Evidence map›Paper›PMID 37704693›Full record

ArticleScientific reports2023

Modeling the intention and donation of second-hand clothing in the context of an emerging economy.

Mengling Wu, Abdullah Al Mamun, Qing Yang, Jingzu Gao, Muhammad Khalilur Rahman, Sayed Samer Ali Al Shami

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Mengling WuUKM-Graduate School of Business, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor Darul Ehsan, Malaysia.
Abdullah Al MamunUKM-Graduate School of Business, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor Darul Ehsan, Malaysia. almamun@ukm.edu.my.
Qing YangUKM-Graduate School of Business, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor Darul Ehsan, Malaysia.
Jingzu GaoUKM-Graduate School of Business, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor Darul Ehsan, Malaysia.
Muhammad Khalilur RahmanFaculty of Entrepreneurship and Business, Universiti Malaysia Kelantan, Pengkalan Chepa, Malaysia.
Sayed Samer Ali Al ShamiInstitute of Technology Management and Entrepreneurship, Universiti Teknikal Malaysia Melaka, Melaka, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The culture of fast fashion accelerates the consumption rate of individuals but at the expense of significant environmental stress. With a large amount of discarded clothing accumulating in landfills, it is crucial to encourage people to dispose of second-hand clothing (SHC) as sustainably as possible, especially in an emerging economy with large volume consumption. Through a survey of 619 respondents from China, this study explored the factors affecting people's intentions and actual donation behaviors toward SHC. It extends the theory of interpersonal behavior (TIB) with environmental factors to construct a research framework, which included cognitive factors (attitude towards sustainable consumption), social factors (sense of community) and personal factors (perceived hedonic benefit) under TIB and the environment factors refers to problem awareness and ascription responsibility. Partial least squares structural equation modeling was employed to analyze the data. The findings revealed that attitudes toward sustainable consumption, problem awareness, ascription of responsibility, sense of community, and perceived hedonic benefit significantly and positively influenced people's intentions and practices of SHC donation. This study will aid governments and relevant green environmental protection organizations in formulating more precise strategies for sustainable development, and promote relevant research on the sustainable disposal of SHC.

Identifiers

PMID37704693
PMCPMC10499903

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.