The Role of Organizational Agility in Reinforcing Job Engagement: A Study on Industrial Companies in Egypt
Bibliographic record
Abstract
Background: In the current turbulent and highly competitive environment, organizational agility (OA), that is the ability of organizations to quickly sense and respond to environmental changes, is an important determinant of organization success. Purpose: The purpose of this research is to identify the types of OA (sensing agility, decision-making agility and acting agility) and its role in promoting job engagement (JE) of the employees at the Egyptian industrial companies in Sadat city. Research Design/Methodology: To assess positive OA, refer to (OA Questionnaire, Jaworski & Kohli, 1993) and JE (JE Questionnaire, Rich et al. (2010) are used). The data of the study was collected from 315 employees at the Egyptian industrial companies in Sadat city. Out of the 372 questionnaires that were distributed to employees at industrial companies in Egypt, 315 usable questionnaires were returned, a response rate of 85%. Multiple Regression Analysis (MRA) was used to confirm the research hypotheses. Findings: The researcher has found that the study subjects do agree that OA directly affects the dimensions of JE of the employees at the industrial companies involved in the current study. Practical implications: This research helps to stimulate scientific research, particularly in terms of testing the model content, as well as studying the study variables and the factors affecting them. In addition, this research 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 the Egyptian industrial companies in Sadat City.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".