Behavioural Determinants of Impulse Buying – An Empirical Study of a Metropolitan Hub of Pakistan
Bibliographic record
Abstract
Unpredictable shopping expenses take a toll on family's monthly budget in poor economies like Pakistan. Studying the determinants to these uncalled and impulsive shopping urges is of the essence when the objective is to plan for the future. This study explores the main factors affecting consumers' unplanned buying from departmental stores in Pakistan's metropolitan city. The indicators included buying behaviour, customers' emotions, promotion & advertisement, physical environment, and price of products. The objective was set to examine the leading factors influencing customers to buy in departmental stores (Metro Cash and Carry, Al- Fateh and Hyper Star) of Lahore, Pakistan. The survey approach was taken in this study through a convenience sampling design with a sample size of 250. The estimation results of median regression were derived from the conclusion by using the SPSS software. The results support policy makers in developing social and economic regulations that assist individuals in avoiding impulse buying.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".