Nonlinearities Between Attitude and Subjective Norms in Information Technology Acceptance: A Negative Synergy?1
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
Empirical results both from information technology acceptance research as well as from other fields suggest that attitude and subjective norms may have a nonlinear relationship. Based on the economic theory of complementarities, the present paper hypothesizes a substitution relationship or negative synergy between attitude and subjective norms in organizational IT use contexts. Employing two methods for modeling and measuring nonlinear effects of latent constructs, as well as two approaches for visualizing and interpreting interaction and quadratic terms, structural equation modeling analysis of data collected from 258 users of a variety of IT applications in 14 organizations provides support for the hypothesis that attitude and subjective norms were substitutes in predicting intention to use.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it