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Random effects logistic regression model for data envelopment analysis with correlated decision making units

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  • S Y Sohn

    (Yonsei University)

  • H Choi

    (Yonsei University)

Abstract

This study attempts to exploit information from environmental variables together with data envelopment analysis (DEA) efficiency scores for efficiency predictions of groups with more limited information. Based on DEA efficiency scores, decision-making units (DMUs) are sorted into two sets containing efficient and inefficient units, respectively. Then they are reshuffled into homogeneous groups with respect to environmental factors. We assume that the efficiency of DMUs in such a homogeneous group would be correlated. However, efficiency of different groups would vary. A beta binomial logistic model is proposed to fit such phenomena and is applied to predict the performance of a new group of commercialization projects for given environmental characteristics.

Suggested Citation

  • S Y Sohn & H Choi, 2006. "Random effects logistic regression model for data envelopment analysis with correlated decision making units," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 552-560, May.
    • Handle: RePEc:pal:jorsoc:v:57:y:2006:i:5:d:10.1057_palgrave.jors.2602026
    DOI: 10.1057/palgrave.jors.2602026
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    References listed on IDEAS

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    5. Rajiv D. Banker & Richard C. Morey, 1986. "The Use of Categorical Variables in Data Envelopment Analysis," Management Science, INFORMS, vol. 32(12), pages 1613-1627, December.
    6. Sohn, S. Y., 1996. "Random effects meta analysis of military recruiting," Omega, Elsevier, vol. 24(2), pages 141-151, April.
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    Cited by:

    1. Daniel Friesner & Ron Mittelhammer & Robert Rosenmane, 2006. "Inferring the Latent Incidence of Inefficiency from DEA Estimates and Bayesian Priors," Working Papers 2006-8, School of Economic Sciences, Washington State University.
    2. Nima Mirzaei & Béla Vizvári, 2015. "A New Approach to Reconstruction of Moody’s Rating System for Countries Investment Risk Rating," Journal of Empirical Economics, Research Academy of Social Sciences, vol. 4(3), pages 167-182.
    3. S Y Sohn & Y Kim & B T Kim, 2009. "Cost of ownership model for spare engines purchase for the Korean navy acquisition program," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1674-1682, December.
    4. Kim, Yoonseong & Sohn, So Young, 2008. "Random effects model for credit rating transitions," European Journal of Operational Research, Elsevier, vol. 184(2), pages 561-573, January.
    5. Friesner, Daniel & Mittelhammer, Ron & Rosenman, Robert, 2013. "Inferring the incidence of industry inefficiency from DEA estimates," European Journal of Operational Research, Elsevier, vol. 224(2), pages 414-424.

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