The influence of electronic service quality on relationship quality: Evidence from tourism industry
Bibliographic record
Abstract
The purpose of this study is to offer better understanding to the dimensions of e-service quality and relationship quality by building on previous literature on e-service quality of tourism sector in Jordan. Moreover, the study also aimed to study the influence of Electronic Service Quality on relationship quality within the tourism sector in Jordan from the customer's perspective. The Electronic Service Quality is represented by information quality, ease of use, reliability, privacy and responsiveness. The population of the study consisted international tourists, who visited (Dead Sea) Jordan during summer 2019. A convenient random sample was taken amounted (400) participants and PLS was used to examine the study hypotheses. The researchers found that there was statistically significant influence of the Electronic Service Quality on relationship quality. The study also indicates that ease of use, privacy and responsiveness had significant positive influence on relationship quality. The researchers recommended the use of electronic services and focus on the dimensions of e-service quality on tourism electronic services especially in Jordan.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".