovsky & Andrés López & Martín Rossi & Diego Ubfal, 2006. "Evaluating a Program of Public Funding of Scientific Activity. A Case Study of FONCYT in Argentina," OVE Working Papers 1206, Inter-American Development Bank, Office of Evaluation and Oversight (OVE).
    6. Bronwyn Hall & Jacques Mairesse & Laure Turner, 2007. "Identifying Age, Cohort, And Period Effects In Scientific Research Productivity: Discussion And Illustration Using Simulated And Actual Data On French Physicists," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 16(2), pages 159-177.
    7. Mehdi Rhaiem, 2017. "Measurement and determinants of academic research efficiency: a systematic review of the evidence," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 581-615, February.
    8. Lee, Seonghee & Lee, Hakyeon, 2015. "Measuring and comparing the R&D performance of government research institutes: A bottom-up data envelopment analysis approach," Journal of Informetrics, Elsevier, vol. 9(4), pages 942-953.
    9. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2011. "A field-standardized application of DEA to national-scale research assessment of universities," Journal of Informetrics, Elsevier, vol. 5(4), pages 618-628.
    10. Jaehun Park & Joonyoung Kim & Si-Il Sung, 2017. "Performance Evaluation of Research and Business Development: A Case Study of Korean Public Organizations," Sustainability, MDPI, vol. 9(12), pages 1-16, December.
    11. Chen, Kaihua & Kou, Mingting & Fu, Xiaolan, 2018. "Evaluation of multi-period regional R&D efficiency: An application of dynamic DEA to China's regional R&D systems," Omega, Elsevier, vol. 74(C), pages 103-114.
    12. Amy Apon & Linh Ngo & Michael Payne & Paul Wilson, 2015. "Assessing the effect of high performance computing capabilities on academic research output," Empirical Economics, Springer, vol. 48(1), pages 283-312, February.
    13. Alessandro Muscio & Davide Quaglione & Giovanna Vallanti, 2010. "Does Government Research Funding to Universities substitute, Complement or leverage Industry Funding?," Working Papers CELEG 1006, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    14. Ortega, Francisco J. & Gavilan, Jose M., 2013. "The measurement of production efficiency in scientific journals through stochastic frontier analysis models: Application to quantitative economics journals," Journal of Informetrics, Elsevier, vol. 7(4), pages 959-965.
    15. Chen Kaihua & Kou Mingting, 2014. "Staged efficiency and its determinants of regional innovation systems: a two-step analytical procedure," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 52(2), pages 627-657, March.
    16. Mehdi Rhaiem & Nabil Amara, 2020. "Determinants of research efficiency in Canadian business schools: evidence from scholar-level data," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 53-99, October.
    17. Gustavo Crespi & Aldo Geuna, 2005. "Modelling and Measuring Scientific Production: Results for a Panel of OECD Countries," SPRU Working Paper Series 133, SPRU - Science Policy Research Unit, University of Sussex Business School.
    18. Giovanni Abramo & Ciriaco Andrea D’Angelo & Fabio Pugini, 2008. "The measurement of Italian universities’ research productivity by a non parametric-bibliometric methodology," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(2), pages 225-244, August.
    19. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Di Costa, 2014. "Variability of research performance across disciplines within universities in non-competitive higher education systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 777-795, February.
    20. Gavilan, José M. & Ortega, Francisco J., 2020. "Productive efficiency analysis of quantitative economics journals through Stochastic Frontier Analysis using panel data || Análisis de eficiencia productiva de revistas de economía cuantitativa a trav," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 30(1), pages 297-311, December.

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