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Overcoming the limitations of efficiency modeling in the health care foodservice industry

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  • A. Assaf
  • K.M. Matawie
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    Abstract

    Purpose – This paper aims to reflect on the sources of the technical inefficiency of health care foodservice operations, using a sample of Australian and American hospitals. Design/methodology/approach – The paper applies the stochastic frontier model to reflect on the technical inefficiency and its sources. The advantage of the model is that it allows the simultaneous parameters estimation of technical efficiency as well as the factors that explain variations in technical efficiency. A set of hypotheses are tested to ensure the applicability and suitability of the suggested model. Then the model parameters are estimated, discussed and checked against the theoretical requirements and the literature. Findings – Results show that all the variable coefficients are correctly signed and that the average technical efficiency is around 83 percent for Australia and 80 percent for the USA. Practical implications – The technical efficiency results, according to the introduced model, suggest that health care foodservice operations in both countries are not operating at a full efficient level. The results also reveal that factors such as manager's education, manager's experience, and size have a direct impact on reducing the level of technical inefficiency of these operations. Originality/value – This paper overcomes the limitations of the existing efficiency techniques in the area of health care foodservice and also provides policy implications by emphasizing on the sources of technical inefficiency of health care foodservice operations for Australia and USA.

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    Bibliographic Info

    Article provided by Emerald Group Publishing in its journal Journal of Economic Studies.

    Volume (Year): 36 (2009)
    Issue (Month): 6 (November)
    Pages: 571-582

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    Handle: RePEc:eme:jespps:v:36:y:2009:i:6:p:571-582

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    Related research

    Keywords: Australia; Food service; Health services; Process efficiency; Stochastic modelling; United States of America;

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