Technical, Allocative, and Economic Efficiency and Profitability of Black Soldier Fly Farming Among Smallholder Farmers in Selected Counties in Kenya
Why this work is in the frame
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Bibliographic record
Abstract
Black Soldier Fly (BSF) has emerged as a source of protein and frass fertiliser, while also helping reduce greenhouse gas emissions. Despite promising opportunities in BSF farming, low production levels, labour-intensive technologies, limited input resources, and rearing systems hinder the optimization, consumption, and marketing of BSF and its products. Therefore, the study aimed to determine the technical, allocative, and economic efficiency and profitability of BSF farming among smallholder farmers in selected counties in Kenya. Guided by the production theory of the firm and profit maximization theory, the research analysed secondary data from 373 smallholder BSF farmers across 12 counties in Kenya, collected by the National Agricultural Value Chain Development Project (NAVCDP) in June and July 2024. Data analysis was conducted using STATA software version 17.0, employing Cobb-Douglas stochastic frontier production and cost functions, a two-limit Tobit regression model, and metrics such as gross profit margin (GPM), return on investment (ROI), and benefit-cost ratio (BCR). The results showed that the average technical efficiency was 72%, allocative efficiency was 56%, and economic efficiency was 40%, indicating that farmers in the study area were generally inefficient in their production activities. Additionally, factors such as experience, credit access, source of income, structure size, herd size, feeding times, organic waste feeds, substrate bought, agro-weather information services, output market access, and transport services significantly affected the efficiency of BSF farming. Profitability analysis revealed that production and sales of both BSF larvae and frass fertiliser yielded higher profits, with GPM, ROI, and BCR of 51.41%, 8.77%, and 1.18, respectively, compared to selling only larvae or only frass. The study recommends that the government and other development partners develop good-quality feeder roads, establish public markets, and provide grants to farmers. Farmers should also join co-operatives and informal credit/savings groups to access credit.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it