Model the allocation of productive financial resources from the perspective of livelihood poverty indicators using a combination of clustering methods and SAW technique

Poverty is a social, economic, cultural and political reality that has long been one of the greatest human problems. The diversity of problems, needs and problems of the deprived and low-income groups of the society and the multiplicity of poverty indicators on the one hand, and on the other hand th...

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Main Authors: mehrdad Mohamadpour shatery, hoshang taghizadeh, sahar khoshfetrat
Format: Article
Language:fas
Published: Kharazmi University 2023-06-01
Series:تحقیقات کاربردی علوم جغرافیایی
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Online Access:http://jgs.khu.ac.ir/article-1-3805-en.pdf
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author mehrdad Mohamadpour shatery
hoshang taghizadeh
sahar khoshfetrat
author_facet mehrdad Mohamadpour shatery
hoshang taghizadeh
sahar khoshfetrat
author_sort mehrdad Mohamadpour shatery
collection DOAJ
description Poverty is a social, economic, cultural and political reality that has long been one of the greatest human problems. The diversity of problems, needs and problems of the deprived and low-income groups of the society and the multiplicity of poverty indicators on the one hand, and on the other hand the lack of financial resources and credits to solve the poverty indicators, organizations in charge of poor affairs, including Imam Khomeini Relief Committee Has faced serious challenges in the optimal allocation of resources. Therefore, the aim of the present study is to classify the clients of Tabriz Relief Committee from the perspective of livelihood poverty indicators, ranking these clusters in terms of cost and finally allocating productive and optimal resources for each cluster. In this way, with the least resources, a wide range of the needy benefit from these resources. To do this, with cluster analysis of data extracted from the system, 700 clients of Tabriz Relief Committee have been clustered from the perspective of livelihood poverty indicators and K-mean method. The results of this study were a cluster structure consisting of 10 clusters, which according to the characteristics of the clusters, titles for the clusters were considered. Finally, in order to rank the clusters, a multi-characteristic SAW decision-making method has been used. The research findings show the difference between the effectiveness of allocation in clustering method compared to other traditional methods.
format Article
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institution Kabale University
issn 2228-7736
2588-5138
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publishDate 2023-06-01
publisher Kharazmi University
record_format Article
series تحقیقات کاربردی علوم جغرافیایی
spelling doaj-art-210a394c428147d4a5b62e554101421d2025-01-31T17:29:56ZfasKharazmi Universityتحقیقات کاربردی علوم جغرافیایی2228-77362588-51382023-06-012369381401Model the allocation of productive financial resources from the perspective of livelihood poverty indicators using a combination of clustering methods and SAW techniquemehrdad Mohamadpour shatery0hoshang taghizadeh1sahar khoshfetrat2 Ph.D. Student, Department of Management, Tabriz Branch, Islamic Azad University, Tabriz, Iran. Professor, Department of Management, Tabriz Branch, Islamic Azad University, Tabriz, Iran (Correspondimg Author) Assistant Professor, Department of Mathematics, Tabriz Branch, Islamic Azad University, Tabriz, Iran Poverty is a social, economic, cultural and political reality that has long been one of the greatest human problems. The diversity of problems, needs and problems of the deprived and low-income groups of the society and the multiplicity of poverty indicators on the one hand, and on the other hand the lack of financial resources and credits to solve the poverty indicators, organizations in charge of poor affairs, including Imam Khomeini Relief Committee Has faced serious challenges in the optimal allocation of resources. Therefore, the aim of the present study is to classify the clients of Tabriz Relief Committee from the perspective of livelihood poverty indicators, ranking these clusters in terms of cost and finally allocating productive and optimal resources for each cluster. In this way, with the least resources, a wide range of the needy benefit from these resources. To do this, with cluster analysis of data extracted from the system, 700 clients of Tabriz Relief Committee have been clustered from the perspective of livelihood poverty indicators and K-mean method. The results of this study were a cluster structure consisting of 10 clusters, which according to the characteristics of the clusters, titles for the clusters were considered. Finally, in order to rank the clusters, a multi-characteristic SAW decision-making method has been used. The research findings show the difference between the effectiveness of allocation in clustering method compared to other traditional methods.http://jgs.khu.ac.ir/article-1-3805-en.pdfpovertycluster analysissaw methodimam khomeini relief committee
spellingShingle mehrdad Mohamadpour shatery
hoshang taghizadeh
sahar khoshfetrat
Model the allocation of productive financial resources from the perspective of livelihood poverty indicators using a combination of clustering methods and SAW technique
تحقیقات کاربردی علوم جغرافیایی
poverty
cluster analysis
saw method
imam khomeini relief committee
title Model the allocation of productive financial resources from the perspective of livelihood poverty indicators using a combination of clustering methods and SAW technique
title_full Model the allocation of productive financial resources from the perspective of livelihood poverty indicators using a combination of clustering methods and SAW technique
title_fullStr Model the allocation of productive financial resources from the perspective of livelihood poverty indicators using a combination of clustering methods and SAW technique
title_full_unstemmed Model the allocation of productive financial resources from the perspective of livelihood poverty indicators using a combination of clustering methods and SAW technique
title_short Model the allocation of productive financial resources from the perspective of livelihood poverty indicators using a combination of clustering methods and SAW technique
title_sort model the allocation of productive financial resources from the perspective of livelihood poverty indicators using a combination of clustering methods and saw technique
topic poverty
cluster analysis
saw method
imam khomeini relief committee
url http://jgs.khu.ac.ir/article-1-3805-en.pdf
work_keys_str_mv AT mehrdadmohamadpourshatery modeltheallocationofproductivefinancialresourcesfromtheperspectiveoflivelihoodpovertyindicatorsusingacombinationofclusteringmethodsandsawtechnique
AT hoshangtaghizadeh modeltheallocationofproductivefinancialresourcesfromtheperspectiveoflivelihoodpovertyindicatorsusingacombinationofclusteringmethodsandsawtechnique
AT saharkhoshfetrat modeltheallocationofproductivefinancialresourcesfromtheperspectiveoflivelihoodpovertyindicatorsusingacombinationofclusteringmethodsandsawtechnique