Work engagement among managers and professionals in Egypt
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine potential antecedents and consequences of work engagement in a sample of male and female managers and professionals employed in various organizations and industries in Egypt. Design/methodology/approach Data were collected from 242 respondents, a 48 percent response rate, using anonymously completed questionnaires. Engagement was assessed by three scales developed by Schaufeli et al. ; vigor, dedication, and absorption. Antecedents included personal demographic and work situation characteristics as well as measures of need for achievement and workaholic behaviors; consequences included measures of work satisfaction and psychological well‐being. Findings The following results are observed. First, both need for achievement and one workaholic job behavior are found to predict all three engagement measures. Second, engagement, particularly dedication, predict various work outcomes (e.g. job satisfaction, intent to quit). Third, engagement, again, particularly dedication, predicted various psychological well‐being outcomes but less strongly than these predicted work outcomes. Research limitations/implications Questions of causality cannot be addressed since data were collected at only one‐point in time. Longitudinal studies are needed to determine the effects of work life experiences on engagement. Practical implications Organizations can increase levels of work engagement by creating supportive work experiences (e.g. control, rewards, and recognition) consistent with effective human resource management (HRM) practices. But caution must be exercised before employing North American practices in the Egyptian context. Originality/value This paper contributes to the understanding of work engagement among managers and professionals and HRM more broadly in a large Muslim country.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".