The Effect of Consumption Value for Bio Cosmetics on Purchasing Behavior -Focusing on the mediating effect of brand loyalty-
Bibliographic record
Abstract
Purpose: The purpose of this study is to examine the effect of consumption value perceived by cosmetic consumers on brand loyalty and purchasing behavior of bio cosmetics through empirical analysis. Methods: To this end, multi-regression analysis was conducted to analyze the relationship between perceived consumption value, brand loyalty, and purchasing behavior. In addition, bootstrapping was performed to verify the mediating effect of brand loyalty. Results: The research results are as follows. First, among perceived consumption values of bio cosmetics, pleasure value, brand value, and functional value were found to have a significant positive (+) effect on brand loyalty. Second, brand loyalty of bio cosmetics was found to have a significant positive (+) effect on purchasing behavior. Third, among the consumption values perceived by bio cosmetics, functional value, pleasure value, and brand value were found to have a significant positive (+) effect on purchasing behavior. Fourth, the mediating effect of brand loyalty was confirmed in the relationship between perceived consumption value and purchasing behavior of bio cosmetics. Conclusion: The results of this study will be meaningful in that it empirically examines the influence relationship between consumption value and purchase behavior for bio cosmetics and examines the mediating effect of brand loyalty in the relationship between them. In the post-corona era, as new changes are expected throughout the cosmetic industry, a new trend appears in the cosmetic industry, and the need for value establishment is emerging. The results of this study will have great implications for the bio-cosmetic 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".