Hindering and fostering factors SMEs performance in the Western Province of Sri Lanka
Bibliographic record
Abstract
It is very significant to understand what factors affect the failure of Small and Medium Scale Industries (SMEs). The study is to empirically identify factors effecting on SMEs for the success and it’s an exploratory using a sample form Western province in Sri Lanka. To study the failure factors of SMEs in Western province in Sri Lanka., forty six (46) samples were selected through systematic random sampling throughout the year of 2010 to 2016. A questionnaire is used for collecting primary data for this study and it includes five point of Likert scale questions. Researcher gives more weight to failed ventures because this research main objective is find out factors affecting the rate of failure of small business enterprises. Reliability of dimensions is test using with the support of Cronbach’s Alpha Value. Validity of dimensions is test using convergent validity using KMO values. The results of the study revealed that out of eight factors affecting to failure such as Owner manager’s attitude, Financial Issues, Raw material availability, Labor Availability, Technology Issues, Entrepreneurial knowledge, Feasibility study and Government Support ; the raw material availability and the government support are the most important factors for the success.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".