Assessing the impact of uncertainty on benchmarking the eco-efficiency of dairy farming using fuzzy data envelopment analysis

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Abstract

The dairy sector is challenged to increase its eco-efficiency, which means, minimizing environmental impacts, while maintaining economic viability. To quantify eco-ef fi ciency, multiple environmental and economic indicators are needed. Data envelopment analysis (DEA) has been used to evaluate the eco-
efficiency of agricultural systems accounting for multiple indicators simultaneously. In practice, how-ever, data used to calculate the economic and environmental performance of dairy farms can contain high levels of uncertainty. Standard DEA is deterministic and does not consider data uncertainty. Fuzzy
DEA is a useful approach to account for uncertainties when benchmarking the eco-efficiency of dairy farming. In this study we therefore demonstrate how fuzzy DEA can be used to evaluate the eco-efficiency of dairy farming. We used a case study of 55 dairy farms from different regions across Western Europe. We used N surplus, P surplus, land use, energy use as the environmental indicators and gross margin as the economic indicator. We found that accounting for uncertainty around the value of environmental and economic indicators can affect substantially the eco-efficiency of evaluated farms. In addition, fuzzy DEA identified different set of peers compared to the peers of the standard DEA. All the aforementioned findings showed the importance of taking uncertainty into consideration in the benchmarking process, and how fuzzy DEA can be used to do so.
Original languageEnglish
Pages (from-to)709-717
JournalJournal of Cleaner Production
Volume189
Early online date11 Apr 2018
DOIs
Publication statusPublished - 10 Jul 2018

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dairy farming
data envelopment analysis
Data envelopment analysis
Dairies
benchmarking
Benchmarking
Economics
Farms
economics
environmental indicator
energy use
Land use
farming system
Environmental impact
Uncertainty
Eco-efficiency
Dairy farming
environmental impact
farm
land use

Cite this

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title = "Assessing the impact of uncertainty on benchmarking the eco-efficiency of dairy farming using fuzzy data envelopment analysis",
abstract = "The dairy sector is challenged to increase its eco-efficiency, which means, minimizing environmental impacts, while maintaining economic viability. To quantify eco-ef fi ciency, multiple environmental and economic indicators are needed. Data envelopment analysis (DEA) has been used to evaluate the eco-efficiency of agricultural systems accounting for multiple indicators simultaneously. In practice, how-ever, data used to calculate the economic and environmental performance of dairy farms can contain high levels of uncertainty. Standard DEA is deterministic and does not consider data uncertainty. FuzzyDEA is a useful approach to account for uncertainties when benchmarking the eco-efficiency of dairy farming. In this study we therefore demonstrate how fuzzy DEA can be used to evaluate the eco-efficiency of dairy farming. We used a case study of 55 dairy farms from different regions across Western Europe. We used N surplus, P surplus, land use, energy use as the environmental indicators and gross margin as the economic indicator. We found that accounting for uncertainty around the value of environmental and economic indicators can affect substantially the eco-efficiency of evaluated farms. In addition, fuzzy DEA identified different set of peers compared to the peers of the standard DEA. All the aforementioned findings showed the importance of taking uncertainty into consideration in the benchmarking process, and how fuzzy DEA can be used to do so.",
author = "W. Mu and A. Kanellopoulos and {van Middelaar}, C.E. and D. Stilmant and J.M. Bloemhof-Ruwaard",
year = "2018",
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T1 - Assessing the impact of uncertainty on benchmarking the eco-efficiency of dairy farming using fuzzy data envelopment analysis

AU - Mu, W.

AU - Kanellopoulos, A.

AU - van Middelaar, C.E.

AU - Stilmant, D.

AU - Bloemhof-Ruwaard, J.M.

PY - 2018/7/10

Y1 - 2018/7/10

N2 - The dairy sector is challenged to increase its eco-efficiency, which means, minimizing environmental impacts, while maintaining economic viability. To quantify eco-ef fi ciency, multiple environmental and economic indicators are needed. Data envelopment analysis (DEA) has been used to evaluate the eco-efficiency of agricultural systems accounting for multiple indicators simultaneously. In practice, how-ever, data used to calculate the economic and environmental performance of dairy farms can contain high levels of uncertainty. Standard DEA is deterministic and does not consider data uncertainty. FuzzyDEA is a useful approach to account for uncertainties when benchmarking the eco-efficiency of dairy farming. In this study we therefore demonstrate how fuzzy DEA can be used to evaluate the eco-efficiency of dairy farming. We used a case study of 55 dairy farms from different regions across Western Europe. We used N surplus, P surplus, land use, energy use as the environmental indicators and gross margin as the economic indicator. We found that accounting for uncertainty around the value of environmental and economic indicators can affect substantially the eco-efficiency of evaluated farms. In addition, fuzzy DEA identified different set of peers compared to the peers of the standard DEA. All the aforementioned findings showed the importance of taking uncertainty into consideration in the benchmarking process, and how fuzzy DEA can be used to do so.

AB - The dairy sector is challenged to increase its eco-efficiency, which means, minimizing environmental impacts, while maintaining economic viability. To quantify eco-ef fi ciency, multiple environmental and economic indicators are needed. Data envelopment analysis (DEA) has been used to evaluate the eco-efficiency of agricultural systems accounting for multiple indicators simultaneously. In practice, how-ever, data used to calculate the economic and environmental performance of dairy farms can contain high levels of uncertainty. Standard DEA is deterministic and does not consider data uncertainty. FuzzyDEA is a useful approach to account for uncertainties when benchmarking the eco-efficiency of dairy farming. In this study we therefore demonstrate how fuzzy DEA can be used to evaluate the eco-efficiency of dairy farming. We used a case study of 55 dairy farms from different regions across Western Europe. We used N surplus, P surplus, land use, energy use as the environmental indicators and gross margin as the economic indicator. We found that accounting for uncertainty around the value of environmental and economic indicators can affect substantially the eco-efficiency of evaluated farms. In addition, fuzzy DEA identified different set of peers compared to the peers of the standard DEA. All the aforementioned findings showed the importance of taking uncertainty into consideration in the benchmarking process, and how fuzzy DEA can be used to do so.

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