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Bayesian and DEA efficiency modelling: an application to hospital foodservice operations

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  • K. M. Matawie
  • A. Assaf

Abstract

The significant impact of health foodservice operations on the total operational cost of the hospital sector has increased the need to improve the efficiency of these operations. Although important studies on the performance of foodservice operations have been published in various academic journals and industrial reports, the findings and implications remain simple and limited in scope and methodology. This paper investigates two popular methodologies in the efficiency literature: Bayesian “stochastic frontier analysis” (SFA) and “data envelopment analysis” (DEA). The paper discusses the statistical advantages of the Bayesian SFA and compares it with an extended DEA model. The results from a sample of 101 hospital foodservice operations show the existence of inefficiency in the sample, and indicate significant differences between the average efficiency generated by the Bayesian SFA and DEA models. The ranking of efficiency is, however, statistically independent of the methodologies.

Suggested Citation

  • K. M. Matawie & A. Assaf, 2010. "Bayesian and DEA efficiency modelling: an application to hospital foodservice operations," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(6), pages 945-953.
    • Handle: RePEc:taf:japsta:v:37:y:2010:i:6:p:945-953
    DOI: 10.1080/02664760902949058
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    References listed on IDEAS

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    1. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1995. "Bayesian long-run prediction in time series models," Journal of Econometrics, Elsevier, vol. 69(1), pages 61-80, September.
    2. Greene, William H., 1980. "Maximum likelihood estimation of econometric frontier functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 27-56, May.
    3. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 77-105.
    4. Bauer, Paul W. & Berger, Allen N. & Ferrier, Gary D. & Humphrey, David B., 1998. "Consistency Conditions for Regulatory Analysis of Financial Institutions: A Comparison of Frontier Efficiency Methods," Journal of Economics and Business, Elsevier, vol. 50(2), pages 85-114, March.
    5. 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.
    6. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    7. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    8. 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.
    9. Greene, William, 1990. "Multiple roots of the Tobit log-likelihood," Journal of Econometrics, Elsevier, vol. 46(3), pages 365-380, December.
    10. Cullinane, Kevin & Wang, Teng-Fei & Song, Dong-Wook & Ji, Ping, 2006. "The technical efficiency of container ports: Comparing data envelopment analysis and stochastic frontier analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(4), pages 354-374, May.
    11. Fare, Rolf & Grosskopf, Shawna & Logan, James, 1983. "The relative efficiency of Illinois electric utilities," Resources and Energy, Elsevier, vol. 5(4), pages 349-367, December.
    12. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    Cited by:

    1. Dariusz Wozniak & Piotr Czarnecki & Robert Szarota, 2011. "The analysis of convergence process of voivodships' efficiency in Poland using the DEA metod," ERSA conference papers ersa11p925, European Regional Science Association.
    2. Chris Tofallis, 2024. "Objective Weights for Scoring: The Automatic Democratic Method," Papers 2409.02087, arXiv.org.
    3. Assaf, A. George & Tsionas, Mike & Kock, Florian & Josiassen, Alexander, 2021. "A Bayesian non-parametric stochastic frontier model," Annals of Tourism Research, Elsevier, vol. 87(C).
    4. Kounetas, Kostas & Napolitano, Oreste & Stavropoulos, Spyridon & Burger, Martijn, 2018. "European Regional Productive Performance under a Metafrontier Framework. The role of patents and human capital on technology gap?," MPRA Paper 88957, University Library of Munich, Germany, revised 17 Jul 2018.

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