Farm Power and Machinery Distribution in Iran: Fuzzy Analytical Hierarchy Process (FAHP) and Weight Restriction Data Envelopment Analysis (WR-DEA) Models

Authors
E. Houshyar 1
H. Azadi 2
S. M. Mirdehghan 3
1 Department of Mechanical Engineering of Biosystems, Jahrom University, P. O. BOX: 74135–111, Jahrom, Islamic Republic of Iran.
2 Czech University of Life Sciences Prague, Faculty of Environmental Sciences, Prague, Czech Republic.
3 Department of Mathematics, College of Sciences, Shiraz University, Shiraz, Islamic Republic of Iran.
Abstract
In Iran, allocating tractors and agricultural machinery to regions that have different characteristics has been a challenge. This study was carried out in order to develop an optimal and practical model for distribution of agricultural machinery throughout the country. Gini coefficient was used in order to investigate whether current status of tractor distribution is suitable. This coefficient confirmed that the current tractor power distribution is not appropriate since there were no relationships between Gini coefficient of distributed machinery power and crop production or farm area. Accordingly, two main techniques were applied to develop a suitable agricultural machinery distribution pattern; i.e. a Fuzzy Analytical Hierarchy Process (FAHP) and a Weight Restriction Data Envelopment analysis (WR-DEA) technique. A power distribution category was defined in order to show qualitatively how much machinery power should be sent to each province. The outputs of both FAHP and WR-DEA models showed that three and nine provinces need ‘much more power’ and ‘more power’, respectively, while four and three provinces need ‘absolutely no more power’ and are ‘currently suitable’, respectively. The sensitivity analysis revealed that none of the developed models was sensitive to the weights defined by a panel of experts. The similarity of the results obtained from both models implies that the provided agricultural machinery distribution pattern is reliable and can be used in the country.

Keywords

Subjects

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Journal of Agricultural Science and Technology
Volume 22, Issue 3
March and April 2020
Pages 639-652