Job Engagement as a Mediator of the Relationship between Organizational Agility and Organizational Performance: A Study on Teaching Hospitals in Egypt
Bibliographic record
Abstract
Purpose: The purpose of this study is to examine the moderating significant role of Job Engagement (JE) in the relationship between Organizational Agility (OA) and Organizational Performance (OP).Research Design/Methodology: To assess positive OA, refer to (OA Questionnaire, Jaworski and Kohli 1993), JE (JE Questionnaire, Rich et al., 2010) and OP (OP Questionnaire, Darroch, 2003; Pathirage, et al., 2007; and Chen & Mohamed, 2007). The data of the study was collected from 310 employees at Teaching Hospitals in Egypt. Out of the 357 questionnaires that were distributed to employees at Teaching Hospitals in Egypt, 310 usable questionnaires were returned, a response rate of 86%. Multiple Regression Analysis (MRA) was used to confirm the research hypotheses.Findings: The research has found that there is significant relationship between OA, JE and OP at Teaching Hospitals in Egypt. JE significantly influenced OA and OP. The finding reveals that OA affects OP through JE. Accordingly, the study provided a set of recommendations including the necessity to pay more attention to OA as a key source for organizations to enhance the competitive advantage which is of prime significance for OP through JE.Practical implications: This research helps boost scientific research, particularly in terms of testing the model content, as well as studying the study variables and the factors affecting them. In addition, it pointed to the need for organizations to practice OA in order to be able to meet contemporary intense competition, as this trend is to play an important role in enhancing JE.Originality/value: This research dealt with OA in terms of its concept and dimensions, in addition to dealing with the role of OA in promoting JE at Teaching Hospitals in Egypt.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".