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.
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Acknowledgements
The authors are grateful to Isil Cillidag and Asli Cetiner from Taris Zeytin Company, Izmir, Turkey for their collaboration and support in data collection for this research.
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Atıcı, K.B., Gülpınar, N. (2016). Robust DEA Approaches to Performance Evaluation of Olive Oil Production Under Uncertainty. In: Doumpos, M., Zopounidis, C., Grigoroudis, E. (eds) Robustness Analysis in Decision Aiding, Optimization, and Analytics. International Series in Operations Research & Management Science, vol 241. Springer, Cham. https://doi.org/10.1007/978-3-319-33121-8_14
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DOI: https://doi.org/10.1007/978-3-319-33121-8_14
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