伊朗村民改造农村住房倾向的影响因素研究

A. Anabestani, Mojtaba Rousta, SeyyedMostafa HedayatnejadKashi, Tina Esmaieli
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引用次数: 0

摘要

本研究是一项应用描述分析法的研究,目的是分析农村住宅改造的影响因素。我们的统计范围包括Jahrom县郊区Simekan区的11个村庄,这些村庄从住房基金会获得了50多件贷款。为估计农村家庭层面的样本量,采用Cochran抽样法,以95%的准确率对186人(家庭监护人)进行了简单随机抽样调查。然后,通过调查和问卷收集必要的信息。根据因子分析结果,在前两个因子的有效性比例排序中,第一因子(农村宅基地满意度)单独描述了57.455%的方差,第二因子(宅基地改造)单独描述了20.835%的方差。此外,调查还发现,改造农村住宅的最佳理由是利用农村住宅设施(67%)。防止地震、洪水等自然灾害(33%)是进行房屋改造的另一个原因,因此我们的主要假设得到支持。根据假设检验的结果,根据Pearson相关系数和方差检验,我们的显著性数大于0.05,我们的自变量(性别,年龄和教育)与房屋改造之间没有显著性差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Examining the Effective Factors on Villagers’ Tendency to Retrofit Rural Housing in Iran
This research is an applied one with a descriptive – analytic method was conducted in Jahrom with the objective of analyzing the effective factors on retrofitting of rural homes. Our statistical universe includes 11 villages of Simekan district in the suburbs of Jahrom County, these villages have taken a loan over 50 items from Housing Foundation. For estimating the sample volume at rural family level, by using Cochran sampling method with 95 percent accuracy, the number of 186 persons (family guardian) was questioned by simple random sampling method. Then, the necessary information was gathered by survey and questionnaire. Based on the results of factor analysis, among the first two factors in the order of effectiveness proportion, the first factor (satisfaction with rural homing) describes 57.455 percent of variance by itself and the second factor (homing retrofitting) is accounted for 20.835 percent of variance. Also, it was found that the best reason for retrofitting of rural homes is using of rural homing facilities (67%). Safety against natural disasters such as earth quake and flood (33%) is another reason for homing retrofitting, so our main hypothesis is supported. According to the results of hypothesis testing, based on Pearson correlation coefficient and regarding to variance testing and our significance number which is more than 0.05, there isn’t a significant difference between our independent variables (gender, age & education) and housing retrofitting.
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