Spatial Analysis of the Effects of Lar Cement Factory on Regional Development with Resilient Approach )Case study: Roudab section of Sabzevar city)
Article Type:
Research/Original Article (دارای رتبه معتبر)
The program of this study was to investigate the spatial analysis of the effect of Lar Cement Factory in the Roudab section of Sabzevar city, with a resilient approach. The type of applied research and its method is descriptive-analytical. To collect the required information in the theoretical part of the library method, fieldwork and questionnaire tools were used to collect the required data. At first, the effects of the construction of the factory in the department were identified and then the effects of the resilience approach were placed in four dimensions and a questionnaire was designed. The reliability of the questionnaire was evaluated using the views and opinions of the experts and experts and the validity of the questionnaire was calculated using Cronbach's alpha (0.94). The statistical population of the Roudab section of Sabzevar City in Khorasan Razavi province and the sample size were estimated by calculating the Cochran formula 365. The method of random sampling was simple. In this research, for analyzing the data in the descriptive statistics section of the mean and in the inferential statistics, multivariate linear regression was used in SPSS software as well as standardized modeling of structural equations in Lisrel software environment. The level of resilience of Lar Cement Factory in the sector of different dimensions and indicators was measured by analyzing the questionnaires and required calculating. According to the results, the average of the effects of the factory in various dimensions with a mean total of 3.07 affects the sector's resiliency. The results of the standardized structural equation modelling test showed that the established factory had the most impacts on the social dimension of resilience, the economic dimension of resilience, physical and, eventually, physical dimensions of resilience respectively. The results of linear regression show that the investigated effects explains 98% of the sector's resiliency.
Quarterly of Geography (Regional Planing), Volume:9 Issue: 2, 2019
393 - 408  
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