In this paper we consider the use of data envelopment analysis (DEA) for the assessment of
efficiency of units whose output profiles exhibit specialisation. An example of this is found in
agriculture where a large number of different crops may be produced in a particular region,
but only a few farms actually produce each particular crop. Because of the large number of
outputs, the use of conventional DEA models in such applications results in a poor efficiency
discrimination. We overcome this problem by specifying production trade-offs between
different outputs, relying on the methodology of Podinovski (2004). The main idea of our
approach is to relate various outputs to the production of the main output. We illustrate this
methodology by an application of DEA involving agricultural farms in different regions of
Turkey. An integral part of this application is the elicitation of expert judgements in order to
formulate the required production trade-offs. Their use in DEA models results in a significant
improvement of the efficiency discrimination. The proposed methodology should also be of
interest to other applications of DEA where units may exhibit specialization, such as
applications involving hospitals or bank branches.
Funding
This research was partly supported by the European Commission through the Seventh Framework Programme (FP7) project 265616, titled “Integrating Econometric and Mathematical Programming Models into an Amendable Policy and Market Analysis Tool using FADN Database” (FADNTOOL).
History
School
Business and Economics
Department
Business
Published in
Omega (United Kingdom)
Volume
54
Pages
72 - 83
Citation
ATICI, K.B. and PODINOVSKI, V.V., 2015. Using data envelopment analysis for the assessment of technical efficiency of units with different specialisations: an application to agriculture. Omega, 54, pp.72-83
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
Publication date
2015
Notes
This paper was accepted for publication in the journal Omega and the definitive published version is available at http://dx.doi.org/10.1016/j.omega.2015.01.015