Analysis of Factors Influencing Marketing Channel Choices by Smallholder Farmers: A Case Study of Paddy Product in Wet and Dry Season of Prey Veng Province, Cambodia
Bibliographic record
Abstract
This study analyzes factors influencing marketing channels that were chosen by paddy smallholder farmers in the wet and dry season. The aims focused on determining the factors influence marketing channel choices to be able to reveal out the need for smallholder farmers to increase their productions and investments to formulate policies to enhance them such as increasing revenue, poverty alleviation, food security, and sustainable development. The primary data was collected through structured and semi-structured interviews with 216 smallholder farmers cultivated in both seasons, 12 collectors, 12 traders, 12 millers, 6 wholesalers, and 6 retailers by analyzed with Multinomial Logit. Results revealed that socio-economic, institutional, and marketing factors were different statistically significant influence into marketing channel choices in both seasons. These findings relate to factors that need to resolve and stimulate smallholder farmers to choose the right marketing channels by suggestion to policymakers. The outcomes of policies aim to stimulate and encourage extension office to support, sharing experiences, and knowledge to smallholder farmers who older, low experiences, and low educations. To improve extension services by the focus on telecommunications, storage facilities, and rural infrastructures. Moreover, urge smallholder farmers to market participation, and enhance market competitions. Finally, the policymakers should work efforts to improve and enhance the ongoing investments in the water supporting such as small, medium, large irrigation systems, and so forth for reducing the constraints.
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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 | 0.001 | 0.000 |
| 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".