Developing New Technology Acceptance Model With Multi-Criteria Decision Technique: An Implementation Study
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
This study aims to develop and implement a new Technology Acceptance Model (TAM) to verify and explain users’ acceptance of SAP software. The structural equation model (SEM) technique is used with the AMOS program for the adoption process. General structural model, which includes Experience, Voluntariness, Perceived Enjoyment, Perceptions of External Control, Computer Self Efficacy, Output Quality and Job Relevance, is developed with Analytical Hierarchy Method (AHP) and Pareto Analysis by deciding variables from previously original developed models which are called TAM1, TAM2 and TAM3. New TAM is tested to a sample of 384 SAP users in a company that serves in metal production. Results illustrates that new TAM is an appropriate tool to explain and understand users’ acceptance of SAP besides of being flexible and easily implemented. SAP users’ job relevance and their perceptions of external control are the most important variables that affect perceived usefulness and perceived ease of use in the model.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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