MétaCan
Menu
Back to cohort
Record W1997006860 · doi:10.1109/iccie.2010.5668440

Redesigning the service quality measurement factors for the airline call centers in

2010· article· en· W1997006860 on OpenAlexaboutno aff
Jong‐In Choi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceQuality (philosophy)Service (business)Service qualityQuality of serviceTelecommunicationsBusinessMarketing

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.136
GPT teacher head0.303
Teacher spread0.167 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicConsumer Retail Behavior StudiesFrench-language works237,207