Marketing Efficiency of Date in Khartoum State, Sudan
Bibliographic record
Abstract
The study aimed to measure the marketing efficiency of date at wholesalers in Khartoum State in the year 2013. The study depended mainly on primary data which was collected through questionnaire. About 35 of wholesaler were selected through simple random sampling. Also, secondary data was collected from sources related to topic of the study. The data was analyzed using descriptive statistics tool. Also, quantitative analysis techniques were used to calculate net marketing margins and marketing efficiency for wholesalers. The study revealed that 82.9% of wholesalers bought the product from local traders. On the other hand, about 68.6% of wholesalers sold their product to retailers. About 25.30, 33.20, 13.30 and 7.40 SG/Sack represented Gross Marketing Margins for Gondaila, Tomoda, Brakawie and Gawa, respectively. About 25.25, 6.15, -13.75 and -20.65 SG/Sack represented Net Marketing Margins for Gondaila, Tomoda, Brakawie and Gawa, respectively. The Shepherd’s Formula indicated that Gondaila, Tomoda, Brakawie and Gawa got marketing efficiency equal to 17.41, 13.09, 06.06 and 02.45, respectively. The main obstacles that facing wholesalers in marketing of date were follows: transportation cost, taxes, losses and finance. Increasing Net Marketing Margins at wholesaler’s Brakawie and Gawa in Khartoum market through reducing marketing costs (minimize economics and normal risks (balance between supply and demand beside control store pest) transportation and taxes cost items). In this efficiency activity, investment and credit services should be encouraged and provided, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".