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Showing 3 results for Jiroft

Saleh Shahrokhi Sardou, Mehdi Nooripoor,
Volume 4, Issue 12 (9-2015)
Abstract

Introduction
The concept of quality of life has been emerged in theoretical literature and press in early 1960s, it has turned to be one of the interested issues in social science and in recent years, it has been a base for modern differentiation and classification of countries. Improving quality of life in a special place or for special people or groups is always the focusing concern to plan makers. Improving quality of life could be followed by other dimensions of development such as social, economic and physical ones. In this way, rural areas need some studies related to quality of life. These studies should include related aspects to quality of life in the village, reduction of geographical exclusion and accessibility to basic needs of life. Moreover, the results of studies on quality of life could be helpful in assessment of policies, ranking the locations, codification of management strategies and urban and rural planning which can facilitate understanding and prioritization of socio-economic issues for plan makers and managers to improve people's quality of life. Considering that urban growth and urbanization are the most obvious social, economic changes in recent times, urbanization rapidly spread so that this phenomenon has limited most of the opportunities which can improve quality of life for the villages. However, in many rural areas in Iran, despite of different changes in case of improving quality of life, we are still far from the ideal situation. This condition is more obvious in the areas that most of the population lives in the villages; Jiroft County located in Kerman Province is an example. Therefore, this study aims to assess factors affecting quality of life in villages located in Jiroft.
Methodology
According to its aim, this study is a practical one and regarding its data collection method, it is a survey which uses questionnaires as the tool of data collection; The face validity is confirmed by faculty members in Yasouj University and Shiraz University; to examine its validity, Pilot study is conducted as the pre-test outside the study population, on the residents in Ali-Abad village, Jiroft; Calculation of Cronbach's alfa for different factors (from 0.71 to 0.89) is estimated that suggests the reliability of this assessment tool. In this study, the unit of analysis includes the householder. Furthermore, according to government census, the population was 4243 households among them 350 households have been chosen using Krejcie & Morgan random sampling table as the population of this study; samples have been chosen according to each village population and geographical region according to the classes. Data analysis was performed using SPSS.
Discussion and Conclusion
This study is the assessment of each factors of quality of life in studied villages from householders' point of view. According to the obtained average value of 2.75, analytical results in the case of social factor are assessed which is under the average. According to the obtained average value of 3.43, in the case of social security, the studied households' condition has been estimated more than the average and findings related to average comparison in this factor shows that Delfard village has the worst condition and Sarbijan village has the best condition. According to the average value of 0.74 in the case of housing factor, the housing status in the studied villages was estimated more than the average. The results of average comparison showed that Halil village is on the highest level and Esfandegheh village is on the lowest level in the case of average factor. According to the average value of 20.38 which is related to the third group that means most of the studied population, income factor showed that most of studied population have average income and among them, comparing other studied villages, residents of Khaton-abad village have the highest level in the case of average income and it is different from other studied villages. Next factor is wealth which is assessed by five subset. According to the average value of 0.41 in this factor, it can be said that the level of wealth in studied villages is lower than average level and among them, Delfard and Ganj-abad villages are at the lowest level and Esfandegheh and Sarbijan villages are at the highest level. Next factor is per capita household expenditure on clothing; the result of analyzing this factor shows that given the frequency of 192 people (54.9%), per capita expenditure on clothing for each person is between 200 to 300 hundred Tomans in a year and comparing to other villages, Delfard village has a better condition regarding the average level of this factor. The results in the nutrition factor shows that villages located in this region are divided to four grades regarding the average calories intake per gram in food by households. Among them, Delfard village is completely different from other villages and in terms of calories amount that its residents consume, this village has a better condition. The last studied factor is people's satisfaction of objective dimensions of quality of life. According to the obtained average value of 3.15 which is higher than theoretical average (number 3), considering this factor, the status of studied households is assessed higher than the average level. The results of average comparison in this factor show that all the villages are divided to four classes regarding the average value of the considered factor. Among them Dolat-abad and Ganj-abad villages have the worst and Esfandegheh and Delfard villages have the best condition.

Aliakbar Anabestani, Farokh Legha Bahadori Amjaz, Jamileh Tavakolinia,
Volume 11, Issue 39 (5-2022)
Abstract

 Introduction
Smart growth is one of the regional planning strategies that aims to create regional balance and prevent degradation in line with the goals of sustainable development, which seeks to create and promote social equality, a sense of spatial and social belonging and preservation of natural resources alongside cultural resources. It also has significant benefits for rural communities through preserving their history and identity, making rural settlements more pleasant and livable, sustainable economic development, creating diverse and more affordable housing options and preserving ecological sustainability. It can be argued that the challenges a rural area is facing even if sometimes similar, can never be the same in different countries. Rural areas or villages need a specific growth that improves people's lives. This is because rural development is essential to accelerate the overall development of any country. However, the unplanned growth of the rural population, unplanned physical development of rural settlements and the improper use of the rural environment have created a situation which calls for the special need for planning in rural areas. A review of the statistics of involuntary rural migration and the problems that migrants create in destinations show the consequences of neglecting the villages, which are the main challenges facing managers and planners. Therefore, paying attention to rural development and sustainability requires more serious and systematic research. One of the proposed strategies in the field of rural sustainability is the smart growth strategy, which is in the form of sustainable development theory. Therefore, it seems that the smart growth approach can provide a way out of instability and achieve sustainable development in rural areas. in addition to identifying the indicators of smart growth and determining the effect and relationships between them, the purpose of this study is the spatial analysis of factors affecting the formation of smart growth in rural settlements of Jiroft.

 Methodology
This research is an applied and descriptive-analytical study. we used documentary and library methods for theoretical framework and to investigate the factors affecting the formation of smart growth in rural settlements, field study and the questionnaire were used. The statistical population of the present study consists of two groups. According to the assumption that smart growth infrastructure is probable in large villages, we selected over 1000 people villages as the experimental group villages. Also, in this study, cluster sampling method (multi-stage) was used. For this purpose, in the first stage, among 4 districts of Jiroft County and 14 rural districts of this county, according to the 2016 census, 11 rural districts were selected as a cluster sample. According to the 2016 census, this city has 30 villages with a population of more than 1000 people (Jabal Barez 2 villages, Markazi 21 villages, Ismaili 7 villages). To determine the sample size of villages, Cochran's formula was applied. In this formula, to take advantage of 95% confidence level, accuracy coefficient of 0.05 and variance = 0.15 d2, the sample size of 18 villages has been determined. Among rural households, according to Cochran's formula, 261 households were selected as a sample and were randomly interviewed.

Discussion and conclusion
The extent smart growth and sustainable development affect all members of society from the lowest to the highest level. Therefore, improving the status of smart growth indicators can provide the basis for sustainable rural development. We examined different sources as well as the characteristics of the study area and ended up with seven components of local economy stability, environmental quality improvement, density and intensive development, housing quality improvement, transportation and communication, local community stability, and physical texture improvement. From the perspective of rural respondents, the indicators of rural smart growth, transportation and communication and physical texture improvement, respectively, were the most important indicators of rural smart growth. From the experts point of view, based on a pairwise comparison of components, the components of local economy stability, transportation and communications, housing quality improvement, environmental quality improvement with weights of 0.303, 0.204, 0.132 and 0.126, respectively, were the most important factors affecting smart growth. Also, the components of density and intensive development, improvement of physical texture and stability of the local community with weights of 0.065, 0.081 and 0.089, respectively, are the less important factors. Finally, for spatial analysis of smart growth indices, the combined weighting method of AHP and COCOSO were used. Narjo and Sogdar have the lowest rank in terms of intelligent growth indicators. The research findings are in line with the results of other researchers. For instance, Tregear & Cooper 2016 believes that smart growth can help by making rural settlements more livable, sustainable economic development, creating diverse and affordable housing options, and maintaining ecological, social, economic, and physical sustainability, resulting in significant benefits for rural communities.

Aliakbar Anabestani, Sirous Ghanbari, Habib Lotfi,
Volume 12, Issue 43 (4-2023)
Abstract

Introduction
Iran has successfully leveraged knowledge and technology with the Islamic economic system to cultivate a prosperous rural economy. This economy encompasses a wide range of activities at the village level, all aimed at supporting rural residents' livelihoods and material well-being. It encompasses both individual and social activities within the rural environment and has yielded impressive results. The rural economy is interdependent with agriculture and is a component of the national economy. Any changes in the national economy will affect the rural economy. This economy level depends on environmental and economic resources, which aligns with the principles of resilient economic policies.
In this regard, Jiroft Plain, located in the western region of Jazmourian, with Halil-Rood passing through its center, encompasses more than 1400 villages. The rural economy in Jiroft and Anbarabad counties primarily relies on livestock farming and agriculture. Economic reconstruction and transformation are taking place in all sectors of the world, and the villages of Jiroft Plain also need to manage and update their economic activities to keep up with global and national developments. Traditional activities are not sufficient to meet the needs of the younger generation. Therefore, the present research aims to analyze the economic situation of villages in terms of resilient economic indicators within the study area and seeks to answer the following question: How is the economic situation of villages in Jiroft Plain in terms of resilient economic indicators? Moreover, what effects do resilient economic indicators have on the rural economy?

 Methodology
The present study employed a descriptive-analytical method to provide a concrete, realistic, and systematic description of the characteristics and features of the studied villages in the Halil-Rud geographical-cultural area and Jiroft plain. Both library research methods and field research methods were utilized to gather information. The geographical scope of this research includes the cities of Jiroft and Anbarabad in Kerman Province. Considering the large number of villages in these two cities, as recognized by experts and professionals in this field, the sample villages were selected as the centers of rural districts. Therefore, the statistical population consists of household heads in the central villages of the rural districts, which according to the 2016 census conducted by the Statistical Center of Iran, have a population of approximately 41,289 individuals and 12,165 households, encompassing around 21 villages. Based on Cochran's formula, a sample size of 314 households was selected for the research and used for data collection. A systematic sampling method was employed to select households in each village.
Furthermore, a questionnaire was developed to examine the rural economy in detail from the perspective of resilience indicators, covering 11 different indicators and components. This questionnaire was administered to the sample population, and after completing 30 questionnaires, the reliability of the questionnaire was determined with a Cronbach's alpha coefficient of 0.780, indicating high reliability. Additionally, data analysis was conducted using Kruskal-Wallis, one-sample t-test, and regression analysis.

Discussion and conclusion
The research results regarding the status of resilience indicators with a rural economic approach revealed that the economic mobility and dynamism indicators scored 12.01, while social justice scored 3.31, indicating a moderate to high level. Other resilience indicators in the study area were estimated to be below the desirable numerical value of 3, indicating a moderate to low status. Furthermore, among the sample villages, Aliabad ranked first with an average rank of 253, followed by Dovlatabad with an average rank of 210, Hossainabad Dehdar with an average rank of 205, and Ismaili Sofla with an average rank of 179. This finding indicates that villages with a larger population and diverse economies tend to have higher resilience indicators. Based on this, over 52% of the villages in the study area do not have a desirable status in terms of the examined indicators, while only over 16% are in a desirable state.
The rural community's ability to withstand and recover from challenges has been achieved through various means. These include economic growth, increased production in agriculture, industry, and services, ensuring fair distribution of services to rural residents, creating more job opportunities, controlling inflation, improving welfare, supporting a knowledge-based economy, paying attention to scientific aspects of rural economics, engaging educated individuals in rural affairs, encouraging participation in village-related matters and meetings, providing a platform for criticism and suggestions to Islamic councils, cooperating with officials, improving access to basic services for all residents, increasing migration rates, and more. All these measures contribute to the sustainability of the rural economy, including employment, investment, productivity, income, and other production factors in the study area.


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