The Determinants of Marketing Efficiency of Cocoa Farmer Organization in Cameroon
Bibliographic record
Abstract
Access to the market for smallholder is a permanent concern of actors of development in developing country. Many studies carried out arrived at conclusions according to which the smallholder still badly connected to the agricultural market (Key et al., 2000; Gabre-Madhin, 2001; Gabre-Madhin, 2009). One of the solutions is to improve the access of those smallholder to the market is the collective marketing of their product through the farmer’s organizations (FOs). These FOs being regarded as small commercial firms, the question of their efficiency remains a permanent concern for the farmers who do always participate to this form of marketing. This article thus aims of measuring the differences in efficiency between the forms of FOs and identifying the determinants of these differences in efficiency. The estimation of efficiency levels is made by the DEA model and the identification of the determinants of these efficiency levels is made by the model of negative binomial regression. Globally, the results show that FOs commercial efficiency is still low. This level is estimated at 0.57. Besides, efficiency is significantly affected by FO’s internal factors (FOs’ age, number of years spent in the position by the FOs’ administrative staff, governance level of FOs, education level of FOs’ leaders and leaders’ productive capacity) and external factor (area removal). In particular, the results indicate on the one hand that the age at which FO is mature for marketing efficiency is 32 months. This age which seems to be rather long may be due to the fragility of most of FOs. On the other hand, the estimation indicates that the weight of productive leaders encouraged them to meet the objectives of farmers.
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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 | 0.002 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".