An Estimation of Market Size for Microfinance: Study on the Urban Microentrepreneurs in Selangor, Malaysia
Bibliographic record
Abstract
Malaysia is a fast growing developing country where majority of the people are Muslim. Due to the religious bindings, Muslim prefers Shariah compliant Islamic credits instead of conventional interest based credits. At the same time, non-Muslims can also consider Shariah compliant Islamic credit because it is considered as the ethical credit. However, still many microentrepreneurs are not receiving the Shariah compliant Islamic microfinance products because they have negative perceptions about the credit and interest (riba). Therefore, this study aims to assess the demand for microfinance among the microentrepreneurs in the State of Selangor, Malaysia and thus, determine the potential market size. Data of the study were collected based on a questionnaire survey from 550 microentrepreneurs from the urban areas of Selangor. It was found that only 12.2 per cent of them received microfinance from various microfinance institutions and banks. However, the study found that still there is potential for microfinance borrowing with around 55,000-128,000 microenterprises in Selangor, Malaysia. Therefore, Islamic microfinance institutions should try to expand their market size by promoting these potential microfinance borrowers among the existing microentrepreneurs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".