Using contingent valuation method to explore the households’ participation and willingness-to-pay for improved plastic waste management in North Vietnam

Abstract

Vietnam is one of the main plastic consumers in the world, yet there is much room for improvement in terms of plastic waste treatment. This study aims to inquire into residents’ awareness and responses to plastic waste, and their willingness to pay for enhancing plastic waste treatment in the North of Vietnam. We employ the contingent valuation method (CVM) and randomly survey 525 households in 25 provinces in Northern Vietnam. Findings suggest that a majority were interested and aware of impacts of plastic waste pollution, 76.8% were willing to contribute to a fund designated for plastic waste pollution alleviation. Residents’ willingness to pay range from VND 900,667 to VND 1,316,088 per household per month. Age, gender, perceived effects of waste pollution, illness due to pollution and care of plastic waste pollution are top factors influencing the households’ voluntary financial contribution to environmental fund. This study provides several evidence-based policy recommendations to improve the quality of plastic treatment in the North of Vietnam.

Contingent Valuation Machine Learning (CVML): A Novel Method for Estimating Citizens’ Willingness to Pay for a Safer and Cleaner Environment

“…The CV method has been used to estimate the value of a wide range of goods and services including clean air, clean water, biodiversity, and cultural heritage [5][6][7][8][9]. It has also been used to estimate the costs of environmental damage, such as waste pollution and climate change [3,[10][11][12]. Over the last four decades, CV development has been centered on five main directions.…”