Exploring strategies to tackle plastic waste pollution: Evidence from Vietnamese household survey and Bayesian approach

Quy Khuc (), Phuong-Thao Dang, Phuong-Mai Tran, Thuy Nguyen, Phu Pham and Duc-Trung Tran

No m73ef, OSF Preprints from Center for Open Science

Abstract: As one of the world’s fastest-growing economies, Vietnam is tackling environmental pollution, particularly plastic waste. According to a recently published report, the country is one of the world’s top five marine polluters of plastic waste. This study contributes to the literature and practical solutions by better understanding households’ perceptions, behaviours, and motivations for sorting waste, contributing to the environmental fund and relocating. The questionnaire-based interview method was used to collect information from 697 households in 25 provinces in Vietnam during February 2022. Statistical descriptive method and Bayesian regression model coupled with mindsponge mechanism were employed to explore and analyse the data. The findings show that people’s strategies and responses to plastic waste pollution vary: 38.63% of respondents have been sorting waste at home, 74.25% agreed to contribute to the environmental fund, and 23.56% plan to relocate to find a better living place. The households’ strategies and intentions are driven by many structural and contextual factors such as age, income, care about the environment, and the perceived effect of polluted waste. More importantly, communication is a robust variable in sorting waste decisions, which suggests that better communication would help increase people’s awareness and real actions in reducing plastic waste and ultimately improving the environment. The findings of our study will benefit the ongoing green economy, circular economy, and green growth transition toward more sustainable development, particular in developing and fast population growing nations.

Date: 2022-08-11
New Economics Papers: this item is included in nep-env and nep-sea
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:m73ef

DOI: 10.31219/osf.io/m73ef

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