Empirical Determinants of the Choice of Intermediaries by Selected Multinationals Operating in Nigeria’s Food/Drinks Market
Bibliographic record
Abstract
This study examines in an empirical manner variables that producers tend to consider in order to determine the choice for a profitable business in the entire distributive process. This endeavor however poses a number of problems for the producers. Seven problems were however identified around which objectives, research questions and hypotheses were generated. In order to provide solutions, descriptive research design was adopted. A sample of 5 (five) multinational companies with well over 30 years of operations in Nigeria, N100billion in Assets, with extensive distributive networks across the country were used for the study. Each of these companies fundamentally operates a network of over 100,000 intermediaries across the nation on a sustainable basis. The instrument for data collection from respondents was a closed-ended questionnaire, piloted for reliability and validity tests. On the strength of these tests, the instrument was adjudged suitable for data collection. Five (5) of the variables investigated, turned up significant. Intermediary’s Knowledge of Product, Market and Customer; Financial Standing of Intermediary and Extent of Competitive and Complementary products being carried by an Intermediary tied as the three most important determinants in producers’ selection of intermediaries. Other determinants are as indicated under the discussion and conclusion. Findings revealed the extent to which each of these empirical factors effectively and efficiently determine the choice of marketing intermediaries in the multinational companies surveyed. Our conclusions and recommendations are relevant to other developing countries especially in Africa.
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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 | 0.011 |
| 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 | 0.001 |
| 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".