What Factors Affect Farmers' Levels of Domestic Waste Sorting Behavior? A Case Study from Shaanxi Province, China

Int J Environ Res Public Health. 2022 Sep 25;19(19):12141. doi: 10.3390/ijerph191912141.

Abstract

Waste sorting is a key element for solving the current predicament of rural waste management. In the pilot areas of China, farmers' domestic waste sorting behavior (DWSB) varies significantly, whereas there are few studies exploring the mechanism of its formation. To fill this research gap, this study constructs a research model of the internal logic of farmers' waste sorting levels (i.e., no sorting; sorting recyclable waste; sorting recyclable and kitchen waste; and sorting recyclable, kitchen, harmful, and other waste) by considering circumstantial constraints (social norms in external factors) and psychological behavioral antecedents (personal norms and group identity in internal factors). Based on pilot survey data from farmers in Shaanxi Province, China, the results of the ordered logit model indicate that social norms and personal norms were the most significant predictors of the level of DWSB, while group identity was found to have no significant influence. Furthermore, the results of the grouping regression analysis showed that personal norms had a positive moderating effect on the relationship between social norms and farmers' DWSB. Therefore, a more positive social atmosphere, better education, and personal environmental moral responsibility for domestic waste sorting should be established to enhance their levels of waste sorting behavior.

Keywords: descriptive norms; domestic waste management; injunctive norms; ordered logit model; rural areas.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Agriculture
  • China
  • Farmers*
  • Humans
  • Morals
  • Social Norms
  • Waste Management*

Grants and funding

This research was funded by National Natural Science Foundation of China, grant number 72103164; Ministry of Education of Humanities and Social Science Project of China, grant number 20YJC790171; Postdoctoral Science Foundation of China, grant number 2018M631213; Chinese Universities Scientific Fund, grant number 2452022046 and Scientific Research Foundation for Talents of Shaanxi Province, grant number F2020221010.