Product Smartness and Use-Diffusion of Smart Products: The Mediating Roles of Consumption Values
Bibliographic record
Abstract
This study proposes and tests the antecedent effects of product smartness on the consumption values using smart phones. The study also examines the relationship between consumers’ value perception and use-diffusion. Results show that the six smartness dimensions have different impacts on each of the values. Multifunctionality and adaptability are the primary antecedents of functional value perception. Reactivity, humanlike interaction, multifunctionality and adaptability are positively related to perceived emotional value. Both functional and emotional values reinforce higher usage behavior as well as new usage behavior, thereby broadening the applicability of the technology. Consumption values mediate the relationships between some product smartness dimensions and the usage rate. Results also suggest that the smartness features that act as the primary drivers for intense usage are not the same features that drive the decision to use the product in various ways. The findings support the use of differentiated marketing strategies for the use-diffusion of each smart product.
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How this classification was reachedexpand
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".