IDEAS home Printed from https://ideas.repec.org/a/eee/respol/v34y2005i4p495-516.html
   My bibliography  Save this article

On research efficiency: A micro-analysis of Dutch university research in Economics and Business Management

Author

Listed:
  • Cherchye, L.
  • Abeele, P. Vanden

Abstract

We argue that efficiency assessments of academic research should focus on micro-units of research production rather than on conventionally employed (aggregated) macro-units, and show that such a detailed analysis of research performance provides interesting insights. In addition, we propose a non-parametric methodology that is specially tailored for analyzing the productive efficiency of research: it starts from a specification of the managerial objectives of research activities while imposing minimal structure on the (typically unknown) production technology. We illustrate our points by assessing the productive efficiency of research in Economics and Business Management faculties at Dutch universities. Next to measuring productive efficiency, we look for specific patterns in efficiency distributions over universities, years and areas of specialization. In addition, we investigate the impact of external funding and of the size of research programs on academic research efficiency.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Cherchye, L. & Abeele, P. Vanden, 2005. "On research efficiency: A micro-analysis of Dutch university research in Economics and Business Management," Research Policy, Elsevier, vol. 34(4), pages 495-516, May.
  • Handle: RePEc:eee:respol:v:34:y:2005:i:4:p:495-516
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0048-7333(05)00057-0
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    2. Kalaitzidakis, Pantelis & Mamuneas, Theofanis P. & Savvides, Andreas & Stengos, Thanasis, 2004. "Research spillovers among European and North-American economics departments," Economics of Education Review, Elsevier, vol. 23(2), pages 191-202, April.
    3. Afriat, Sidney N, 1972. "Efficiency Estimation of Production Function," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 13(3), pages 568-598, October.
    4. Kocher, Martin G. & Luptacik, Mikulas & Sutter, Matthias, 2006. "Measuring productivity of research in economics: A cross-country study using DEA," Socio-Economic Planning Sciences, Elsevier, vol. 40(4), pages 314-332, December.
    5. Cordero, Rene, 1990. "The measurement of innovation performance in the firm: An overview," Research Policy, Elsevier, vol. 19(2), pages 185-192, April.
    6. Jerry G. Thursby, 2000. "What Do We Say about Ourselves and What Does It Mean? Yet Another Look at Economics Department Research," Journal of Economic Literature, American Economic Association, vol. 38(2), pages 383-404, June.
    7. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    8. John R. Hauser, 1998. "Research, Development, and Engineering Metrics," Management Science, INFORMS, vol. 44(12-Part-1), pages 1670-1689, December.
    9. Peter Bogetoft, 1996. "DEA on Relaxed Convexity Assumptions," Management Science, INFORMS, vol. 42(3), pages 457-465, March.
    10. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
    11. Varian, Hal R., 1990. "Goodness-of-fit in optimizing models," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 125-140.
    12. Rajiv D. Banker, 1993. "Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation," Management Science, INFORMS, vol. 39(10), pages 1265-1273, October.
    13. Graves, Philip E & Marchand, James R & Thompson, Randal, 1982. "Economics Departmental Rankings: Research Incentives, Constraints, and Efficiency," American Economic Review, American Economic Association, vol. 72(5), pages 1131-1141, December.
    14. Korhonen, Pekka & Tainio, Risto & Wallenius, Jyrki, 2001. "Value efficiency analysis of academic research," European Journal of Operational Research, Elsevier, vol. 130(1), pages 121-132, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Laurens Cherchye & Bram De Rock & Frederic Vermeulen, 2008. "Analyzing Cost-Efficient Production Behavior Under Economies of Scope: A Nonparametric Methodology," Operations Research, INFORMS, vol. 56(1), pages 204-221, February.
    2. Valentin Zelenyuk, 2019. "Data Envelopment Analysis and Business Analytics: The Big Data Challenges and Some Solutions," CEPA Working Papers Series WP072019, School of Economics, University of Queensland, Australia.
    3. Cherchye, Laurens & Van Puyenbroeck, Tom, 2007. "Profit efficiency analysis under limited information with an application to German farm types," Omega, Elsevier, vol. 35(3), pages 335-349, June.
    4. 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.
    5. Santiago Herrera & Gaobo Pang, 2008. "Eficiency of Infrastructure: The Case of Container Ports," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 9(1), pages 165-194.
    6. Forsund, Finn R. & Sarafoglou, Nikias, 2005. "The tale of two research communities: The diffusion of research on productive efficiency," International Journal of Production Economics, Elsevier, vol. 98(1), pages 17-40, October.
    7. Nadia M. Guerrero & Juan Aparicio & Daniel Valero-Carreras, 2022. "Combining Data Envelopment Analysis and Machine Learning," Mathematics, MDPI, vol. 10(6), pages 1-22, March.
    8. Santiago Herrera & Gaobo Pang, 2006. "How Efficient is Public Spending in Education?," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 24(51), pages 136-201, June.
    9. Cristian Barra & Roberto Zotti, 2016. "Measuring Efficiency in Higher Education: An Empirical Study Using a Bootstrapped Data Envelopment Analysis," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 22(1), pages 11-33, February.
    10. George E. Halkos & Nickolaos G. Tzeremes & Stavros A. Kourtzidis, 2010. "An application of statistical interference in DEA models: An analysis of public owned university departments' efficiency," EERI Research Paper Series EERI_RP_2010_17, Economics and Econometrics Research Institute (EERI), Brussels.
    11. Fulvio Castellacci & Jinghai Zheng, 2010. "Technological regimes, Schumpeterian patterns of innovation and firm-level productivity growth," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 19(6), pages 1829-1865, December.
    12. Kuosmanen, Timo & Post, Thierry & Scholtes, Stefan, 2007. "Non-parametric tests of productive efficiency with errors-in-variables," Journal of Econometrics, Elsevier, vol. 136(1), pages 131-162, January.
    13. Léopold Simar & Paul W. Wilson, 2015. "Statistical Approaches for Non-parametric Frontier Models: A Guided Tour," International Statistical Review, International Statistical Institute, vol. 83(1), pages 77-110, April.
    14. repec:bdr:ensayo:v::y:2006:i:51:p:136-201 is not listed on IDEAS
    15. Kristof De Witte & Laura López-Torres, 2017. "Efficiency in education: a review of literature and a way forward," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 339-363, April.
    16. C. Lovell & Shawna Grosskopf & Eduardo Ley & Jesús Pastor & Diego Prior & Philippe Eeckaut, 1994. "Linear programming approaches to the measurement and analysis of productive efficiency," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 2(2), pages 175-248, December.
    17. Valero-Carreras, Daniel & Aparicio, Juan & Guerrero, Nadia M., 2021. "Support vector frontiers: A new approach for estimating production functions through support vector machines," Omega, Elsevier, vol. 104(C).
    18. Simar, Leopold & Wilson, Paul W., 2002. "Non-parametric tests of returns to scale," European Journal of Operational Research, Elsevier, vol. 139(1), pages 115-132, May.
    19. Sokol, Ondřej & Frýd, Lukáš, 2023. "DEA efficiency in agriculture: Measurement unit issues," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    20. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    21. Gounopoulos, Dimitrios & Kallias, Konstantinos & Newton, David & Tzeremes, Nickolaos, 2016. "Political connections and IPO underpricing: An efficiency problem," MPRA Paper 69427, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • A11 - General Economics and Teaching - - General Economics - - - Role of Economics; Role of Economists
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:respol:v:34:y:2005:i:4:p:495-516. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/respol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.