Power imbalance issues in athlete sponsorship versus endorsement in the context of a scandal
Bibliographic record
Abstract
Purpose – The purpose of this study is to contrast athlete endorsement vs athlete sponsorship from a power imbalance perspective when a scandal strikes the athlete. Design/methodology/approach – A first study was conducted with a probabilistic sample of 252 adult consumers where the type of brand–athlete relationship (endorsement or sponsorship) and the level of congruence between the two entities (low or high) were manipulated in a mixed experimental design. A second study with a probabilistic sample of 118 adult consumers was conducted to demonstrate that consumers perceive that the balance of power between the brand and the athlete is not the same in endorsement and sponsorship situations. Findings – The results of the first study showed that when an athlete is in the midst of a scandal, the negative impact on the associated brand is stronger in the case of an endorsement than in the case of a sponsorship. However, this occurs only when the brand–athlete relationship is congruent. The results of the second study showed that the athlete’s power relative to the brand is greater in an endorsement than in a sponsorship context. Research limitations/implications – The findings suggest that a company that worries about the possibility that the athlete with whom it wants to build a relationship be eventually associated with some negative event (e.g. a scandal) should consider sponsorship rather than endorsement as a strategy. Originality/value – This study is the first to compare the athlete endorsement and sponsorship strategies in general and the first to put forward the notion of power imbalance in brand–athlete partnerships, its impact on how the two entities are represented in consumers’ memory networks and the consequences on brand attitude when the athlete is associated with a negative event.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".