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Measuring technical efficiency of dairy farms with imprecise data: a fuzzy data envelopment analysis approach
Author(s) -
Mugera Amin W.
Publication year - 2013
Publication title -
australian journal of agricultural and resource economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.683
H-Index - 49
eISSN - 1467-8489
pISSN - 1364-985X
DOI - 10.1111/1467-8489.12008
Subject(s) - data envelopment analysis , fuzzy logic , production (economics) , fuzzy set , computer science , decision maker , efficiency , envelopment , data mining , econometrics , mathematics , mathematical optimization , statistics , operations research , economics , artificial intelligence , microeconomics , estimator
This article integrates fuzzy set theory in the data envelopment analysis ( DEA ) framework to compute technical efficiency scores when input and output data are imprecise. The underlying assumption in conventional DEA is that input and output data are measured with precision. However, production agriculture takes place in an uncertain environment, and, in some situations, input and output data may be imprecise. We present an approach of measuring efficiency when data are known to lie within specified intervals and empirically illustrate this approach using a group of 29 dairy producers in P ennsylvania. Compared to the conventional DEA scores that are point estimates, the computed fuzzy efficiency scores are interval bound allowing the decision maker to trace the performance of a decision‐making unit at different possibility levels.