Facing the challenges of expansion in the European Union
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine challenges and opportunities that occurred in the Polish ultra‐high temperature (UHT) milk market after Poland entered the European Union. Design/methodology/approach Through an in‐depth analysis of the Polish UHT market and by interpreting statistical data, this paper analyzes the retailing, production, and distribution channels, branding, and potential changes in the marketing perspective of the UHT market in Poland. To understand the nature of the market, this paper employs a marketing science method, marketing persistence analysis, to explore the relationship of short‐term marketing efforts and long‐term market response in Polish UHT milk market. Findings Based on empirical testing of ten Polish brands, results show that the UHT milk market in Poland presents marketing persistence, which means that short‐term marketing efforts can generate long‐term revenue effects. Research limitations/implications If marketing spending data are available, causality tests can be performed to see what are most effective marketing means (e.g. TV advertising or sale promotion) in Polish dairy markets. Practical implications Combining the empirical findings with the facts that previous marketing activities in Poland are relatively low, and it is now a historic transition for Poland after joining the homogenous market of Europe, the authors suggest that existing marketers increase the marketing investment to strengthen brands, gain market share, and build long‐term customer relationships. International marketers also have good opportunities now to enter Polish UHT markets through intensive marketing campaigns. Originality/value This study is the first attempt to apply marketing science techniques to examine the Polish market and the findings enable both academic researchers and industrial practitioners to understand this market better and explore its potential business opportunities.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".