Store brands’ purchase intention: Examining the role of perceived quality
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
Considering the increase of the store brand's market share globally, the present study addresses the following question: “Does the consumer product perceived quality influence store brands’ proneness?”; or in other words “Does product perceived quality influence store brands’ purchase intention?”, since perceived quality is a customer-based undertaken variable. The present study proposes and empirically tests a conceptual model of the influence of perceived product quality of store brands relative to perceived value and purchase intention. Structural Equation Modelling (SEM) was developed on a sample of 439 consumers, distinguishing between consumers with high perceived quality (HPQ) and low perceived quality (LPQ). Our findings highlight that store brands’ purchase intention is strongly influenced by confidence for both HPQ and LPQ customers, followed by product price. Additionally, our results suggest the moderating role of perceived quality on some of the proposed relationships. Store brand managers and retailers could develop market segmentation and perform marketing strategies based on customers’ perceived quality.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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 it