Bibliographic record
Abstract
Purpose - The paper aims to explore a major issue in international marketing: how to build a global brand in a way that makes a strong local connection. Design/methodology/approach - Using qualitative research methods on a single case, the Brisbane Goodwill Games, the processes used in the staging of this major sport event are analyzed. In particular, the stakeholder relations employed by the marketing department of the Goodwill Games Organization are investigated and a process model is developed that explains how a global brand can be built locally. Findings - A major outcome of the paper is a revision to the four-step Freeman process to make it more proactive; and three major principles for effective stakeholder management are articulated. The findings demonstrate that stakeholder analysis and management can be used to build more effective event brands. Stakeholder theory is also proposed as an appropriate and possibly stronger method of building inter-organizational linkages than alternatives such as network theory. Originality/value - Previous literature has generally dealt with the global brand issue in terms of the standardization versus adaptation debate, and the extent to which the marketing mix should be adapted to meet local needs in foreign countries. This research provides a unique extension to this literature by demonstrating how the brand itself needs to be modified to meet local needs.
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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.040 | 0.005 |
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".