Identification of Niche Market for Hanwoo Beef: Understanding Korean Consumer Preference for Beef using Market Segment Analysis
Bibliographic record
Abstract
Korean Hanwoo beef producers are interested in improving the image of Hanwoo beef for Korean consumers, as the Korean beef market is becoming increasingly open to international competition. This study examines the consumer profile and positioning for the Hanwoo beef product in South Korea. A survey of 480 consumers is conducted to analyze preferences for 33 attributes of beef purchasing decisions. Factor analysis was used to determine factors that are important in beef purchasing decisions, and cluster analysis was used to identify a niche market for branded Hanwoo beef. Factor analysis results indicated that effective labeling and quality assurance of Hanwoo products, the meat quality, price and branding are important to the positioning and marketing of the Hanwoo beef product. Consumers with medium to high income, married and aged between 30 to 39 years, and those that appreciate Hanwoo quality but do not trust the current labeling system are most likely to purchase branded Hanwoo beef and represent a potential niche market, according to cluster analysis results.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".