Bibliographic record
Abstract
Background: Liquor industry is growing to become a global giant by empowering its competitiveness. Nowadays, alcohol has been accepted and welcomed as a normal part of everyday life with innovatively embedded alcohol development and promotion. Alcohol products consist of a range of offerings including Gin, wine, vodka and Scotch, among which brandy has been gaining higher importance. Objectives: This paper explores the consumers’ preferences for brandy, their knowledge on brandy and also the factors determining the consumer choice on consumption of brandy.This study aims to contribute to the brandy consumer behavior-responsive managerial implications, especially in hospitality industry by identifying the attributes that are perceived important for the marketing of brandy to a large segment of dynamic market. Methods: The academic discourse on this paper includes exploration of multiple dimensions related to the study of consumer behavior. Theories concerning consumer preferences, with specific focus on Reasoned Action Theory, Engel Kollat Blackwell Model, Hybrid Choice Model, Hedonic Price Model, Consumer Perception Factor Model and Conjoint Analysis are reviewed.The study on brandy, along with the differences from other alcoholic beverages, has also been included. Findings: Brandy represents a wide category and the bases of differences among types of brandy are studied along with the review of brandy products available worldwide. This study highlights brandy consumption practices in the world, benefits of brandy consumption and people’s perception towards brandy among other alcoholic beverages. Conclusions: Alcohol is the fastest growing industry and requires consumer preference for the promotions and penetration of the product into the market, and for developing the product and improving it further.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.030 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".