Exploring the psychological benefits of value co-creation in tourism: Enhancing hedonic and eudaimonic well-being through empowerment, social connectedness, and positive emotions
Bibliographic record
Abstract
Abstract This study investigates the psychological benefits of value co-creation in tourism, focusing on its effect on hedonic and eudaimonic well-being. Although tourism has conventionally been associated with hedonic consumption, less consideration has been given to its fuller potential for bettering more profound psychological outcomes. Therefore, this research fills this gap by investigating how value co-creation activities enhance well-being. In particular, we propose that co-creation enhances positive emotions, empowerment, and social connectedness, providing both hedonic and eudaimonic well-being in the short and long run. We used data from 410 domestic travelers who participated in co-creation during their most recent trips and used structural equation modeling to investigate the links between co-creation behaviors and well-being outcomes. Results showed that positive emotions act as partial mediators in associations of co-creation behaviors with hedonic and eudaimonic well-being. The strongest drivers of psychological benefits involved empowerment and social connectedness. These findings spotlight the emotional and psychological dimensions of tourism marketing strategies, offering the potential for tourism businesses to achieve more significant customer satisfaction and long-term well-being benefits from travelers. These findings have valuable implications for managers pursuing meaningful customer relationships through value co-creation and enhancement of overall well-being through inspiring travel experiences.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".