Village and Development

Village and Development

Investigating the Impact of Social Capital Components on Rural Waste Management (Case Study: Villages of the Padena District of Semirom County)

Document Type : Original Article

Authors
A.R. Alipour 1
S.Sh. Mousavi 2
M.S. Ebrahimi 3
1 Assistant Professor, Department of Rural Development, College of Agriculture, Isfahan University of Technology, Isfahan, Iran.
2 MSc Graduate, Department of Rural Development, College of Agriculture, Isfahan University of Technology, Isfahan, Iran.
3 Associate Professor, Department of Rural Development, College of Agriculture, Isfahan University of Technology, Isfahan, Iran.
10.30490/rvt.2024.367012.1621
Abstract
Introduction
The expansion of villages in the last few decades has caused significant changes in the quality and quantity of rural waste. Rural waste not only leads to diseases but also results in unpleasant odors, unsightly rural landscapes, and pollution of water, soil, and air in the village environment, adversely affecting rural residents. According to the Demographic Data Organization statistics, Iran ranked 17th globally in waste production in 2021. The per capita waste production in Iran is approximately double the global average. Despite the Public Service Department of Rural Affairs of Iran reporting that 10,000 tons of regular wastes are generated daily in the country's villages, half of which cannot be recycled, emphasizing the importance of optimal rural waste management and identifying effective components in this area.
Materials and Methods
This study evaluated the impact of social capital components on rural waste management in villages of the Padena district (Semirom County). Data were collected using a questionnaire in 2024. The questionnaire's validity was confirmed by a panel of experts, and its reliability was assessed using Cronbach's alpha test. Pearson's correlation coefficient was employed to analyze the relationship between social capital components and rural waste management behavior in the study area. The artificial neural network was utilized to identify the most crucial social capital component in rural waste management. Lastly, a stepwise multivariate regression method was used to assess the statistical significance of social capital components in influencing waste management behavior and identify key predictor components.
Results and Discussion
The Pearson correlation analysis revealed a positive correlation between various dimensions of social capital and waste management at a significant confidence level, indicating a strong relationship between social capital and effective rural waste management in the region. The study found that the social ethics component, with an importance coefficient of 0.22 and a relative importance of 100%, was relatively more critical in rural waste management behavior than other social capital components. Social trust was identified as the second most important component in waste management behavior. Among the social capital components, only ethics and social participation had a positive and significant impact on rural waste management in the study area. These two components should be considered as predictive variables in waste management behavior, with each unit increase in social ethics leading to a 1.41 unit improvement in waste management behavior, and each unit increase in social participation contributing 0.75 units to improved waste management behavior.
Conclusions
The study highlights the importance of adhering to social ethics and positive characteristics such as respecting others' rights, social responsibility, empathy, solidarity, and participation in social activities in rural waste management. The results emphasize the need for planning and policy-making to enhance ethics and social participation in optimal rural waste management through educational workshops and financial incentives in rural areas.
Keywords
Rural Waste
Social Network
Social Capital
Artificial Neural Network
Semirom

Subjects

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