درخت حوزه‌های تخصصی

Purpose: In this research, we aimed to identify the pattern of cooperative relations among the Pistachio producers in Damankuh rural district in Damghan. The social capital among the producers was also evaluated. Design/methodology/approach: In this paper, the cooperative relations and the social capital among the Pistachio producers in Mehmandoost, Zarrinabad and Hoseinabad Doolab, which are located in Damankooh in Damghan, were studied by applying social network analysis method. Thus, 66 people from Mehmandoost, 70 producers from Zarrinabad, and 74 farmers from Hosseinabad Dulab were studied. The relations which were studied included cooperation in exchanging farming tools, irrigation of Pistachio orchards, marketing and pest control. For analyzing these relations, we used network- level indicators of social network analysis including density, centralization, reciprocity, transitivity and Geodesic distance. These indicators were analyzed in the UCINET software. Finding: Results showed that the network macro-level indicators including density, centralization, reciprocity, transitivity and geodesic distance in studied villages were very low. This has caused problems for producers to cooperate with each other and threatens the stability of producers’ network and indicates cooperation among pistachio producers requires tremendous investment of both time and cost. Research limitations/implications: Problems like accessing farmers, distributing questionnaires among them and the long time needed in order to interview them were among the challenges faced in this research. Practical implications¬: In order to increase cooperation among the producers and social capital in their network it is suggested that farmers be instructed and informed by holding cooperative workshops, handling their problems in irrigation and pest control, running local cooperatives for supporting the farmers in the crop prices and paying attention to their demands. Originality/value: Given the importance of the studied area in the production of Pistachio, paying attention to cooperation and social capital among producers, can be a big step in using the fertility (potentiality) of this region to develop and improve the Pistachio production.

Purpose: The environment is a divine favor whose protection can have a positive effect on lives of humans and other creatures. A look at the verses of the Quran and the life style of the Prophet’s family (PBUT) make it clear that no school like Islam has attached such a great importance to nature and the environment. Accordingly, using Quranic indices, in this study we have aimed to analyze the level of environmental development in rural areas of Sistan. Design/methodology/approach- The population of the study is the people in the rural areas of Sistan. To determine the sample population using Sharpe formula, 40 villages (with 51663 households) out of 796 villages in Sistan region were selected, and 381 heads of households were randomly selected according to Cochran formula. For data analysis, Kruskal-Wallis statistical method in SPSS was used, and then Topsis was employed to weigh and determine the degree of development of the villages. Findings: The evaluation showed that level of environmental development in rural areas is less than .01% percent significant. Out of 9 environmental indices, the index of optimal utilization of water, with a mean of 4.29 ranked first. Practical implications- According to the research results, coherent planning for the revival of the genuine Islamic culture and development of religious teachings about the role and significance of nature, the realization of God's real ownership of all national resources, optimal utilization of natural resources, prevention of corruption in the environment, and appropriate utilization of forests and rangelands, especially national resources, is a strategy that can lead our society to sensible utilization of natural resources.

Purpose: The aim of this study was to analyze the spatial reflection rural housing reconstruction after the earthquake in Sinai district located in the Varzeghan county aspects of infrastructure-related, social, cultural and health treatment. Design/methodology/approach: This study is a descriptive and analytical. The data collection was in the library field. In the field, the questionnaire is used. The sample size was 300 and the sampling method is simple random sampling. The validity of the questionnaire was evaluated based on the validity and reliability of the Guttman coefficient (split-half) which is equal to 955/0 and show the reliability of the questionnaire. Finding: After assuring the goodness of fitting the designed model, the standardized load factor test indicates that the measuring instrument has very good validation tools and shows that the coefficients and chi-square ratio are relative to the degree of freedom that has strong correlation, the relationships between hidden variables together and the relationship of obvious variables; Investigating T values of the obvious variables shows that the Infrastructure Index has the most impact on the renovation of rural housing. Which has the most effective coefficients in this case, the variables of "gas supply", "water distribution", and "transport communication network". Finally, the covariance matrix of the independent variables of the research indicates that the path estimates between all the infrastructural, cultural, social, health and physical variables are acceptable and acceptable at the upper limit. In fact, the proposed model can be proposed as a useful tool for reflecting the spatial renovation of rural housing in general, the renovation of rural housing after the earthquake in the Sina village of Varzaghan has caused the infrastructure index to have the highest spatial reflection. Research limitations/implications: The study population dispersion and trouble completing the questionnaires, as well as the lack of necessary resources on SEM and LISREL software. Originality/value: research innovation combined two important issues the village, housing "and" disaster "and interpret the results using a combination of software LISREL structural equations and multivariable regression analysis using software SPSS.