A Study on Purchase Behavior of Bio Cosmetics Applying the Theory of Planned Behavior(TPB): Mediating Effect of Brand Image
Bibliographic record
Abstract
The purpose of this study is to examine the TPB(Theory of Planned Behavior) factors that affect the purchasing behavior of bio cosmetics consumers and to examine the mediating effect of brand image in the relationship between them. In this survey, cosmetics consumers aged 20 or older residing nationwide were selected as the population. Bio-cosmetics consumers in their 20s or older living in the Seoul metropolitan area were selected as a sample group, and an online survey was conducted for about 4 weeks in October 2022. For statistical processing of the collected data, multi-regression analysis and bootstrapping were performed using SPSS 28.0 and SPSS Macro 3.4 to verify the hypothesis. As a result of the study, Attitude, Subjective Norm, and Perceived Behavioral Control had a significant effect on purchase behavior, and the mediating effect of brand image was confirmed. Therefore, in order to increase consumers' purchasing behavior, it seems to be very important in terms of marketing to build an image such as awareness and trust in the brand as well as the functional efficacy of bio-cosmetics. These research results will have great implications for the bio-cosmetics industry preparing for the post-corona era.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".