The Impact of Microfinance Services on Malaysian B40 Households’ Socioeconomic Performance: A Moderated Mediation Analysis
Bibliographic record
Abstract
This research examines the influence of microfinance services on the socioeconomic performance of Malaysian B40 households, which are considered vulnerable communities in Malaysia. Mainly, it explores the mediating role of entrepreneurial competencies and financial management practices in the relationship of microfinance services with households’ economic well-being, entrepreneurial success, and social wellbeing. Likewise, this research also examines the moderating role of microfinance institutions’ service efficiency in the success of microfinance services to improve households’ socioeconomic outcomes. The responses were collected from the participants of Amanah Ikhtiar Malaysia, the largest microfinance institution serving the low-income population of Malaysia. Employing the structural equation modelling approach, results show that microfinance financial services and non-financial services positively influence households’ socioeconomic performance through entrepreneurial competencies and financial management practices. On the other hand, microfinance financial services are also found to have significant direct influence on households’ socioeconomic performance. Further, results also indicate that microfinance institutions’ service efficiency positively moderates the influence of financial services to improve households’ socioeconomic performance. This is novel research that introduces human capital development as an underlying mechanism in the household economic portfolio model, suggesting that microfinance interventions develop human capabilities among their participants, which further assist them in the efficient management of financial and business affairs, thus, improving socioeconomic outcomes.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".