The Effect of Employee Engagement on Organizational Performance Via the Mediating Role of Job Satisfaction: The Case of IT Employees in Jordanian Banking Sector
Bibliographic record
Abstract
This study sought to investigate the effect of IT employees' engagement on organizational performance through the mediating role of job satisfaction for IT employees within the IT Departments in Jordanian banking sector. Quantitative research design and regression analysis were applied on a total of 429 valid returns that were obtained in a questionnaire based survey. The results showed that IT employee engagement significantly affected organizational performance and three of its dimensions, vigor, absorption, and dedication contributed significantly to organizational performance. The results also showed that IT employee engagement positively and significantly affected job satisfaction, where vigor had the most contribution. In addition, it was found that job satisfaction significantly and positively affected organizational performance. Furthermore, job satisfaction only partially mediated the association between IT employee engagement and organizational performance. This study implies that IT departments in Jordanian banking should try their best to promote and facilitate IT employees' engagement and satisfaction in an effort to improve their performance, which will eventually yield positive results for the bank as a whole. In light of these results, the research presented many recommendations for future research, the most important ones were the application of this study in other sectors, cultures, and countries, the exploration of the moderating role of job satisfaction instead of mediating role, and the use of other sampling techniques.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".