Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 538222
Title Assessing the impact of uncertainty on benchmarking the eco-efficiency of dairy farming using fuzzy data envelopment analysis
Author(s) Mu, W.; Kanellopoulos, A.; Middelaar, C.E. van; Stilmant, D.; Bloemhof-Ruwaard, J.M.
Source Journal of Cleaner Production 189 (2018). - ISSN 0959-6526 - p. 709 - 717.
Department(s) Animal Production Systems
Operations Research and Logistics
Wageningen School of Social SciencesWASS
Publication type Refereed Article in a scientific journal
Publication year 2018
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.
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