Evidence map›Paper›PMID 39562710›Full record

ArticleScientific reports2024

How perceived sustainability influences consumers' clothing preferences.

Mingzhi Li, Young-Hwa Choe, Chao Gu

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

3 authors.

Mingzhi LiDepartment of Culture and Arts Management, Honam University, Gwangju, 62399, Korea.
Young-Hwa ChoeDepartment of Culture and Arts Management, Honam University, Gwangju, 62399, Korea.
Chao GuAcademy of Arts & Design, Tsinghua University, Beijing, 100084, China. cguamoy@my.honam.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we explored innovative approaches to sustainable fashion design, focusing on the increasingly prominent issue of sustainability in the global fashion industry. By analyzing consumer feedback in online communities, particularly through a systematic study of user comments on clothing products on the JD.com website, this paper reveals consumers' attitudes, expectations, and suggestions regarding sustainable fashion. The findings provide new directions for improvements in sustainable clothing design. We collected data using Python web scraping technology from the Chinese e-commerce platform JD.com and employed the Latent Dirichlet Allocation (LDA) method for text topic modeling. This approach successfully identified three main themes: perceived quality, perceived value, and sensory comfort. Additionally, we employed multivariate analysis of variance to assess consumers' perceptions. Survey data show that consumers demonstrat higher levels of perceived quality, value, purchase intention, and intention to repurchase sustainable clothing compared to traditional apparel. The research findings help apparel companies understand consumer needs regarding sustainability, providing theoretical support for designers and confirming the importance of emphasizing eco-friendly materials and sustainable production in new product development. This research not only provides actionable insights for the fashion industry but also contributes to the ongoing discourse on sustainable design strategies globally.

Indexed as

ClothingConsumer BehaviorAdultChinaFemaleHumansMalePerceptionSurveys and QuestionnairesLatent Dirichlet AllocationOnline community feedbackProduct design improvement strategiesSustainable apparel

Identifiers

PMID39562710
PMCPMC11576948

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.