تحلیل علل نابرابری های توسعۀ فضایی استان کهگیلویه و بویراحمد (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
هدف از این پژوهش سطح بندی مناطق شهری شهرستان های استان کهگیلویه و بویراحمد و تعیین اولویت توسعه شهرستان ها در استان و اولویت هر عامل در هر شهرستان است. این پژوهش با استفاده از 84 شاخص مختلف ترکیب شده در spss به 8 عامل؛ اشتغال و فعالیت، مسکن، اقتصادی - تولیدی، حمل ونقل 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. جامعه 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 مؤلفه های اصلی در مدل سازی معادلات ساختاری 364 نفر برآورد گردید. روایی پرسش نامه به صورت روایی صوری و ظاهری و پایایی پرسش نامه از آلفای کرونباخ استفاده شد، مورد تأیید قرار گرفت. یافته های پژوهش حاکی از آن است که شهرستان های؛ بویراحمد، دنا و گچساران در رتبه های اول تا سوم و شهرستان بهمئی در رتبه آخر توسعه یافتگی قرار داشته است. بر اساس مدل ساختاری تأییدشده چهار مؤلفه؛ صنعتی - تولیدی، اشتغال، خدمات عمومی - شهری و حمل ونقل 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 داشته اند. اولویت توسعه فضایی در برنامه ریزی های استان می بایست به ترتیب شهرستان های؛ بهمئی، چرام، کهگیلویه، باشت، گچساران، دنا و بویراحمد با ترتیب اولویتی بخش های؛ صنعتی - تولیدی، اشتغال، خدمات عمومی - شهری و حمل ونقل و ارتباطی، باشد.Analysis of the Causes of Spatial Development Inequalities in Kohgiluyeh and Boyer-Ahmad Province
The purpose of this research is to stratify the urban areas of Kohgiluyeh and Boyer Ahmad provinces and to determine the priority of the development of the cities in the region and the priority of each factor in each city. This research uses 84 different indicators combined in spss into 8 factors; Employment and activity, housing, economic production, transportation and communication, public urban services, health and treatment, book literacy and education related to the statistics of 2015, using two techniques; Morris and confirmatory factor analysis has been done. The statistical population of the research is the urban areas of seven cities (17 cities) of the province. The statistical population in the department related to the identification of research factors were experts and university professors at the province level, and the sample number was estimated to be 364 people using the principle of principal component analysis in structural equation modelling. The validity of the questionnaire was confirmed by using the face and face validity and reliability of the questionnaire using Cronbach's alpha. The research findings indicate that Boyer Ahmad, Dena, and Gachsaran cities are in the first to third ranks, and Behmai City is in the last rank of development. Based on the approved structural model of four components; Industrial-manufacturing, employment, public-urban services, and transportation and communication have had a more significant impact on development inequality with coefficients of 0.71, 0.62, 0.54, and 0.51, respectively, compared to other variables. The priority of spatial development in the planning of the province should be in the order of the cities; Behmai, Cheram, Kohgiluyeh, Bashet, Gachsaran, Dena and Boyer Ahmad with the priority order of the sections; industrial-production, employment, public-urban services and transportation and communication.
Extended Abstract
Introduction
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.
Methodology
The 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 discussion
Findings 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.
Conclusion
This 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.
Funding
There is no funding support.
Authors’ Contribution
All of the authors approved thecontent of the manuscript and agreed on all aspects of the work.
Conflict of Interest
Authors declared no conflict of interest.
Acknowledgments
We are grateful to all the scientific consultants of this paper.
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