The impact of emotional perceived value on hotel guests’ satisfaction, affective commitment and loyalty
Bibliographic record
Abstract
Purpose This study aims to investigate the impact of emotional perceived value on hotel guests’ satisfaction, affective commitment and loyalty. Design/methodology/approach Data were collected from 348 respondents living in the United Arab Emirates, and hypotheses were tested using AMOS 28 and structural equation modeling. Findings This study’s unique contribution lies in its revelation that emotional perceived value directly impacts guests’ satisfaction, affective commitment and loyalty. Furthermore, it uncovers that emotional-perceived value indirectly influences loyalty through satisfaction and affective commitment. Practical implications This research underscores the importance of hotel managers prioritizing guests’ emotional perceived value in their offerings. Managers can significantly enhance guests’ satisfaction, affective commitment and loyalty by highlighting self-gratification, aesthetics, prestige, transaction and hedonics. Originality/value This study brings a fresh perspective to understanding customer perceived value (CPV). It argues that the mere emphasis on the functional aspect of CPV would likely fall short of fully comprehending specific outcomes of their experience (e.g. satisfaction-dissatisfaction, loyalty, etc.). Assessing the emotional aspect of CPV, known as emotional customer perceived value (ECPV), adds further explanations and sheds light on the understanding of the CPV concept and its impacts on consumers’ experience. Furthermore, this study emphasizes that emotional perceived value is better comprehended as a multidimensional rather than a unidimensional construct. It adds that the concept of customer value as a multidimensional concept is context-specific (i.e. dimensions vary from one service sector to another), providing a unique and valuable perspective for the luxury hotel industry.
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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 | 0.004 |
| 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 | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".