Volume 13, Issue 50 (3-2024)
Haft Hesar J Environ Stud 2024, 13(50): 119-144 |
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Safavi Mirmahaleh S F, Rashid Kalvir H, Ebadollahi Chenzanegh H. Identifying and Measuring the Consequences of Reverse Migration On Rural Housing (Case Study: Villages in The Central Part of Masal City). Haft Hesar J Environ Stud 2024; 13 (50) :119-144
URL: http://hafthesar.iauh.ac.ir/article-1-2188-en.html
URL: http://hafthesar.iauh.ac.ir/article-1-2188-en.html
Abstract: (376 Views)
In continuation of the successive migrations of villagers to cities, today we see the return of city dwellers to villages under the name of reverse migration or city escape. This practice, which is not a new issue, unfortunately has gained intensity and a faster rate of growth today, and it must have had some effects on the villages, one of the most important of which is the changes in rural housing. In this regard, the main goal of the research is to identify and measure the consequences of reverse migration on rural housing with a case study of villages in the central part of Masal city. This mixed (qualitative-quantitative) research, which was carried out with a practical purpose and a combined method (exploratory and experimental), firstly, the primary factors extracted from the library study along with the factors calculated from 20 structured interviews; It was subjected to content analysis (CVR) by 10 experts and finally the final factors were evaluated in the form of a questionnaire by a statistical sample. In general, the statistical population of this research consists of villages in the central part of Masal city, which were selected as a statistical sample of 6 villages using a combined method. In particular, the statistical population of this research is divided into two qualitative and quantitative parts. In the qualitative part (interviews), experts and experts were chosen by a selective method and further by the snowball method and were questioned in a targeted manner (20 experts) and in the quantitative part (questionnaire), the statistical population of the research was rural residents who, using Cochran's formula determined the volume (352 residents of the studied villages) and randomly classified (proportionate to the population of each village) were sampled. Considering that the intended research is of a mixed type, therefore, data analysis was done in two stages. In the first stage, interviews were analyzed using MAXQDA software. In the second step, to analyze the validity of the questionnaire and finalize the identified effects, the CVR content analysis method was used, the Kornbach's alpha test was used to measure the reliability of the questionnaire, and the structural partial least squares (PLS) method was used to measure the effects of migration. In this regard, the results of the research show that more than half of the items counted (23 out of 45) refer to the physical changes of rural housing, but in terms of the repetition of indicators, according to the interviewees, we see dispersion in all dimensions. However, the issues and their repetition show the positive role of immigration in changing rural housing. Among the 45 items counted (the effects of immigration on rural housing), 25 items with a total of 100 repetitions are among the positive effects of reverse migration on rural housing, and on the other hand, 20 items with a total of 67 repetitions are among the negative effects of immigration on They are rural housing. Also, the results of the evaluation of the questionnaires also indicate the impact of migration on rural housing, such that about 68% of the statistical sample of the research (villagers) agreed that migration has caused changes in rural housing and the 14 investigated indicators together They explain 0.793 of the effects of migration on rural housing.
Keywords: Reverse Migration, Rural Housing, Partial Least Squares Structural Model, Villages of Masal City.
Type of Study: Research |
Received: 2023/12/20 | Accepted: 2024/04/23 | Published: 2025/03/30
Received: 2023/12/20 | Accepted: 2024/04/23 | Published: 2025/03/30
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