The impact of entrepreneurship factors on organization behavior and learning at Jordan Orange Telecommunication firm
Bibliographic record
Abstract
The purpose of this study was to evaluate the impact of important entrepreneurship variables, notably self-concept, work motivation, and risk-taking, on organizational behavior and learning within the setting of Jordan Orange Telecommunication firm. Notably, the research was intended to look at how these factors affect organizational behavior and learning. To evaluate the hypotheses that were proposed in this research, a sample size of 294 people participated in the study, and their data were evaluated and debated. It was shown that an individual's perception of themselves as entrepreneurs, their level of drive at work, and their willingness to take risks all had an impact on developing organizational behavior and organization learning. It became clear that self-concept was the most important component, and that it included aspects such as self-confidence, self-perception, and self-definition. Closely following behind was the concept of work motivation, which included concepts such as self-motivation, extrinsic motivation, the setting of goals, and concentration. Risk-taking was the third key factor, and within this category were subcategories such as risk tolerance and risk perception, as well as expectations surrounding the consequences. The findings showed the possibility for improving organizational behavior and fostering innovation by assisting employees in comprehending the roles they play in their jobs, boosting job motivation, and encouraging a predilection for risk-taking. This can be accomplished by providing employees with training and development opportunities. The study adds fresh insights to a field that merits additional exploration, particularly considering the connection between workload, compensation, and the structural demands that are placed on organizations. The fact that the research concentrated on Jordan Orange Telecommunication company makes it both innovative and of major importance. This is because it can improve both the business's operations as well as the overall quality of the company's goods and services.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".