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Robust DEA Approaches to Performance Evaluation of Olive Oil Production Under Uncertainty

In: Robustness Analysis in Decision Aiding, Optimization, and Analytics

Author

Listed:
  • Kazım Barış Atıcı

    (Hacettepe University)

  • Nalân Gülpınar

    (Warwick Business School, The University of Warwick)

Abstract

In this chapter, we are concerned with performance evaluation of olive oil production using Data Envelopment Analysis (DEA) under uncertainty. In order to measure production efficiency of olive-growing farms, we first apply an imprecise DEA approach by taking into account optimistic and pessimistic perspectives on uncertainty realized in olive oil production yield. We then consider robust optimization based DEA under an uncertainty set where the random data belong. The robust DEA model enables to adjust level of conservatism that is defined by the price of robustness of the uncertainty set. The performance of imprecise and robust DEA models is illustrated via a case study of olive-growing farms located in the Aegean Region of Turkey. The numerical experiments reveal that the efficiency scores and efficiency discriminations dramatically depend on how the uncertainty is treated both in imprecise and robust DEA modeling. There exists a trade-off between the protection level and conservatism of the efficiency scores.

Suggested Citation

  • Kazım Barış Atıcı & Nalân Gülpınar, 2016. "Robust DEA Approaches to Performance Evaluation of Olive Oil Production Under Uncertainty," International Series in Operations Research & Management Science, in: Michael Doumpos & Constantin Zopounidis & Evangelos Grigoroudis (ed.), Robustness Analysis in Decision Aiding, Optimization, and Analytics, chapter 0, pages 299-318, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-33121-8_14
    DOI: 10.1007/978-3-319-33121-8_14
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