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Using Coopers Approach to Explore the Extent of Congestion in the New British Universities

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  • A T Flegg
  • D O Allen
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    Abstract

    This paper uses data envelopment analysis (DEA) to explore the issue of congestion in British universities.? The focus is on 41 former polytechnics that became universities in 1992, and the analysis covers the period 1995/6 to 2003/4.? These new universities differ from the older universities in many ways, especially in terms of their far higher student:staff ratios and much lower research funding per member of staff.? The primary aim is to examine whether this under-resourcing of the new universities has led to congestion, in the sense that their output has been decreased as a result of having too many students.? This phenomenon is measured using the method proposed by Cooper et al. in a series of articles.? To check the sensitivity of the results to different specifications, three alternative DEA models are formulated.? The results reveal that a substantial amount of congestion was present throughout the period under review, and in a wide range of universities.? An overabundance of undergraduate students is identified as the largest single cause of congestion in the former polytechnics.? Less plausibly, the results also suggest that academic overstaffing was a major cause of congestion.? By contrast, postgraduates and ?other expenditure? are found to play a noticeably smaller role in generating congestion.

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    Bibliographic Info

    Article provided by Economic Issues in its journal Economic Issues.

    Volume (Year): 12 (2007)
    Issue (Month): 2 (September)
    Pages: 47-82

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    Handle: RePEc:eis:articl:207flegg

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    Web page: http://www.economicissues.org.uk
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    1. Cooper, William W. & Seiford, Lawrence M. & Zhu, Joe, 2000. "A unified additive model approach for evaluating inefficiency and congestion with associated measures in DEA," Socio-Economic Planning Sciences, Elsevier, vol. 34(1), pages 1-25, March.
    2. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    3. Timothy Rodgers, 2007. "Measuring Value Added in Higher Education: A Proposed Methodology for Developing a Performance Indicator Based on the Economic Value Added to Graduates," Education Economics, Taylor & Francis Journals, vol. 15(1), pages 55-74.
    4. Cherchye, Laurens & Kuosmanen, Timo & Post, Thierry, 2001. "Alternative treatments of congestion in DEA: A rejoinder to Cooper, Gu, and Li," European Journal of Operational Research, Elsevier, vol. 132(1), pages 75-80, July.
    5. Johnes, Jill, 2006. "Data envelopment analysis and its application to the measurement of efficiency in higher education," Economics of Education Review, Elsevier, vol. 25(3), pages 273-288, June.
    6. 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.
    7. Tone, Kaoru & Sahoo, Biresh K., 2004. "Degree of scale economies and congestion: A unified DEA approach," European Journal of Operational Research, Elsevier, vol. 158(3), pages 755-772, November.
    8. Cooper, W. W. & Gu, Bisheng & Li, Shanling, 2001. "Comparisons and evaluations of alternative approaches to the treatment of congestion in DEA," European Journal of Operational Research, Elsevier, vol. 132(1), pages 62-74, July.
    9. Izadi, Hooshang & Johnes, Geraint & Oskrochi, Reza & Crouchley, Robert, 2002. "Stochastic frontier estimation of a CES cost function: the case of higher education in Britain," Economics of Education Review, Elsevier, vol. 21(1), pages 63-71, February.
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    Cited by:
    1. Flegg, A.T. & Allen, D.O., 2009. "Congestion in the Chinese automobile and textile industries revisited," Socio-Economic Planning Sciences, Elsevier, vol. 43(3), pages 177-191, September.

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