The service quality construct on a global stage
Bibliographic record
Abstract
The eagerness of global marketers to establish a competitive advantage based upon service quality excellence within emerging markets displays a degree of naïveté in respect to the influence of environmental factors upon consumption behaviour. An example of this is the global application of Parasuraman, Zeithamal and Berry’s conceptualisation of service quality (SERVQUAL) in 1988 without consideration of the possible influence of the variety of cultures found in international markets. This paper takes a cautionary stance to such global application, and proposes that cultural values endow consumers with rules that guide their evaluation of service quality. Field research was conducted within Taiwan to ascertain whether the dominant service quality model holds in this “foreign” environment. The results indicate that not only do cultural values influence the hierarchy of service quality dimensions, but also that Parasuraman et al.’s SERVQUAL conceptual model does not capture the breadth of criteria utilised by Taiwanese consumers. Interpersonal relations are highlighted as a dimension of service quality that is not adequately addressed by SERVQUAL.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".