تحلیل ساختاری مؤلفه های مؤثر بر پایداری اجتماعی- اقتصادی مناطق روستایی استان ایلام

Abstract

Today, considering the position and role of rural society in the balanced development of the country and also considering the issues and problems that this society is facing, it seems necessary to pay attention to rural sustainability. The issue of socio-economic sustainability is one of the important issues in relation to rural areas. These two dimensions of sustainability, due to more attention to the components of environmental sustainability, have been largely overshadowed by it and have been less independently studied. Therefore, the purpose of this study is to analysis the structural components affecting the socio-economic sustainability of rural areas in Ilam province using spatial analysis in GIS for sampling, among 378 villages with more than 20 households, 37 villages were selected as a sample and 250 questionnaires were completed by the villagers. The research method in this article is descriptive-analytical and for data collection were used of two methods field ‌ libraries. Also, data analysis was performed by one-sample t-test in SPSS software and Structural Equation Modeling approach in PLS software. The results of one-sample t-test show that the component of social participation with an average of 3.1646, is above average 3 and other research components are average or below. The results of structural equation modeling show that the obtained T values for all paths are greater than 1.96, therefore, the relationship between higher level structures with lower level structures is significant. Also overall results show that social sustainability has a more important role in creating overall sustainability than economic sustainability.



Introduction

In the current situation, it becomes more necessary to pay attention to social and economic sustainability, taking into account the challenges and bottlenecks facing developing countries and in the meantime, rural areas are facing many problems. A significant share of rural instabilities goes back to socio-economic instability, which in addition to deteriorating employment, income, inequality of opportunity, access to services, basic needs and the like, also have negative feedback on environmental sustainability. Due to these instabilities, rural areas are experiencing consequences such as urban-rural inequalities, population evacuation, migration and environmental degradation. Economic sustainability and social sustainability are two inseparable components, because individual welfare is not separate from the welfare of society and the existence of social cohesion, empathy, tolerance leads to the creation of space which people feel more responsible and believe that a fairer distribution of resources plays a key role in the long-term survival of society.



Methodology

The type of research is applied and in terms of nature and descriptive-analytical method. To analyze the data were used from Inferential statistical methods (one-way analysis of variance and Tukey test). The statistical population of this research uses spatial analysis in GIS for sampling( Using the adjacent layers raster to the province's permanent rivers, settlement density, rural population density, distance from the road, distance from the nearest cities, the province's land layer, slope and height and their overlap in the final raster and placing the whole province in Three classes are high, middle, low and select villages according to their placement in the final raster) Out of 378 villages with more than 20 households, 37 villages were selected as a sample and 250 questionnaires were calculated and randomly completed by the villagers in the period 1399-1399.



Results and Discussion

Numerical mean analysis obtained from the calculation of components affecting socio-economic sustainability in rural areas was obtained among the respondents using questionnaire data.To investigate this issue was used from single-sample t-test, which the component of social participation with an average of 3.1646, was higher than the average (3). Also, the analysis of research data with the structural equation modeling approach in PLS software is includes the study of model fit in three parts: measurement model, structural model and general model. Measurement models show the relationship between each of the hidden variables and its indicators. To evaluate the measurement models, the reliability and validity of the variables are checked. After testing the measurement models, it is necessary to evaluate the structural model of the research that shows the relationships between the variables. For this purpose, are examined the coefficient of determination (R2) and the predictive power of Stone and Geiser (Q2). After evaluating the measurement and structural models of the research, is examined the fit of the overall model. The GoF criterion is used to evaluate the fit of the overall model. Finally, the results show that according to the results of t and the significance of path coefficients in PLS software, social stability has a more important role in creating overall stability than economic stability.



Conclusion

The results of one-sample t-test show that the component of social participation with an average of 3.1646 is higher than the average (3), so it has the greatest impact on the stability of the region.. Cronbach's alpha values of the research variables are in the range of 0.72-0.92 and the combined reliability values of the variables are in the range of 0.82-0.93. Therefore, is confirmed the reliability of all research variables. AVE values for all research were obtained variables greater than or equal to 0.5. Therefore, the variables have good convergent validity. After testing the measurement models, it is necessary to evaluate the structural model of the research that shows the relationships between the variables. For this purpose, are examined the coefficient of determination (R2) and the predictive power of Stone and Geiser (Q2). According to the results, the values of R2 and Q2 for all research variables are at a high level. Therefore, the structural part of the research model has a strong fit. After evaluating the measurement and structural models of the research, was examined the overall model fit and the GoF criterion was used to evaluate the overall model fit. Achieving a value of 0.69 for GoF is means a strong fit of the overall research model. Also, the results obtained from Student t test and the significance of path coefficients show that the t-values obtained for all paths are greater than 1.96, Therefore, is significant the relationship between higher level structures and lower level structures.