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Using multi-level frontiers in DEA models to grade countries/territories

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  • Yang, Guoliang
  • Ahlgren, Per
  • Yang, Liying
  • Rousseau, Ronald
  • Ding, Jielan

Abstract

Several investigations to and approaches for categorizing academic journals/institutions/countries into different grades have been published in the past. To the best of our knowledge, most existing grading methods use either a weighted sum of quantitative indicators (including the case of one properly defined quantitative indicator) or quantified peer review results. Performance measurement is an important issue of concern for science and technology (S&T) management. In this paper we address this issue, leading to multi-level frontiers resulting from data envelopment analysis (DEA) models to grade selected countries/territories. We use research funding and researchers as input indicators, and take papers, citations and patents as output indicators. Our research results show that using DEA frontiers we can unite countries/territories by different grades. These grades reflect the corresponding countries’ levels of performance with respect to multiple inputs and outputs. Furthermore, we use papers, citations and patents as single output (with research funding and researchers as inputs), respectively, to show country/territory grade changes. In order to increase the insight in this approach, we also incorporate a simple value judgment (that the number of citations is more important than the number of papers) as prior information into the DEA models to study the resulting changes of these Countries/Territories’ performance grades.

Suggested Citation

  • Yang, Guoliang & Ahlgren, Per & Yang, Liying & Rousseau, Ronald & Ding, Jielan, 2016. "Using multi-level frontiers in DEA models to grade countries/territories," Journal of Informetrics, Elsevier, vol. 10(1), pages 238-253.
    • Handle: RePEc:eee:infome:v:10:y:2016:i:1:p:238-253
    DOI: 10.1016/j.joi.2016.01.008
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    1. Wang, Eric C. & Huang, Weichiao, 2007. "Relative efficiency of R&D activities: A cross-country study accounting for environmental factors in the DEA approach," Research Policy, Elsevier, vol. 36(2), pages 260-273, March.
    2. Yang, Guo-liang & Rousseau, Ronald & Yang, Li-ying & Liu, Wen-bin, 2014. "A study on directional returns to scale," Journal of Informetrics, Elsevier, vol. 8(3), pages 628-641.
    3. Yang, Hsu-Hao & Chang, Cheng-Yu, 0. "Using DEA window analysis to measure efficiencies of Taiwan's integrated telecommunication firms," Telecommunications Policy, Elsevier, vol. 33(1-2), pages 98-108, February.
    4. Seiford, Lawrence M. & Zhu, Joe, 2003. "Context-dependent data envelopment analysis--Measuring attractiveness and progress," Omega, Elsevier, vol. 31(5), pages 397-408, October.
    5. Gerhard Kempkes & Carsten Pohl, 2010. "The efficiency of German universities-some evidence from nonparametric and parametric methods," Applied Economics, Taylor & Francis Journals, vol. 42(16), pages 2063-2079.
    6. Worthington, Andrew C. & Lee, Boon L., 2008. "Efficiency, technology and productivity change in Australian universities, 1998-2003," Economics of Education Review, Elsevier, vol. 27(3), pages 285-298, June.
    7. Avkiran, Necmi K., 2001. "Investigating technical and scale efficiencies of Australian Universities through data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 35(1), pages 57-80, March.
    8. 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.
    9. Zhong, Wei & Yuan, Wei & Li, Susan X. & Huang, Zhimin, 2011. "The performance evaluation of regional R&D investments in China: An application of DEA based on the first official China economic census data," Omega, Elsevier, vol. 39(4), pages 447-455, August.
    10. R. Allen & A. Athanassopoulos & R.G. Dyson & E. Thanassoulis, 1997. "Weights restrictions and value judgements in Data Envelopment Analysis: Evolution, development and future directions," Annals of Operations Research, Springer, vol. 73(0), pages 13-34, October.
    11. Abbott, M. & Doucouliagos, C., 2003. "The efficiency of Australian universities: a data envelopment analysis," Economics of Education Review, Elsevier, vol. 22(1), pages 89-97, February.
    12. Entani, Tomoe & Maeda, Yutaka & Tanaka, Hideo, 2002. "Dual models of interval DEA and its extension to interval data," European Journal of Operational Research, Elsevier, vol. 136(1), pages 32-45, January.
    13. Lee, Hakyeon & Shin, Juneseuk, 2014. "Measuring journal performance for multidisciplinary research: An efficiency perspective," Journal of Informetrics, Elsevier, vol. 8(1), pages 77-88.
    14. Tasso Brandt & Torben Schubert, 2013. "Is the university model an organizational necessity? Scale and agglomeration effects in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(2), pages 541-565, February.
    15. 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.
    16. Joe Zhu, 2014. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 1, pages 1-9, Springer.
    17. Shawna Grosskopf & Kathy Hayes & Lori L. Taylor, 2014. "Applied efficiency analysis in education," Economics and Business Letters, Oviedo University Press, vol. 3(1), pages 19-26.
    18. Andrew Worthington, 2001. "An Empirical Survey of Frontier Efficiency Measurement Techniques in Education," Education Economics, Taylor & Francis Journals, vol. 9(3), pages 245-268.
    19. Andrea Bonaccorsi & Cinzia Daraio, 2005. "Exploring size and agglomeration effects on public research productivity," Scientometrics, Springer;Akadémiai Kiadó, vol. 63(1), pages 87-120, March.
    20. Seema Sharma & V. J. Thomas, 2008. "Inter-country R&D efficiency analysis: An application of data envelopment analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(3), pages 483-501, September.
    21. Bandyopadhyay, Arindam, 2013. "Ranking of Business School Journals: A Rating Guide for Researchers," MPRA Paper 49608, University Library of Munich, Germany.
    22. Joanna Wolszczak-Derlacz & Aleksandra Parteka, 2011. "Efficiency of European public higher education institutions: a two-stage multicountry approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(3), pages 887-917, December.
    23. Cook, Wade D. & Tone, Kaoru & Zhu, Joe, 2014. "Data envelopment analysis: Prior to choosing a model," Omega, Elsevier, vol. 44(C), pages 1-4.
    24. Banker, Rajiv D. & Cooper, William W. & Seiford, Lawrence M. & Thrall, Robert M. & Zhu, Joe, 2004. "Returns to scale in different DEA models," European Journal of Operational Research, Elsevier, vol. 154(2), pages 345-362, April.
    25. 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.
    26. Torben Schubert, 2014. "Are there scale economies in scientific production? On the topic of locally increasing returns to scale," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 393-408, May.
    27. Guoliang Yang & Wanfang Shen & Daqun Zhang & Wenbin Liu, 2014. "Extended utility and DEA models without explicit input," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(8), pages 1212-1220, August.
    28. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    29. A. T. Flegg & D. O. Allen & K. Field & T. W. Thurlow, 2004. "Measuring the efficiency of British universities: a multi-period data envelopment analysis," Education Economics, Taylor & Francis Journals, vol. 12(3), pages 231-249.
    30. Peter Smith, 1997. "Model misspecification in Data Envelopment Analysis," Annals of Operations Research, Springer, vol. 73(0), pages 233-252, October.
    31. Roger Carrington & Tim Coelli & D. S. Prasada Rao, 2005. "The Performance Of Australian Universities: Conceptual Issues And Preliminary Results," Economic Papers, The Economic Society of Australia, vol. 24(2), pages 145-163, June.
    32. Lee, Hakyeon & Park, Yongtae & Choi, Hoogon, 2009. "Comparative evaluation of performance of national R&D programs with heterogeneous objectives: A DEA approach," European Journal of Operational Research, Elsevier, vol. 196(3), pages 847-855, August.
    33. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, December.
    34. Rajiv D. Banker, 1993. "Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation," Management Science, INFORMS, vol. 39(10), pages 1265-1273, October.
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