Sport Events Customers’ Behavior in the Light of Hedonic Consumption
Bibliographic record
Abstract
Consumption of sport events has raised the specialists’ interest since it has become a global phenomenon, accessible to a large mass of consumers. At the same time, this consumption generates implications from an economic, social, and cultural point of view, in the countries/locations where various sport events have been organized, through the development of cultural and sport tourism. Sport event consumption belongs to the category of consumption acts that presume total implication apart from individuals and accordingly, their emotional involvement. This involvement is correlated on the one hand with the typology and the nature of needs and consumption motives underlying this consumption, and on the other hand with the more and more intensive promotion of these events and the easier participation access of consumers. Consumer involvement is a multidimensional construct, so the idea of an “involvement profile” is more appropriate to describe how the consumer relates to such products or services. The purpose of our paper is to clarify whether involvement within consumption for sport events customers is determining a specific behavior for the hedonic type of consumption also related to other categories of products or services. The consumption of sport events represents mainly a hedonic type of consumption correlated with a high level of emotional involvement during the consumption process, an involvement developed against the backdrop of the special role, and specific meaning that sport events can have at the level of individuals’ perception.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".