4.4 Article

Predicting the effect of promotion measures on waste separation behavior: a case study in Da Nang City, Vietnam

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SPRINGER
DOI: 10.1007/s10163-021-01300-w

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Behavior prediction; Waste separation; Recyclable; Participation rate; Behavior modeling

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  1. University of Danang, University of Science and Technology [T2021-02-25]

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The study suggests that providing information is the most effective measure to promote recycling, leading to a significant increase in participation rates and the amount of separated recyclables. Following that is the provision of collection services. Authorities should consider enhancing environmental awareness to further improve recycling efforts.
Recycling is one of the priority solutions for reducing the amount of waste entering landfills. To achieve high rates of recycling, citizens are encouraged to participate in waste separation at home. Behavior prediction has been used to understand the factors that promote participation in recycling activities. This study focused on predictive models of waste separation behavior and their application in estimating the effect of promotion measures on behavior. Data were collected from 600 households in Da Nang, Vietnam. Logistic regression was used to develop predictive models of separation behavior for 14 recyclable categories. Sensitivity analyses of the models were carried out to predict changes in participation rates and waste amount caused by the implementation of various promotion measures. Provision of information was the most effective promotion measure, with the highest predicted increase in recycling participation rates (6.1-49.0%) and the amount of separated recyclables (up to 9.6% of total waste generated), followed by provision of collection services, with a predicted increase of 1.6-7.7% in participation rates and 7.7% in the amount of separated recyclables. For further improvement, promotion of environmental awareness should be considered. This study is beneficial to authorities looking for ways to motivate citizens to recycle.

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