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Responsible Citizen Behavior Modeling in Urban Waste Management (Case study: Roodehen city)

Year: 2025
Type: article
Abstract: Identifying factors affecting citizens' responsible behavior in the field of waste generation can provide insights for urban planners for policymaking and improving waste management practices. The aim of the present study is to identify the factors affecting citizens' responsible behavior in waste management. This study is exploratory in purpose and applied-developmental in nature. The study site in this research was the city of Arak in Markazi Province. In the qualitative section, related studies were reviewed using MAXQDA software, and the model's factors and items were identified and categorized. These factors were then evaluated through content validity and reliability testing using the Kappa coefficient. In the quantitative section, the designed model was validated using expert opinions and a Likert-scale questionnaire. Smart PLS software was used for data analysis. The study's findings identified seven components and twenty-three items, including economic and financial motivations, culture and media, social, legal, infrastructure, environmental and waste literacy, and individual and psychological characteristics, as influential factors in responsible waste management behavior. The Kappa coefficient, with a value of 0.95, confirmed the model's reliability. Additionally, the quantitative findings showed that the factor loadings obtained for all components were evaluated as acceptable or excellent. The highest Q² value belonged to the environmental literacy construct, indicating the model's predictive power for responsible waste management behavior through this construct. The obtained P values for all paths confirmed the model's hypotheses, and the structural fit of the model was also validated. Therefore, the critical necessity of developing environmental literacy and waste management to minimize waste, through green consumption, waste prevention, and recycling, is clearly emphasized.
DOI: 10.57647/j.ap.2025.0902.20
Language: English
Open Access status: green
OpenAlex ID: W7128495014
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