Impacto da renovação de vitrines: um experimento
Bibliographic record
Abstract
The window display was always a challenge subject research in a retail environment. We can mention some authors to base this experiment, like Mehrabian and Russel (1974) about S.O.R (Stimulus-Organism-Response) theory, Sen, Block e Chandran (2002) that explicit how important is the window display and product information to associate the shopper entry in the store and consequently increase sales, and also, the research made by Oh and Petrie (2002) about window display with product display versus store image, that refer a low or high shopper cognitive load. This experiment aim measures the relationship between rising frequency of window display changes and growth of product sales (in units) in the fashion retail stores. It will also contribute for better understanding about these variables in an external retail environment. Through field experiment classified as quasi-experiment and getting time series analysis, it was realized a study in four stores in a popular fashion apparel chain (low income), located in a commercial street and divided /called by A, B and C stores. Changes in the window display were frequently made, every 3 days, with fashion young female (women from 16 to 24 years old) looks suggestion displayed in the store A window, over a certain period, from 4 to 13 January 2018, and, any other change was made in the window displays from B and C stores. The purpose of that was to investigate the influence from window displays on products physical sales. There was an exception in a C store, where an internal display (dummy) was put inside the store beside the product equipment. Stores were selected with same cluster standards, including same variables of behavior for all 3 stores. These variables took into consideration the following aspects: sales volume, stores size square meters, shopper income profile, store location, equipment and display formats. The results obtained shows that rise frequency changes on window display in A store provided a growth of physical sales volume with 43 pieces of clothing, and 41 and 56 in B and C stores respectively, however in the last store the sales volume was higher than others due to internal display (dummy), which showed us that complement information to the shopper can help on sales. There was statistical difference below 0.1% over p-value in a comparison between 3 stores (A, B and C). These comparisons were required due to the exception of C store and internal display. In this way, we could find significant evidence in the relation between rising the offering of products in the window display and growth of physical product sales, into believing that it can influence shopper enter in the store and buy products when a window display is prepared with low cognitive load toward to these clients.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".