چکیده:
شناسایی وضع موجود مناطق، اساسیترین موضوع در برنامهریزی توسعهی فضایی منطقهای به شمار میرود که مستلزم تجزیهوتحلیل بخشهای اقتصادی، اجتماعی – فرهنگی است. لذا نحوهی بخشایش امکانات و خدمات با بررسی تطبیقی شاخصهای مختلف برنامهریزی در مناطق مختلف نسبت به همدیگر روشن میشود. هدف از این پژوهش سطحبندی مناطق شهری شهرستانهای استان کهگیلویه و بویراحمد و تعیین اولویت توسعهی شهرستانها در استان و اولویت هر عامل در هر شهرستان است. این پژوهش با استفاده از 84 شاخص مختلف ترکیبشده در spss به 8 عامل؛ اشتغال و فعالیت، مسکن، اقتصادی – تولیدی، حملونقل و ارتباطی، خدمات شهری عمومی، بهداشت و درمان، کتاب - سواد و آموزشی مربوط به آمار سال 1395، با استفاده از دو فن؛ موریس و تحلیل عاملی تأییدی صورت گرفته است. جامعهی آماری پژوهش مناطق شهری هفت شهرستان (17 شهر) استان است. جامعه آماری در بخش مربوط به شناسایی عوامل پژوهش، کارشناسان و اساتید دانشگاه در سطح استان بودند که تعداد نمونه با استفاده از قانون تحلیل مولفه-های اصلی در مدل سازی معادلات ساختاری 364 نفر برآورد گردید. روایی پرسشنامه بهصورت روایی صوری و ظاهری و پایایی پرسشنامه از آلفای کرونباخ استفاده شد، مورد تایید قرار گرفت. یافتههای پژوهش حاکی از آن است که شهرستانهای؛ بویراحمد، دنا و گچساران در رتبههای اول تا سوم و شهرستان بهمئی در رتبهی آخر توسعهیافتگی قرار داشته است. بر اساس مدل ساختاری تائید شده چهار مؤلفه؛ صنعتی – تولیدی، اشتغال، خدمات عمومی - شهری و حملونقل و ارتباطی به ترتیب با ضرایب 71/0، 62/0، 54/0 و 51/0 در نسبت به سایر متغیرها بر نابرابری توسعه تأثیر بیشتری داشتهاند. اولویت توسعهی فضایی در برنامهریزیهای استان میبایست به ترتیب شهرستانهای؛ بهمئی، چرام، کهگیلویه، باشت، گچساران، دنا و بویراحمد با ترتیب اولویتی بخشهای؛ صنعتی – تولیدی، اشتغال، خدمات عمومی – شهری و حملونقل و ارتباطی، باشد.
The most critical threats are facing Kohgiluyeh and Boyer-Ahmad province, including extensive migration of villagers, nomads and even residents of small towns of the province to Yasuj and its suburbs; lack of quantitative and qualitative development of human capital in the province; inability to maintain skilled workers and economic activists; severe shortage and even lack of commercial and economic infrastructure and the infrastructure; and in short, the low level of all indicators in the small cities of the province and the low level of these indicators compared to other provinces, which doubles the need to recognize the differences and review the development planning policies of the province. The results of this research can be used in future planning and in order to allocate financial and physical resources in the province. Therefore, considering the above, the importance of ranking, measuring, and prioritizing the level of development of counties’ urban areas of Kohgiluyeh and Boyer-Ahmad province are more visible, and these questions are raised:-What is the situation of each city in each factor (set of indicators)? -Has the current distribution and service model caused disproportion and imbalance in the urban and regional system of the province? Therefore, special attention and planning for this developing province, prone to development and understanding the extent of development of its urban areas to allocate resources better and create justice, balance, and proportion in this area seem necessary.MethodologyThe method used in the research is descriptive-documentary and quantitative-analytical, so the study is part of applied research. The statistical population of the study is 16 cities and 7 counties of Kohgiluyeh and Boyer-Ahmad province in 2016. Based on 84 indicators extracted from the results of the 2016 census of the Statistics Center of Iran, their combination and reduction to eight factors, and using two Morris techniques and confirmatory factor analysis, the counties of the province were graded and compared.Results and discussionFindings showed that in the employment factor of counties, Basht, Gachsaran, and Bahmaei were in the first to third ranks, and Boyer-Ahmad and Dena counties were in the last ranks. Boyer-Ahmad, Gachsaran, and Charam were in the first to third ranks in the urban housing factor, and Basht and Bahmaei were in the last ranks. In the economic-productive factor of counties, Gachsaran, Kohgiluyeh, and Boyer-Ahmad were in the first to third ranks, and Charam and Bahmaei were in the last ranks. In urban transportation and communication factor, Boyer-Ahmad, Gachsaran and Kohgiluyeh were in the first to third ranks, and Basht and Bahmaei were in the last ranks. In counties' urban public service agents, Dena, Boyer-Ahmad, and Charam were in the first to third ranks, and Gachsaran and Bahmaei were last. Dena, Boyer-Ahmad, and Kohgiluyeh were in the first to third ranks in the urban health factor, and Charam and Gachsaran were in the last ranks. In the book and urban literacy factor; Boyer-Ahmad, Gachsaran, and Dena were in the first to third ranks, and Bahmaei and Kohgiluyeh counties were in the last ranks, and finally, in the educational factor of the counties, Basht, Charam, and Dena were in the first to third ranks, and Gachsaran and Bahmaei were in the last ranks.ConclusionThis study aimed to identify the spatial inequality prevailing in the counties of the studied province and investigate the effect of the studied factors and indicators on spatial inequality. Based on the results obtained from the Morris technique of the counties, Boyer-Ahmad, Gachsaran, and Dena were in the first to third ranks, and Bahmaei was in the last rank. In terms of the level of development of counties, Boyer-Ahmad, Gachsaran, and Dena are at the level of near development, Basht is improving, and Kohgiluyeh, Charam, and Bahmaei are deprived and lacking. Therefore, the priority of spatial development in the planning of the province should be focused on Bahmaei, Charam, Kohgiluyeh, Basht, Gachsaran, Dena and Boyer-Ahmad counties based on industrial-production, employment, public-urban services and transportation and communication sectors. According to the approved structural model, the four components of industrial and production, employment, public and urban services, and transportation and communication with coefficients of 0.71, 0.62, 0.54, and 0.51, respectively, have a significant effect on inequality development than other variables. Considering that all coefficients within the structural model are significant and the model fit indices are optimal, so the research model is approved.According to the approved structural model, the four components of industrial and production, employment, public and urban services, and transportation and communication with coefficients of 0.71, 0.62, 0.54, and 0.51, respectively, have a significant effect on inequality development than other variables. Considering that all coefficients within the structural model are significant and the model fit indices are optimal, so the research model is approved.