Prediction of waste separation behavior and its underlying mechanisms using logistic regression
Year: 2024
Type: article
Study design: Observational Study
Abstract: Waste separation is essential to reduce the impact of pollution on the environment and to promote sustainability. Despite the implementation of waste separation policies in many countries and regions, the results have not met expectations. Therefore, it is imperative to identify the key factors that encourage waste separation behavior. Based on self-determination theory and the theory of planned behavior, we examine these determinants and underlying mechanisms of green intrinsic motivation and perceived factors on waste separation behavior. The study employs logistic regression to identify predictor variables, and uses the Python statsmodels library for data analysis. The results show that green intrinsic motivation and perceived control positively predict waste separation behavior, while perceived difficulty has a negative predictive effect. Perceived control mediates the effect of green intrinsic motivation and perceived difficulty on separation behavior.
Authors: Xuejin Zhang, Pingping Liu
Language: English
Subfield: Management, Monitoring, Policy and Law
Field: Environmental Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4405730013