The effect of perceived barriers on social entrepreneurship intention in Malaysian universities: The moderating role of education
Bibliographic record
Abstract
This paper attempts to identify barriers of social entrepreneurship intention by the moderating role of education amongst research universities in Malaysia.Entrepreneurship is regarded as the major factor for economic development while social entrepreneurship is considered as the alternative method of solving social problems.Entrepreneurship is not new for Malaysia as is evident from various policies and programs initiated by the government.However, social entrepreneurship is a relatively new phenomenon in Malaysian context that requires much attention.To promote entrepreneurship we need to know the barriers influencing on entrepreneurship to overcome the barriers and promote new policies and measures to create new ventures.The study used Ajzen's Theory of Planned Behavior as a framework to investigate the barriers of social entrepreneurship intention.Data was collected through questionnaire and confirmatory factor analysis was conducted by using AMOS 18.The multilevel sampling design was used with purposive sampling scheme in Malaysian research universities.The findings of this study show that overall students consider the lack of competency, lack of self-confidence and lack of resources were the barriers that affect social entrepreneurial intentions.Results also show that the social entrepreneurial education moderated the relationship between the perceived barriers and social entrepreneurial intentions of the students.This implies that teaching of social entrepreneurial can help to reduce perceived barriers.Also, the present study premises future directions that a cross country analysis between developing countries and between developed and developing countries can be done to figure out barriers of social entrepreneurship intention amongst students.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".