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Record W2797449706 · doi:10.5539/jas.v10n5p384

Marketing Efficiency of Date in Khartoum State, Sudan

2018· article· en· W2797449706 on OpenAlexvenueno aff
Abda Abdalla Emam, Wafa Abd-Alrhaim Abu-Algasim

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMarketingProduct (mathematics)BusinessDescriptive statisticsSimple random sampleInvestment (military)Agricultural scienceMathematicsStatistics

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.312

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.225
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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