Reexamining Relative Advantage and Perceived Usefulness
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
Relative advantage and perceived usefulness are often used interchangeably in the literature. In this paper, the authors argue that this limits the understanding of the adoption of ICTs, especially when there are multiple alternatives. To address this issue, the authors reexamine relative advantage in relation to perceived usefulness, providing a re-specification of relative advantage and empirically testing a model that explores the roles of these constructs in explaining and predicting the adoption of a new technology in the presence of an existing one. The results demonstrate that perceived usefulness and relative advantage are related but distinct constructs. In particular, relative advantage fully mediates the effect of perceived usefulness of existing technology on the intention to use a new technology, and partially mediates the effect of perceived usefulness of the new technology on the intention to use it. The findings have important theoretical implications that help investigators better apply these constructs in research, as well as practical implications for ICT promotion strategy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 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