Redesigning the service quality measurement factors for the airline call centers in
Bibliographic record
Abstract
Prior to this paper, how the airline call center employees recognize the relative importance of the service quality measurement factors categorized under SERVQUAL model has been analyzed and the findings were that they recognize the “technical quality factors,” which are categorized under the dimensions of reliability and tangibles, as same or more important than the “functional qualities factors,” which are categorized under the dimensions of assurance, empathy and responsiveness. Though the study was a very brief and informal one, it has indicated the service quality measurement factors currently used for Korea Service Quality Index (KSQI) by Korea Management Association (KMA), and quality assurance activities by one of Korea's airline companies may have to be redesigned to suit the air transportation market in Korea. In order to see how the call centers' service qualities were measured out side of Korea, Service Quality Management (SQM) Group, Inc. based in Calgary, Canada, was chosen and their service quality measurement factors were reviewed with categorizing them under the five dimensions of service quality measurement. The result was that the chosen firm had a measurement chart which put quite an amount of importance on the dimensions of reliability and tangibility. Each and every country's service product market has to have a unique service quality measurement chart of its own composed of different measurement factors because of its unique market situation, and Korea's airlines market would be no exception. As the airline call center employees see more importance on their abilities to meet customer's specific requirements as the systematic capacities and supports than what traditionally had been thought to be important in call center services, it is believed that customers' thoughts would be quite similar since the airline call center employees are the ones who directly serve thousands of customers through phone calls, internet chats and e-mails everyday, and, therefore, suggested that the service quality measurement factors for Korea's airline call centers should be redesigned to better reflect such findings.
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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 | 0.002 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".