Fear of failure for entrepreneurs in emerging economies: stress, risk, finances, hard work, and social support
Bibliographic record
Abstract
Purpose Many entrepreneurs often struggle with the fear of failure, which can be detrimental to both their business and personal well-being. To better understand the factors that contribute to this fear, the authors conducted research on the impact of various obstacles, such as limited financial resources, risk aversion, stress and hard work avoidance, and prior business failures. Additionally, the authors explored the effects of social capital in mitigating these obstacles and their relationship to fear of failure in entrepreneurship. Design/methodology/approach The authors conducted a survey with 440 young Iraqi entrepreneurs using non-probabilistic and purposive methods. The survey instrument included multiple measuring scales, which were provided in both English and Arabic. The authors analysed valid responses using structural equation modelling (SEM) with partial least squares (PLS). Findings The findings show that the fear of failure in entrepreneurship is negatively influenced by factors such as limited financial access, risk aversion, and past business failures. However, aversion to stress and hard work did not have a significant impact. The findings also show that social capital could potentially mitigate these negative factors. Research limitations/implications The theoretical and practical implications of this study manifest in revealing the difficulties entrepreneurs encounter in developing countries like Iraq, where entrepreneurship is vital for economic growth. The study's limitations stem from its focus on one country and the use of a single survey method. Future research could use varied methods across multiple countries for a more comprehensive view. Originality/value This study sheds light on the factors that are obstacles for entrepreneurs to starting a business in emerging economies like Iraq.
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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 | 0.002 |
| 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".