The impact of human resources employment strategy in achieving competitive advantage: Zain Jordan Telecom company
Bibliographic record
Abstract
Organizations in all sectors seek to achieve their goals and achieve competitive advantage in order to reach profits, which is the main goal of organizations. They work to determine their needs of human resources, and try to attract the largest possible number of job seekers, in order to choose the best elements among them and then plan the workforce, through which the full and good description of all the jobs to be filled and the specifications of those who occupy them are determined, and once this process is completed, the next step begins, which is to search for the most suitable people for these jobs and try to attract and attract the most qualified to work in the organization and entice them to stay in it. The aim of this paper is to identify the effect of the human resources employment strategy in achieving competitive advantage in Zain Jordan Telecom company. The descriptive and analytical approach was relied on. The study community consisted of all (1200) employees of Zain Jordan Telecom company, and a random sample of (180) employees was taken. The study concluded that there was a positive impact of the strategy of employing human resources in achieving competitive advantage, and the presence of a positive impact of the strategy of human resources in achieving the dimensions of competitive advantage (quality, cost, and innovation). The paper contributes to the development of literature related to the relationship between the strategy of employing human resources and achieving competitive advantage by providing field indicators on the nature of the between these two variables in the work environment.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".