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Measuring National Innovation Systems Efficiency - A Review of DEA Approach

Listed author(s):
  • Maxim Kotsemir

    ()

    (ISSEK - Institute for Statistical Studies and Economics of Knowledge - State University Higher School of Economics)

Take full free-available version of this paper on http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2304735 The paper reviews the application of the data envelopment analysis (DEA) method for measuring the efficiency of national innovation systems (NIS). The paper firstly visualizes the logic of DEA method and briefly summarizes the key advantages and main limitations of the DEA method. Further, this paper provides a comprehensive review of 11 empirical studies on cross-country analysis of NIS efficiency with DEA technique. In its main part the paper analyses the specifications of DEA models used in the reviewed studies, the content of the country samples, sets of input and output variables used and the resulting lists of efficient countries. The review detects general trends and differences in the sets of variables and the content of country samples. Moreover, this paper highlights the problem of "small countries bias" in the reviewed studies: situation when "small" (in terms of national innovation system scope and the level of development) countries (like Venezuela, Kyrgyzstan etc.) are included in the country sample, these "small" countries become the efficient ones. In general, empirical studies on cross-country analysis of national innovation systems efficiency using DEA method pay little attention to profound analysis of previous relevant studies. Therefore, this paper is among the first papers with deep review of such empirical studies.

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Paper provided by HAL in its series Post-Print with number hal-00865875.

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Date of creation: 03 Aug 2013
Publication status: Published in Higher School of Economics Research Paper No. WP BRP 16/STI/2013 http://papers.ssrn.com/sol3/pape.. 2013, http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2304735. <10.2139/ssrn.2304735>
Handle: RePEc:hal:journl:hal-00865875
DOI: 10.2139/ssrn.2304735
Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-00865875
Contact details of provider: Web page: https://hal.archives-ouvertes.fr/

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  1. Maxim Kotsemir, 2012. "Dynamics of Russian and World Science through the Prism of International Publications," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 6(1), pages 38-58.
  2. Ekaterina Khramova & Dirk Meissner & Galina Sagieva, 2013. "Statistical patent analysis indicators as a means of determining country technological specialisation," HSE Working papers WP BRP 09/STI/2013, National Research University Higher School of Economics.
  3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
  4. Ta-Wei Pan & Shiu-Wan Hung & Wen-Min Lu, 2010. "Dea Performance Measurement Of The National Innovation System In Asia And Europe," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 27(03), pages 369-392.
  5. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
  6. Guan, Jiancheng & Chen, Kaihua, 2012. "Modeling the relative efficiency of national innovation systems," Research Policy, Elsevier, vol. 41(1), pages 102-115.
  7. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
  8. Astrid Cullmann & Jens Schmidt-Ehmcke & Petra Zloczysti, 2009. "Innovation, R&D Efficiency and the Impact of the Regulatory Environment: A Two-Stage Semi-Parametric DEA Approach," Discussion Papers of DIW Berlin 883, DIW Berlin, German Institute for Economic Research.
  9. Seiford, Lawrence M. & Thrall, Robert M., 1990. "Recent developments in DEA : The mathematical programming approach to frontier analysis," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 7-38.
  10. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
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