Influence of Sales Promotion Techniques on Consumers’ Purchasing Decisions at Community Pharmacies
Bibliographic record
Abstract
This research aims to identify the most prevalent and impactful sales promotion tools used by pharmaceutical companies on consumers' purchasing decisions at community pharmacies. A cross-sectional study design was carried out using the non-repeated random sampling technique. Standardized questionnaires were administered by means of face-to-face interviews or via emails. The relative importance of prevalence (RIP) and the mean evaluation of effectiveness (MEE) were determined for all studied marketing tools for the different groups of respondents (pharmaceutical sales representatives (PSRs), community pharmacists, consumers, and the entire sample). Inter-individual differences in RIP and MEE were assessed by computing the coefficient of variation, whereas inter-group differences were determined by one-way analysis of variance (ANOVA) with the Scheffé test as a post-hoc test. Research findings showed that, according to all respondents, the consumer promotion technique had the strongest impact on consumers' purchasing decisions while merchandising was the most common sales promotion technique at community pharmacies. PSRs and pharmacists identified trade promotion as the most effective and prevalent technique. Furthermore, research findings showed that, according to all respondents, the following sales promotion tools had the strongest impact on consumers' purchasing decisions: arrangement and design of showcases among the studied tools for merchandising; buy 1 and get 2 among the studied tools for consumer promotion; and gifts among the trade promotion studied tools. The same tools were identified as the most prevalent by all respondents. Free samples of promoted products appeared to be the most prevalent tool, but at the same time was the least effective. In conclusion, the results of the present research enable an understanding of which sales promotion tools are commonly used at community pharmacies and which ones have the strongest impact on consumers' purchasing decisions.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".