Modeling the Social Sustainability in Rural Communities of Developing Countries (case study: Bilevar Plain; Kermanshah Province)

Document Type : Research Paper


1 Ph.D. Candidate, Department of Agricultural Extension and Education, Razi University, Kermanshah, Iran.

2 Associate Professor, Department of Agricultural Extension and Education, Razi University, Kermanshah, Iran.

3 Assistant Professor, Department of Agro-Bio-Tech, Liege University, Gembloux, Belgium.

4 Full Professor, Department of Agroecology, Shahid Beheshti University, Tehran, Iran.

5 Assistant Professor, Department of Industrial Engineering, Kermanshah Univeristy of Technology, Kermanshah, Iran.

6 Full Professor, Department of Geography, Ghent University, Ghent, Belgium.


Purpose: Understanding how rural communities meet their needs and enhance their well-being while promoting social cohesion, equitable access to resources and services, and fostering community resilience is of utmost importance when investigating the social sustainability of rural areas. Social dimensions often receive inadequate attention during the appraisal of rural development projects. Consequently, the main aim of this study is to create social sustainability indexes that can effectively support the evaluation of sustainable rural development.
Methods: To achieve this aim, a proposed methodology is presented, which utilizes Confirmatory Factor Analysis (CFA) to estimate the coefficients of indexes about rural social sustainability (RSS). This approach constructs a Structural Equation Model (SEM), offering insights into the potential of these indexes for driving long-term improvements in social sustainability within rural areas.
Results: The results of the CFA analysis show the variables of quality of life (QOL), social participation (SP), and social responsibility (SR) enhance the sustainability of rural, and the positive effect is more prominent among rural areas that had high social solidarity. Moreover, the construct validity of RSS-SEM model was (P = 0.166, Chisquare/df = 1.229IFI = 0.971, CFI = 0.969, NFI = 0.861, and RMSEA = 0.054).
Conclusion: The application of the SEM (Social-Economic-Environmental) model is recommended for assessing rural projects as it provides a comprehensive framework that complements environmental and economic sustainability assessments. By incorporating social factors into project evaluations, the SEM model enables a more holistic understanding of rural development's social, economic, and environmental dimensions, ultimately contributing to more effective and sustainable outcomes.


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