Low Prices are Just the Beginning: Price Image in Retail Management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recent managerial evidence and academic research has suggested that consumer decisions are influenced not only by the prices of individual items but also by a retailer's price image, which reflects a consumer's impression of the overall price level of a retailer. Despite the increasing importance of price image in marketing theory and practice, existing research has not provided a clear picture of how price images are formed and how they influence consumer behavior. This article addresses this discrepancy by offering a comprehensive framework delineating the key drivers of price image formation and their consequences for consumer behavior. Contrary to conventional wisdom that assumes price image is mainly a function of a retailer's average price level, this research identifies several price-related and nonprice factors that contribute to price image formation. The authors further identify conditions in which these factors can overcome the impact of the average level of prices, resulting in a low price image despite the retailer's relatively high prices, as well as conditions in which people perceive a retailer to have a high price image despite its relatively low average price level.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it