Designing and selecting optimal scenario for outsourcing of tropical farming projects of Mostazafan Foundation of Islamic Revolution; emphasizing the empowerment of agricultural graduates

Document Type : Research Paper

Authors

1 Associate Professor, Department of New Business, Faculty of Entrepreneurship, University of Tehran, Tehran, Iran

2 Institute for Management and Planning, Tehran, Iran

3 Assistant Professor and Member of Sicence, Department of Agricultural Extension and Education, Razi University, Kermanshah, Iran

Abstract

The Mostazafan Foundation is one of the institutions that, in recent years, try to outsourcing its projects to poverty alleviation and empowerment of lower income groups of society. Field experiments show that choosing an effective outsourcing method can guarantee sustainability of the project after their outsourcing. Therefore, this research tried to use grounded theory and hierarchical analysis method to design and select an optimal scenario for outsourcing the project of Foundation of Mostazafan to graduates of Kermanshah province. In this regard, 35 key experts in farming sector with practical experience were selected as qualitative participants of the research. Data were collected from April to February 2016. The data of the first step were analyzed using open, axial and selective coding methods. The data of the second step were analyzed using Expert Choice software. The results of the first step showed that planners and officials are faced with four different scenarios for assigning this project. In order to select the preferred scenario, 9 different quantitative and qualitative indicators were used. Multi-criteria decision analysis method showed that scenario getting private partner among the four considered scenarios was more preferable. The sensitivity analysis of the efficiency of this scenario indicates the high economic efficiency, sustainability and survival of the project after its assignment.

Keywords

References

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Iranian Journal of Agricultural Economics and Development Research
Volume 50, Issue 4
November 2019
Pages 849-871

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