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Mr Farhad Ramezani, Dr Maryam Ghasemi, Dr Hadi Zarghani,
Volume 21, Issue 60 (3-2021)
Abstract

Today, in the context of sustainable rural development, the need to move quickly from traditional livelihoods to sustainable livelihood patterns is evident. It is obvious that achieving this change is not possible without regard to the household's livelihoods and assets. Livelihoods include the types of natural, physical, human, social and financial assets that are considered as essential to the livelihoods of the poor. Accordingly, the main objective of this study is to measure the level of livelihoods of households living in the border villages of Torbat-e-yam. The descriptive-analytic research methodology is an applied-developmental type. In the present study, livelihood assets were categorized into 5 types of assets with the help of 64 indicators. These indices in the confirmatory factor analysis explained 66% of the variance, and also the Cronbach's alpha coefficient was 0.91, indicating the validity and reliability of the research tool. The statistical population of the study is all border villages in more than 20 households in Torbat-e Jam. The unit analyzes 264 households in 17 villages located 10 kilometers from the border between Iran and Afghanistan. The results of the study showed that the livelihood of rural households living at the border is very low, so that the average human capital is 2.13, capital 1.87, social capital 2.48, physical capital 1.81, natural capital 12 / 2 in the Likert spectrum is significantly lower than the theoretical one. Also, the "livelihood assets" structure with an average of 2.22 was measured as "low". The results of the research show that the livelihood patterns of the border villages continue to be characterized by traditional livelihoods and have little adaptation to sustainable livelihoods, and the settlement in the village, along with the geographical isolation of the borders, has created many livelihoods for the dwelling population. Any activity in the field of livelihood modeling requires attention to the multiplicity of livelihoods.
 

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