The Role of Work/Life Balance and Motivational Drivers of Employee Engagement on the Relationship between Talent Management and Organization Performance: A Developing Country Perspective
Bibliographic record
Abstract
The purpose of this paper is to explore the relationship between talent management, work life balance, motivational drivers of employee engagement and organization performance in telecommunication and information technology sector in Jordan. Both work life balance and motivational drivers of employee engagement were examined as mediators between talent management and organization performance. The population of the study consists of the three main telecommunication operators in Jordan; Zain, Orange and Umniah with a total number of employees (3305), a random sample appointed from the population with a total 250 questionnaires filled up. The study found a positive relationship between talent management and its three dimensions, namely talent attraction, talent development and talent retention with organization performance. Results also found a positive relationship between talent management and its three dimensions with work life balance. A positive relationship also found between talent management and its dimensions with motivational drivers of employee engagement. Finally, work life balance found to partially mediating the relationship between talent management and organization performance and motivational drivers of employee engagement fully mediating this relationship between talent management and organization performance. This study stated many recommendations for future researches. 
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".