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Multi-Factor Policy Evaluation and Selection in the One-Sample Situation

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  • Chen, C.M.

Abstract

Firms nowadays need to make decisions with fast information obsolesce. In this paper I deal with one class of decision problems in this situation, called the “one-sample” problems: we have finite options and one sample of the multiple criteria with which we use to evaluate those options. I develop evaluation procedures based on bootstrapping DEA (Data Envelopment Envelopment) and the related decision-making methods. This paper improves the bootstrap procedure proposed by Simar and Wilson (1998) and shows how to exploit information from bootstrap outputs for decision-making.

Suggested Citation

  • Chen, C.M., 2008. "Multi-Factor Policy Evaluation and Selection in the One-Sample Situation," ERIM Report Series Research in Management ERS-2008-084-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    • Handle: RePEc:ems:eureri:14275
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    References listed on IDEAS

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    1. J. P. Royston, 1983. "Some Techniques for Assessing Multivarate Normality Based on the Shapiro‐Wilk W," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 32(2), pages 121-133, June.
    2. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    3. Tsybakov, A.B. & Korostelev, A.P. & Simar, L., 1992. "Efficient Estimation of Monotone Boundaries," Papers 9209, Catholique de Louvain - Institut de statistique.
    4. Green, Rodney H. & Doyle, John R. & Cook, Wade D., 1996. "Preference voting and project ranking using DEA and cross-evaluation," European Journal of Operational Research, Elsevier, vol. 90(3), pages 461-472, May.
    5. Simar, Leopold & Wilson, Paul W., 1999. "Estimating and bootstrapping Malmquist indices," European Journal of Operational Research, Elsevier, vol. 115(3), pages 459-471, June.
    6. 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.
    7. C A K Lovell & A P B Rouse, 2003. "Equivalent standard DEA models to provide super-efficiency scores," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(1), pages 101-108, January.
    8. Talluri, Srinivas & Narasimhan, Ram, 2004. "A methodology for strategic sourcing," European Journal of Operational Research, Elsevier, vol. 154(1), pages 236-250, April.
    9. Korostelev, A. P. & Simar, L. & Tsybakov, A. B., 1995. "Estimation of monotone boundaries," LIDAM Reprints CORE 1178, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Muhittin Oral & Ossama Kettani & Pascal Lang, 1991. "A Methodology for Collective Evaluation and Selection of Industrial R&D Projects," Management Science, INFORMS, vol. 37(7), pages 871-885, July.
    11. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    12. Kleinsorge, Ilene K. & Schary, Philip B. & Tanner, Ray D., 1992. "Data Envelopment Analysis for monitoring customer-supplier relationships," Journal of Accounting and Public Policy, Elsevier, vol. 11(4), pages 357-372.
    13. L. J. Bourgeois, III & Kathleen M. Eisenhardt, 1988. "Strategic Decision Processes in High Velocity Environments: Four Cases in the Microcomputer Industry," Management Science, INFORMS, vol. 34(7), pages 816-835, July.
    14. N. J. Jobst & M. D. Horniman & C. A. Lucas & G. Mitra, 2001. "Computational aspects of alternative portfolio selection models in the presence of discrete asset choice constraints," Quantitative Finance, Taylor & Francis Journals, vol. 1(5), pages 489-501.
    15. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    16. D K Despotis, 2002. "Improving the discriminating power of DEA: focus on globally efficient units," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(3), pages 314-323, March.
    17. Arnd Huchzermeier & Christoph H. Loch, 2001. "Project Management Under Risk: Using the Real Options Approach to Evaluate Flexibility in R...D," Management Science, INFORMS, vol. 47(1), pages 85-101, January.
    18. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2006. "Introduction to Data Envelopment Analysis and Its Uses," Springer Books, Springer, number 978-0-387-29122-2, March.
    19. 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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    More about this item

    Keywords

    R&D project; bootstrap; data envelopment analysis; multiple criteria; parametric transformation; supplier selection;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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