The effects of system and information quality on acceptance of digital public service transportations
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
The application of ICT in central and regional governments to cities in Indonesia seems to be the new face of the National bureaucracy, not least with digital public transportation services, Surabaya is a pilot application of smart cities because one of them implementing the Surabaya Smart Transportation System (SITS), this condition further strengthens that policy Public digital services are taken to make it easier for the public to monitor the crowd or the density of the highway, unfortunately, if you review the SITS comment column on Google Play, the negative sentiment is far big more than the positive sentiment. So, this study aims to capture the phenomenon of resistance by exploring the quality of information and system quality as predictors of public acceptance of the application of SITS. A result, empirically the quality of information and the quality of the system indirectly affect public acceptance of the application of SITS, as among the findings served that system quality is more dominant in influencing acceptance. So, it is highly recommended that the city government pays attention to the development of SITS applications based on system reliability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.009 |
| Open science | 0.002 | 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