Improving Digital Marketing Strategy in Jordanian Air Aviation Sector for Becoming a Regional Training Center
Bibliographic record
Abstract
The transformational processes of the global economy and the development of digital technologies necessitate a conceptual review of existing management strategies and their improvement, a change in the processes of obtaining knowledge and assessing their relationships. In modern conditions, to ensure the effectiveness of activities, the necessary element of management is the use of innovative information and digital technologies in business, which allow optimizing costs and optimizing financial results. The expediency and relevance of the study, which is aimed at assessing the relationship of digital strategies and their impact on the Jordanian aviation sector, is substantiated. It has been taught that the availability of digital technologies contributes to the improvement of management strategies and educational processes, which allows them to become training centers at the regional level. It was determined that the development of digital tools (content, web pages, social networks, advertising, video and other marketing components) and their application in organization management strategies contribute to streamlining the management process and gaining knowledge. It is argued that the process of education and training of managers depends on the approach used by the organization’s digital tools, as well as the type and industry of its economic activity. It is taught that the training used in the Jordanian aviation sector, as a managerial survey compiled by design specialists, explains the degree of accessibility of this sector of the economy and confirms the need to establish a training center at the regional level. It is proved that the establishment of a training center at the regional level will ensure the promotion of employees of the Jordanian aviation sector, state support, a new image and loyalty, which will make managers at the local and regional levels aware. To justify the relevance and necessity, a statistical one-way analysis of variance was carried out for the influence of factors on training processes in the aviation sector of Jordan. The main results of statistical one-way analysis of variance interpret the importance of this study and the need to improve the digital strategy, and its application in marketing activities, which focus on 3digital. Unique practical recommendations have been developed that are based on customer focus and focus on three digital strategies (clients; educational product; digital tools), which will achieve the organization's strategic goals and positive financial results.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".