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طرح مسئله- امروزه رهیافت رشد هوشمند نقش بسیار مهمی در توسعه پایدار روستایی دارد. این رویکرد تلاش می کند، کیفیت زندگی انسان ها را ارتقا دهد، درصدد پاسخگویی به مسائل و مشکلات اجتماعی- اقتصادی، زیست محیطی و کالبدی و راهگشای مدیریت روستایی برای استفاده بهینه از امکانات و حل معضلات روستایی است. درواقع رهیافت رشد هوشمند مسیری را برای برون رفت از ناپایداری و رسیدن به توسعه پایدار در نواحی روستایی فراهم می کند. هدف- هدف این پژوهش، بررسی وضعیت مؤلفه های رشد هوشمند در سکونتگاه های روستایی شهرستان جیرفت است. روش- داده های موردنیاز با استفاده از پرسشنامه جمع آوری و برای تجزیه و تحلیل از نرم افزارهای مختلف استفاده شد. این پژوهش بر پایه روش توصیفی – پیمایشی و ازنظر هدف، کاربردی است. برای گردآوری اطلاعات روش های اسنادی و میدانی به کار رفت. جامعه نمونه این پژوهش، ساکنان 18روستای بالای 1000 نفر جمعیت شهرستان جیرفت از توابع استان کرمان است. در این بین، براساس فرمول کوکران، از بین 12131 خانوار، تعداد 261نفر انتخاب و با روش تصادفی از آنها نظرسنجی شد. برای دستیابی به اهداف پژوهش، از نرم افزارهای SPSS، AHP، GRA و GIS استفاده شد. نتایج- براساس نتایج به دست آمده از مدل ساختاری PLS، بعد حمل ونقل و ارتباطات (723/0) دارای بیشترین اثرگذاری بر شکل گیری رشد هوشمند در محدوده موردمطالعه بوده است. بعد از آن به ترتیب شاخص های بهبود بافت کالبدی، ارتقای کیفیت محیطی، پایداری اجتماع محلی، پایداری اقتصاد محلی، ارتقای کیفیت مسکن و تراکم و توسعه فشرده با 715/0، 707/0، 706/0، 704/0، 626/0 و 459/0 قرار می گیرند. نتایج تحلیل فضایی نشان دهنده آن است که بیشترین میزان رتبه سکونتگاه های روستایی به لحاظ بهره مندی از شاخص های رشد هوشمند متعلق به روستاهای علی آباد، دولت آباد، دوبنه، حسین آباد دهدار، اسماعیلی سفلی و گلاب صوفیان سفلی و روستاهای طرج، کنار صندل، نارجو و سغدر دارای کمترین رتبه به لحاظ بهره مندی از شاخص های رشد هوشمند است. به طور کلی نتایج ارائه شده نشان دهنده آن است که رهیافت رشد هوشمند تأثیر مثبت و معناداری در توسعه پایدار سکونتگاه های روستایی داشته است. نوآوری- در پژوهش حاضر برای اولین بار به موضوع مؤلفه های مؤثر بر شکل گیری رشد هوشمند در توسعه پایدار سکونتگاه های روستایی با استفاده از مدل های کاربردی توجه شده است.

The Roles of the Main Components of the Formation of Smart Growth Approach in the Sustainable Development of Rural Settlements: A Case Study of Jiroft County

Abstract Problem definition: Today, smart growth approach has an extremely important role in rural sustainable development. This approach aims at improving the quality of human life and responding to social-economic, environmental, and physical problems. It can pave the way for rural management, optimal use of facilities, and solve rural problems. Indeed, the smart growth approach can provide a way out of instability and achieving sustainable development in rural areas. Purpose: The aim of this study was to investigate the status of smart growth components in the rural settlements of Jiroft County. Methodology: The required data were collected by using a questionnaire and various pieces of software were used to analyze them. This research was based on a descriptive-survey method with an applied purpose. Also, documentary and field methods were utilized to collect the information. The sample population of this research included the residents of 18 villages with a population of more than 1000 people in Jiroft County in Kerman Province. Using Cochran's formula, 131 households and 261 people were selected and randomly surveyed. To achieve the research objectives, SPSS, AHP, GRA, and GIS software was applied. Results: Based on the results obtained from the structural model of Smart PLS, transportation and communications (0.723) had the greatest impacts on the formation of smart growth in the study area. Afterwards, the indicators of physical texture improvement, environmental quality improvement, local community sustainability, local economic sustainability, quality of housing, and compact development were ranked with 0.715, 0.707, 0.706, 0.704, 0.626, and 0.459. The results of spatial analysis showed that the highest ranks of rural settlement were related to the villages of Aliabad, Dolatabad, Dubneh, Hosseinabad Dehdar, Ismaili Sofla, and Gulab Sufian Sofla and the lowest ranks were related to the villages of Tarj, Kenar Sandal, Narjo, and Soghdar based on the intelligent growth indicators. In general, the results revealed that the smart growth approach had a positive and significant effect on the sustainable development of the studied rural settlements. Innovation: In the present study, for the first time, the issue of effective components on the formation of home-grown growth in the sustainable development of rural settlements was addressed by using applied models.   Introduction It is important to use and expand the smart growth approach in rural areas due to the key roles that villages as the sources of migration have in affecting food security and population, in the current situation and because of the disturbances caused by the unplanned growth of rural population and physical expansion of rural settlements. The rural environment created in recent decades has increased the need to pay attention to villages like Jiroft County, which is now experiencing excessive migration of its young and educated people to the cities. This issue has subsequently led to emptying of villages and non-realization of their high-quality agricultural lands, which can supply a significant amount of the country's food needs. Therefore, to achieve sustainable development, especially in rural areas, the smart growth strategy and its indicators should be studied and analyzed. Therefore, the current research aimed to determine the roles of the main components of the smart growth approach in the sustainable development of rural settlements. Based on this, the main question of the research was raised: What status do the smart growth indicators have in the studied rural settlements?   Research Method The current research was of an applied type based on its purpose and descriptive-analytical based on its nature. Its aim was to investigate the roles of the components of the smart growth approach in the sustainable development of the studied rural settlements. The statistical population of this research included all the rural areas of Jiroft County. The sample villages were selected according to their number of residents with regard to the premise that the smart growth infrastructure possibly occurs in large villages. Thus, the sample group was selected from the villages with more than 1000 people. Also,  the method of multistage cluster sampling was used. In the first stage, from among the 14 districts of Jiroft County according to the census of 2015, 11 villages were selected as the cluster samples. After randomly selecting a number of the villages from each cluster, the desired samples were totally collected. According to the census of 2015, this county had 30 villages (2, 21, and 7 villages in Jabalbarz, Markazi, and Ismaili districts, respectively) with more than 1000 inhabitants, . Cochran's formula was used to randomly determine the sample size, which finally included 18 villages, with an accuracy coefficient of 0.05 and variance of 0.15 at the confidence level of 95%. Also, according to this formula, 261 households were selected and randomly questioned. To choose appropriate tests for analyzing the findings, the "Kolmogorov-Smirnov test" was used. The significance level for all the dependent and independent variables was greater than 0.05. Since the data had a non-normal distribution, the PLS structural equation model was applied to analyze the relationship between the dependent and independent variables. Also, the SPSS statistical software and Gray model were employed to analyze the data.   Discussion & Conclusion Sustainable development indicators can be improved through smart rural growth that offers options for housing, transportation, jobs, and amenities, including social, cultural, recreational, and educational services. This research was carried out with the aim of determining the roles of the main components of the smart growth approach in the process of rural sustainable development in the rural settlements of Jiroft County. The test results of the research question showed that the t-statistic value was greater than 1.96 at the significance level of p=0.000. Therefore, there was a positive and significant relationship between the indicators of smart growth and sustainable development. Using the PLS path analysis model, the effects of smart growth indicators as the independent variables on the sustainable development of rural settlement as a dependent variable were investigated. Their impacts on the sustainable rural development of the studied areas showed that the indicators of improvement of physical texture, improvement of environmental quality, sustainability of local community, sustainability of local economy, improvement of housing quality and density, and intensive development had the ranks of 0.715, 0.707, 0.706, 0.704, 0.626, and 0.459, respectively. Based on the spatial analysis of the smart growth indicators and according to the results of field interviews and the questions raised in this field, the highest and lowest ranks of rural settlements were related to Aliabad, Daulatabad, Dobneh, Hossein Abad, Dehdar, Ismaili Sofla, and Gulab Sufian Sofla villages and Tarj, Kenar Sandal, Narjo, and Soghdar villages, respectively. It could be said that the villages with more populations were in a better situation in terms of satisfying the smart growth indicators. This finding was in line with the results obtained by Tregear & Cooper (2016), who believed that smart growth can help making rural settlements more livable with sustainable economic development, creating diverse and affordable housing options, and maintaining ecological, social, economic, and physical sustainability, thus having a significant effect on rural communities. Also, it was in line with the research done by Datta et al. 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(In Persian)   Figures and Tables - Fig. 1: Conceptual framework of the research - Fig. 2: Location of the study area - Table 1: Details of the studied villages and the number of samples in each village - Table 2: Components and indicators of intelligent growth and its reliability - Table 3: Demographic characteristics of the respondents in the study area - Table 4: Evaluation of intelligent growth indices in the study area using one-sample t-test - Table 5: Spatial analysis of the status of intelligent growth indicators in the studied villages - Table 6: Ranking of the smart growth indicators at the village level using spatial analysis - Table 7: Ranking of the studied villages based on the effective components of intelligent growth in the process of sustainable development - Fig. 3: Ranking of the studied villages based on the smart growth indicators - Table 8: Evaluation of the measurement model - Fig. 5: Structural model with standard coefficients - Fig. 5: Structural model with the absolute value of significant coefficients (t-value) - Table 9: Results of the structural model of the research

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