Domestic Garbage Classification and Incentive-Based Policies in China: An Empirical Analysis

Author:

Shen Yang1,Zhu Tao2,Kumar Rupesh3,Kumar Amit4ORCID,Chen Shaojun1

Affiliation:

1. College of Public Administration, Hohai University, Nanjing 211100, China

2. College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China

3. Jindal Global Business School (JGBS), O. P. Jindal Global University Sonipat Haryana, Sonipat 131001, India

4. School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Nanjing 210044, China

Abstract

In recent decades, with the rising living standards of rural China, the amount and volume of household waste has increased continuously, causing serious environmental and human health risks. Effective garbage classification reduces garbage volume, decreases the difficulty of garbage disposal, and facilitates the recycling of resources, thereby improving environmental quality. Domestic garbage classification (DGC) has been practiced frequently in developed countries and is now at a relatively mature stage. There is no robust model for garbage classification available globally as of yet, and each country has its policy frameworks to reduce, recycle, and reuse (3R) garbage. Little attention has been paid to knowing whether and to what extent incentive-based policies called “rewards and punishments” improve garbage classification and further help achieve targets of sustainable development goals (SDGs). Recently, developing countries, like China, have begun to incorporate DGC into their laws and promote enforcement measures in a few cities. However, empirical studies on residents’ willingness to accept DGC punishments and rewards are still relatively scarce and a hot topic of global scientific discussion. To enrich the knowledge, this study collected datasets from 9983 valid questionnaires from east China (16 selected independent variables), and analyzed the key factors affecting residents’ acceptance of punishments and rewards, employing logit models. The results found that the level of education plays an important role for residents that are more inclined to accept DGC rewards and punishments. Moreover, farmers were insensitive to DGC rewards but very sensitive and unsupportive of punishments, and the hardware facilities of the quarter had a greater impact on residents’ willingness to accept DGC rewards and punishments. Findings recommend that rewards be the main focus and punishments be supplemented, thus the incentive-based policies should be improved through law enforcement and implementation of robust policy frameworks in order to promote residents’ acceptance of rewards and punishments and to accelerate better garbage classification.

Publisher

MDPI AG

Subject

Water Science and Technology,Aquatic Science,Geography, Planning and Development,Biochemistry

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