The impact of packet size on inventory turnover of fmcg products in Pakistan [wholesaler & retailer perspective]
Bibliographic record
Abstract
A question arise, is there any impact of different packet sizes on consumer buying pattern. The study is focus on retailers and wholesaler perspective in Pakistan context. There are 75 respondents were include in research and handed over them a questionnaire having questions regarding with selling pattern of four different packet sizes (i.e. sachet, quarter pack, half pack and full pack) that formulated data of 300 observations (75*4) and asked them about to buy stock on monthly basis. Data converted from monthly basis to yearly basis in order to compose it into inventory turnover. Simple linier regression (OLS-Model) has been used in analyzing data. It was assumed that there is negative impact of packet size on inventory turnover. Several test has been applied on data include (Test of Sufficiency, Test for Significance and Test for Specification). Result matched with hypothesis and negative impact has been shown that represent that with reducing packet size, inventory turnover increases. Beside this it also shows that mostly people in recent context prefer to buy more sachet or quarter pack as compare to half pack and full pack.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".