The impact of brand image and service quality on customer satisfaction: The mediating role of green marketing in the airline transport industry
Bibliographic record
Abstract
The context of this study is that the degree of customer satisfaction attained by airline businesses in the air transportation industry does not align with management goals. The purpose of this study is to ascertain how customer perceptions of satisfaction are impacted by brand image and Quality of Service, as mediated by green marketing, in the aviation industry. Clients or users of air transportation business services were given online questionnaires as part of the study's quantitative survey methodology. In order to address hypotheses and identify the best structural equation model with Smart-PLS, this study goes through the steps of evaluating the reliability and validity of instruments, KMO-MSA, Factor analysis, Bartlett tests, and Path analysis. The findings demonstrated that the hypotheses namely, Direct relationship (1) Brand Image on Green Marketing, (2) Quality of Service on Green Marketing, (3) Green Marketing on Satisfaction Perceived of Customer, (4) Quality of Service on Satisfaction Perceived of Customer, (5) Brand Image on Satisfaction Perceived of Customer were successfully demonstrated to be Positive and Significant. Green marketing also has the Indirect relationship impact of somewhat mediating the relationship (6) Brand Image on Satisfaction of Customer Mediated by Green Marketing, and (7) Quality of Service on Satisfaction of Customer Mediated by Green Marketing. The results of this study provide several managerial implications that can be applied to improve Brand Image and Quality of Service in the Air Transport Business.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".