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MBA Program Reputation And Quantitative Rankings: New Information for Students, Employers, And Program Administrators

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Author Info

  • Yongil Jeon

    (Sungkyunkwan University)

  • Stephen M. Miller

    (University of Nevada, Las Vegas, and University of Connecticut)

  • Subhash C. Ray

    (University of Connecticut)

Abstract

Since 1988, Business Week biennially ranks MBA programs based on qualitative ("subjective") surveys of students and employers. The Business Week ranking, and similar rankings, based on perceptions of MBA-program customers, rings the alarm that image, rather than substance, may become the raison d'etre of MBA-program evaluation and selection. We rank MBA programs using the quantitative ("objective") data collected with the 2004 Business Week survey, attempting to address these concerns about image over substance. We employ equal-weighted and principal components indexes to rank MBA programs. Our indexes fall into three categories - output, input, and output-input indexes - that rank MBA programs proximately from the interests of students, employers, and MBA program administrators, respectively.

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Bibliographic Info

Paper provided by University of Connecticut, Department of Economics in its series Working papers with number 2007-44.

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Length: 36 pages
Date of creation: Oct 2007
Date of revision:
Handle: RePEc:uct:uconnp:2007-44

Note: This paper updates analysis contained in Jeon, Miller, and Ray (2003). That earlier paper employs the Business Week survey from 1998. This paper provides a new look, using the principal components technique to construct a ranking index and using the more recent 2004 Business Week survey.
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Keywords: MBA Programs; Reputation; Ranking; Principal Component;

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References

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  1. Joseph Tracy & Joel Waldfogel, 1994. "The Best Business Schools: A Market Based Approach," NBER Working Papers 4609, National Bureau of Economic Research, Inc.
  2. Breu, Theodore M. & Raab, Raymond L., 1994. "Efficiency and perceived quality of the nation's "top 25" National Universities and National Liberal Arts Colleges: An application of data envelopment analysis to higher education," Socio-Economic Planning Sciences, Elsevier, vol. 28(1), pages 33-45.
  3. Yongil Jeon & Stephen M. Miller & Subhash C. Ray, 2003. "MBA Program Reputation: Objective Rankings for Students, Employers and Program Administrators," Working papers 2003-28, University of Connecticut, Department of Economics.
  4. Johnes, Geraint & Johnes, Jill, 1993. "Measuring the Research Performance of UK Economics Departments: An Application of Data Envelopment Analysis," Oxford Economic Papers, Oxford University Press, vol. 45(2), pages 332-47, April.
  5. 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.
  6. Colbert, Amy & Levary, Reuven R. & Shaner, Michael C., 2000. "Determining the relative efficiency of MBA programs using DEA," European Journal of Operational Research, Elsevier, vol. 125(3), pages 656-669, September.
  7. Burton, M P & Phimister, Euan, 1995. "Core Journals: A Reappraisal of the Diamond List," Economic Journal, Royal Economic Society, vol. 105(429), pages 361-73, 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.
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Cited by:
  1. Besancenot, Damien & Faria, João Ricardo, 2010. "Good research and bad teaching? A business school tale," Research in Economics, Elsevier, vol. 64(2), pages 67-72, June.

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