Inhibitors and Enablers as Dual Factor Concepts in Technology Usage
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
Information systems (IS) research has focused extensively on the factors that foster adoption and usage. A large body of work explores overall beliefs about system usage, antecedents of system satisfaction, and other perceptions that enable system success, create positive attitudes, and encourage usage. However, much less attention has been given to what perceptions uniquely inhibit usage. In large part, this is due to the implicit assumption that the inhibitors of usage are merely the opposite of the enablers. This paper proposes a theory for the existence, nature, and effects of system attribute perceptions that lead solely to discourage use. I posit that usage inhibitors deserve an independent investigation on the basis of three key arguments. One, there exist perceptions that serve solely to discourage usage, and these are qualitatively different from the opposite of the perceptions that encourage usage. Two, these inhibiting and enabling perceptions are independent of one another and can coexist. Three, inhibiting and enabling perceptions have differing antecedent and consequent effects.. As unique beliefs, inhibiting perceptions can add to our understanding of the antecedents of usage or outright rejection. Further, such inhibitors may not only be important to the IS usage decision, they may be more important than enabling beliefs.
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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 | 0.003 | 0.005 |
| 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 | 0.002 |
| 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