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Assessing the impact of the external non-discretionary factor on the performance of forest management units using DEA approach
University of Guilan, Iran.
University of Guilan, Iran.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology. (RCR)
Islamic Azad University, Iran.
2017 (English)In: Journal of Forest Research, ISSN 1341-6979, E-ISSN 1610-7403, Vol. 22, no 3, p. 144-152Article in journal (Refereed) Published
Abstract [en]

The purpose of this paper is to measure the relative performance of forest management units, and to analyze the impact of the external non-discretionary (ND) factors on these units' technical efficiency. Toward this end, data envelopment analysis (DEA) technique in variable returns to scale environment with both discretionary and ND factors has been used. The required data are collected from 24 Iranian forest management units (as decision-making units (DMUs)) and included four inputs and two outputs. The ND factors are first ignored and it is shown that most of the forest management units are operating at high efficiency levels. Then the variable area is considered as the exogenously fixed (or the external ND) input in a modified ND model because it is outside of the forest manager's control. The results indicate that the number of efficient units and the average technical efficiency score are reduced to 12 (approximately 50%) and 0.85, respectively. The forest management units should therefore increase their average efficiency score by 0.15 to move onto the new efficient frontier which is made by applying this strict criterion. As a consequence, it is recommended to apply the ND models for controlling the exogenously fixed factors and carrying out a correct and accurate evaluation, because the traditional DEA approaches may overestimate the efficiency of DMUs.

Place, publisher, year, edition, pages
2017. Vol. 22, no 3, p. 144-152
Keywords [en]
Efficiency, data envelopment analysis, input, output, non-discretionary factors, forest management
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:miun:diva-30562DOI: 10.1080/13416979.2017.1317227ISI: 000401738100002Scopus ID: 2-s2.0-85038084931OAI: oai:DiVA.org:miun-30562DiVA, id: diva2:1086406
Available from: 2017-04-03 Created: 2017-04-03 Last updated: 2020-12-17Bibliographically approved

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Mohammadi Limaei, SoleimanOlsson, Leif

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CiteExportLink to record
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  • apa
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