Bibliographic record
Abstract
Subject area Marketing strategy; services marketing; tourism. Study level/applicability Upper year undergraduate business/management, MBA, marketing/international business. Case overview Memento Park is a large open air museum on the outskirts of Budapest, that houses statues, and related ephemera related to the communist period in Hungary. The park opened in 1993, four years after Hungary had shaken off its yolk of communism as part of the Iron Curtain, in 1989. This case presents a classic example of a business enterprise that sprang from a concept and access to inexpensive materials directly resulting form a changing external environment. The case presents the issues involved in making Memento Park a sustainable part of the Budapest tourist experience. Expected learning outcomes This case challenges students to decide how best to determine a sustainable advantage. Arguably the value proposition that is being offered by Memento Park has a number of identifiable benefits to the target consumer. It is not replicable (at least in Hungary), has a truly unique content, and does not have large fixed or variable costs in terms of operations. The question is how to best develop a plan of attack for such a firm? Supplementary materials Teaching notes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".