مطالب

Purpose - Spatial equilibrium at different stages, especially at the district level, is the most significant purpose of spatial development planning that is the focus of attention in Iran's policy and planning system. In this regard, spatial recognition and analysis of the components and the criteria of eligibility are significant in the context of the existing development concept. By identifying the eligibility components of rural settlements, it is possible to identify low eligibility of spatial areas affected by adverse socio-economic and spatial processes. Accordingly, the research team attempted to examine this criterion in the district of Khorramabad. Design/methodology/approach - The research method was descriptive-analytical. The statistical population was the villages of Khorramabad county (Given the frequency of a statistical population, 150 villages out of 647 were selected as the sample using stratified- random sampling. The required data (35 indices) were collected by the library method (using population and housing census and statistical yearbook of 2016). Data analysis was done using FANP model (for summarizing the indices and determining their weight), VIKOR technique (for ranking the villages), and finally, path analysis test for determining the influence degree of the factors on the level of development. According to the research findings, the following results were obtained; Finding - The process of development in Khorramabad county, is in relatively in good condition. In this process, Integrated development has not been considered. Some components (access to services, economic participation and, economic welfare) are in good conditions while some other components (agricultural production, education and population growth) are not. These conditions resulted in a decline in some villages. The level of development in Khorramabad county has been confronted with spatial inequality not just in terms of topic-specific but an area-specific aspect. This inequality resulted in the formation of the center-periphery spatial pattern that causes the marginalization (and deterioration) of disadvantaged villages.

One of the significant problems of banks and investors in Iran is the lack of precise awareness about the financial performance of each bank and the roadmap for improving the conditions. Besides, the undesirable status of the financial performance of banks becomes evident only when the improvement of conditions is complicated. In this paper, a data mining-based early warning system (EWS) model has been presented to capture the financial performance of banks. To design this model, the CHAID decision tree has been used. Using this model, the banks have been classified as poor, medium, and good regarding financial performance, and the roadmap to achieving the desirable status has been determined. For this purpose, 13 Iranian banks have been investigated within the years 2003-2017. Eventually, the results obtained from the decision tree have been compared with the findings achieved from the CAMELS model. Based on the designed decision tree, 8 profiles have been extracted; 2 representing good, 3 medium, and 3 poor financial performance. Based on these profiles, according to the latest reports published by the studied banks, eight banks have a mediocre financial performance while five banks suffer poor financial performance. According to these profiles, four variables of the asset to shareholders’ equity ratio, the shareholders’ equity to loans ratio, the long-term debt to equity ratio, and liquidity coverage ratio were identified as the most relevant variables associated with the financial performance of banks.