Consumer self‐construal and trust as determinants of the reactance to a recommender advice
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 Commercial recommendation agents (RAs) represent an important type of the decision support systems (DSSs) that are widely used by online retailers and firms. To date, little is known about the factors that shape the user's decision making and reactance toward the recommendations of these agents. Building on theories from psychology and information systems domains, this research proposes that a user's self‐construal and trust are two relevant factors that interact to shape the behavior toward the RA advice. Two studies, the first conducted using potential online customers and the second conducted at a behavioral laboratory, provided support to this proposition. The first study considered RA trust and showed that activating the interdependent self leads users with low (high) trust to exhibit high reactance behavior toward the RA advice. The second study variated trust using trust cues and corroborated the latter finding, while showing no important impact for the psychological reactance trait. As expected, in both studies the reactance behavior of independent users was not affected by trust. These results contribute by underscoring that social interdependence extends to RAs because the role of trust becomes salient when the interdependent self is activated for a user.
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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 | 0.002 | 0.006 |
| 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 | 0.000 | 0.000 |
| 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 it