Measuring Technical Efficiency of Dairy Farms with Imprecise Data: A Fuzzy Data Envelopment Analysis Approach

This article integrates fuzzy set theory in Data Envelopment Analysis (DEA) framework to compute technical efficiency scores when input and output data are imprecise. The underlying assumption in convectional DEA is that inputs and outputs 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 is known to lie within specified intervals and empirically illustrate this approach using a group of 34 dairy producers in Pennsylvania. Compared to the convectional DEA scores that are point estimates, the computed fuzzy efficiency scores allow the decision maker to trace the performance of a decision-making unit at different possibility levels.


Issue Date:
2011
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/103251
Total Pages:
30
JEL Codes:
D24; Q12; C02; C44; C61
Series Statement:
Selected Paper
13276




 Record created 2017-04-01, last modified 2017-08-22

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