Consumers’ preference and willingness to pay for enriched snack product traits in Shashamane and Hawassa cities, Ethiopia
Bibliographic record
Abstract
Abstract This study investigated the consumers’ preference and willingness to pay for enriched snack product traits. Using a choice experiment framework, we generated 8400 observations from a random sample of 700 respondents in Shashamanne and Hawassa city administrations. Taste parameters and heterogeneities were estimated using the generalized multinomial logit (G-MNL) model. The results reveal nutrition and/or health claim labeling is the most influential trait on the consumers’ decision to buy enriched snack products followed by mango flavor, sorghum chickpea main ingredient, price, and mixed shape. The WTP estimates show that consumers are willing to pay a premium for nutrition and/or health claim labeling equal to 1.43, 1.6, and 8.03 times higher than for a change in the flavor of the products from tomato to mango, the improvement of main ingredients to sorghum chickpea, and change of the product shape from spherical to mixed shape, respectively. The heterogeneities (variations) around the mean taste parameters were partially explained by sex, family size, and educational levels of the respondents. Generally, the consumers in the study areas prefer buying sorghum chickpea main ingredients, a combination of different shapes (mixed shape), mango flavored, and nutrition and/or health claim-labeled enriched snack products. Therefore, we suggest designing and implementing innovative ways of promoting snack products to urban communities with a deliberate focus on these traits to create a snack with the best combination. Given the high literacy of urban consumers and influential role of nutrition and/or health claim labeling trait on consumers’ decision, the trait-based promotion and marketing of the products constitute the right strategy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".