An Exploration of Determinants of Entrepreneurial Characteristics, Motivation, and Challenges in Palestine
Bibliographic record
Abstract
Being an entrepreneur is becoming an anabranch in the business world. In addition, many young adults are preparing to be entrepreneurs in the future. Worldwide, many intellectuals view entrepreneurship as necessary to small-medium enterprises (SMEs) in general because it is critical to development. Micro, small-medium enterprises (MSMEs) are crucial in Palestine because MSMEs dominate the Palestinian economy. This study highlights the specific characteristics of entrepreneurship and the factors motivating and challenging people when starting up their enterprises in Palestine and dealing with these challenges and obstacles. The research method combines qualitative and quantitative tools, each of which was used to study relevant aspects. The qualitative tools used are interviews with the entrepreneurs in Palestine, while the quantitative tool included a designed questionnaire. The collected data was then analyzed using SPSS v 23. Findings indicated that entrepreneurs in Palestine are self-confident, passionately seeking new opportunities with a good network of professionals, patient, persistent, and determinant, and can adapt to change. The results further highlighted that the most motivational factors behind being an entrepreneur in Palestine include being their boss and increasing income to have a better financial future. However, Lack of savings, political situation, competition, and the fear of risk associated with starting a business is the significant challenges and obstacles they face., Finally, Results indicate that gaining experience, developing business plans, managing financial resources, and motivating employees are the critical factors they have to consider. At the same time, they deal with these challenges and obstacles.
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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 | 0.002 | 0.004 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".