Individual differences in consumer value for mass customized products
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
ABSTRACT Mass customized products, compared with mass marketed alternatives, offer advantages for optimizing performance outcomes, improving aesthetic appeal, and matching products' symbolic meanings with consumers' expressive desires. Despite having identified these value drivers for mass customized products, extant research has not connected those value drivers to individual differences among consumers. As a result, researchers' and practitioners' abilities to predict consumer value for mass customized products remain limited. This study advances and tests a model of individual differences associated with the perceived value of a customized product and mediated by involvement and perceived risk. A field survey administered to a sample of 240 participants provided data to test the model. Path analysis using structural equations modeling suggests that consumer value for mass customized products differs according to individual differences in need for uniqueness, need for optimization, and centrality of visual product aesthetics. Results also suggest that product category involvement and perceived risk are informative theoretical perspectives from which to study consumer value for mass customized products. The findings hold implications for how firms should approach the design of mass customization toolkits and how they should structure marketing communications promoting mass customized products. Copyright © 2013 John Wiley & Sons, Ltd.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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