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Simulating weight restrictions in data envelopment analysis using the subjective and objective integrated approach

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  • Chun-Chu Liu

Abstract

Data envelopment analysis (DEA) is a method that uses a mathematical programming model to determine the relative efficiency of a decision-making unit, and gives optimal weight for a set of inputs and outputs. The scores of the weights will generally differ from unit to unit and this flexibility in the choice of weights is both a strength and a weakness of this approach. The strength is that the weight generated will be fair and equitable, and not affected by subjective factors. The weakness is that, if the weight is selected intentionally, it may then make the decision-making unit relatively efficient, and its efficiency will not necessarily come from an inherent efficiency, but from the selection of the weight. Is the score of the relative efficiency obtained using such an innate weight fair, reasonable, and acceptable? This question is addressed in order to integrate the subjective and objective weights restriction method, so that the results of the evaluation can be more realistic. The study concludes by taking the garbage clearance of each district in Kaohsiung city in Southern Taiwan is considered to illustrate this approach.

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  • Chun-Chu Liu, 2006. "Simulating weight restrictions in data envelopment analysis using the subjective and objective integrated approach," Applied Economics, Taylor & Francis Journals, vol. 38(21), pages 2545-2552.
    • Handle: RePEc:taf:applec:v:38:y:2006:i:21:p:2545-2552
    DOI: 10.1080/00036840601043752
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    Cited by:

    1. Dimitrov, Stanko & Sutton, Warren, 2010. "Promoting symmetric weight selection in data envelopment analysis: A penalty function approach," European Journal of Operational Research, Elsevier, vol. 200(1), pages 281-288, January.

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