Development and Implementation of E-Business Strategies Managed and Applied by Kuwait Airways
Bibliographic record
Abstract
The chief objective of the current research is to offer significant novel perspectives into the creation and execution of e-business strategies managed and applied by Kuwait Airways, together with an evaluation of their suitability and ability to lead other airlines to secure a competitive advantage. The degree of achievement resulting from the application of e-business strategies for Kuwait Airways depends on the overall value added to its business operations and processes. The researcher adopted a case study of Kuwait Airways (KAC) and Jazeera Airways as a research method. This study shows that a good website can provide positive input for the fundamentals of a trade procedure and change compared to other related technologies, including the telephone, while the basis of the determined benefit is modified, with information becoming an essential asset and electronic commerce being a crucial enabler. This study reveals that the expansion of information through a web-site is related to both technology and policy. The Internet can be considered as a mode or a distribution channel to interact with clients; it is a crucial method to seeking new clients and maintaining associations with existing clients. Both the trade and the clients cannot afford to overlook the latest technology evolution. The current study showed that combining crucial functions including web technologies, marketing, and system solutions can help the KAC to attain competitive benefits.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".