Influences of Sustainability Labels on Fashion Buying Behaviour – A Study on the Example of Fair Trade in Germany
Bibliographic record
Abstract
Purpose – The purpose of this paper is to find out the influences of sustainability labels on fashion buying behaviour. Despite key information about Fair Trade is provided in all stores of the sample company, customers seem not to be aware of the Fair Trade concept. Therefore this paper aims to give recommendations for a fashion retailer in terms of elucidation about Fair Trade by answering the following research questions: Which influences do sustainability labels wield on customer’s buying behaviour? Are consumers of textile products aware of the function and backgrounds of the Fair Trade label?Design/methodology/approach – A paper-based questionnaire was administered to 128 customers of a German fashion retailer “Adler Modemärkte AG” in four city stores from which 127 were correctly completed. Additionally an adjusted self-completion questionnaire administered to 50.000 customers online from which a total of 1.712 were correctly completed. Descriptive analysis and cross-tabulations were applied to abstract the main research findings and evaluate the hypotheses. Findings – Key findings suggest that Adler should either enhance their communication strategy regarding Fair Trade or remove Fair Trade products from the assortment, as the majority of respondents are not aware of Adlers` Fair Trade products. The Fair Trade label could neither be identified as consumer-barrier nor sales support. Further findings revealed participants have more knowledge about Fair Trade than initially assumed. Research limitations/implications – Majorly women aged between 56 and 75 participated in the survey. Findings are limited to geography, the target group of the fashion retailer Adler, gender, age group and the research method questionnaire.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".