An Assessment of the Dimensionality of Should and Will Service Expectations
Bibliographic record
Abstract
Abstract This study is a step forward in the continued evolution of our understanding of multiple standards of customer service expectations. By developing a higher‐order factor model, we examine the existence of hypothesized functional and technical dimensions of should and will expectations, and determine the causal relationships between the two types of expectations and the two hypothesized dimensions. In an effort to provide a richer conceptualization of should and will expectations, we test their dimensionality in the context of the turbulent airline industry. A survey measuring consumers' post‐encounter expectations vis‐à‐vis a well‐known airline carrier was completed by a sample of experienced travelers (N = 363). As expected, should expectations were higher than will expectations with the former exhibiting less variability than the latter. Our second‐order factor model also revealed two types of expectations, should and will, and two dimensions, functional and technical, for each type. Given its multidimensional nature, our model of customer service expectations has far‐reaching implications in carrying out and interpreting service quality and satisfaction research. Based on our findings, we recommend that managers formulate useful marketing strategies by manipulating should and will expectations simultaneously, and by focusing more on the functional as opposed to the technical dimensions, at least in the airline industry. Résumé La présente étude marque un nouveau développement dans la compréhension des diverses normes d'évaluation du service à la clientèle. Grâce à l'élaboration d'un modèle factoriel de plus haut niveau, nous examinons l'existence des dimensions à teneur fonctionnelle et technique qui sont sous‐jacentes aux attentes normatives (should) et prédictives (will) et déterminons la relation causale entre les deux types d'attentes. Dans le souci de fournir une meilleure image de la conceptualisation des attentes prédictives et normatives, nous avons choisi l'industrie aéri‐enne qui a récemment connu beaucoup de mutations. Nous avons sélectionné un échantillon composé de personnes qui ont l'habitude de voyager (N = 363) auxquelles nous avons distribué un questionnaire portant sur les attentes envers une compagnie aérienne reconnue. Conformément à notre hypothèse, le niveau des attentes normatives (should) était plus élevé que celui des attentes prédictives (will), le premier présentant une plus grande variabilityé que le second. Le facteur de second ordre a confirmé non seulement l'existence d'attentes normatives et prédictives, mais aussi l'existence de deux dimensions (fonctionnelle et technique) qui sous‐tendent chacun des deux types d'attentes étudés. De par sa nature multidimensionnelle, le modèle d'attentes proposé dans cet article comporte plusieurs implications théoriques au niveau de la recherche sur la qualityé du service et sur la satisfaction. Nos résultats nous incitent à recommander aux gestionnaires de manipuler simultanément les attentes prédictives et normatives et de concentrer leurs efforts sur la dimension technique du service plutôt que sur sa dimension fonctionnelle, du moins dans l'industrie aérienne.
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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 | 0.010 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".