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Understanding driving forces of food waste separation intention to enhance regional and local solid waste planning: application of PLS-SEM and multi-group analysis.
Le Dinh, Cuong; Fujiwara, Takeshi; Pham Phu, Song Toan.
Afiliação
  • Le Dinh C; Graduate School of Environmental and Life Science, Okayama University, Okayama, 700-8530, Japan. cuongldrs@gmail.com.
  • Fujiwara T; Graduate School of Environmental and Life Science, Okayama University, Okayama, 700-8530, Japan.
  • Pham Phu ST; Faculty of Chemical Technology - Environment, The University of Danang - University of Technology and Education, 48 Cao Thang Street, Hai Chau District, Danang City, 550000, Vietnam.
  • Habuer; Graduate School of Environmental, Life, Natural Science and Technology, Okayama University, Okayama, 700-8530, Japan.
Article em En | MEDLINE | ID: mdl-39103578
ABSTRACT
This study extended the theory of planned behaviour (TPB) and applied it to analyse influencing factors of food waste separation intention (FSI) among households in central Vietnam. Partial least squares structural equation modelling (PLS-SEM) was employed to analyse the data. The heterogeneity of factors contributing to FSI in cities of three levels was examined using multi-group analysis (MGA). The results indicate that attitudes, subjective norms (SN), perceived behavioural control (PBC), awareness of benefit (AB), information publicity (IP), facility availability (FA), and trust significantly affected FSI of households. MGA results indicated the heterogeneity of impacts of PBC and attitude on FSI of households among three municipal levels. The results will serve as basic data for waste officers, solid-waste management project leaders, non-governmental organisations (NGOs), and other related stakeholders to lay the foundation of food waste management planning in terms of regional scale and local scale. This study will also aid the creation of a circular economy by providing a scientific base for enhancing food waste separation at source in central Vietnam.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article