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Supplier selection: comparison of DEA models with additive and reciprocal data

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  • Imre Dobos

    (Budapest University of Technology and Economics)

  • Gyöngyi Vörösmarty

    (Corvinus University of Budapest)

Abstract

Supplier evaluation is one of the most important fields of application for data envelopment analysis (DEA). Criteria may include negative data in both input and output factors. Data translation can solve this problem, but interpretation is not evident from the literature. Use of an additive model is one method of managing the problem of negative data. This paper addresses this issue in relation to the supplier ranking problem. It describes the development of a ranking with cross-efficiency that incorporates negative data into the additive model. The additive model we describe is compared with previously used DEA models in which data is replaced with reciprocal values when necessary. We present a supplier-evaluation-related example of this case. After the efficiency evaluation, a supplier ranking system is constructed. To do this, we use the cross-efficiencies obtained from the additive model. Aggregate efficiencies help display the suppliers in descending order of efficiency. Finally, the paper compares self- and peer-appraisal indicators for reciprocal and additive DEA models.

Suggested Citation

  • Imre Dobos & Gyöngyi Vörösmarty, 2021. "Supplier selection: comparison of DEA models with additive and reciprocal data," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 447-462, June.
    • Handle: RePEc:spr:cejnor:v:29:y:2021:i:2:d:10.1007_s10100-020-00682-w
    DOI: 10.1007/s10100-020-00682-w
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    Cited by:

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