A Systematic Literature Review of Empirical Research on the Impacts of e‐Government: A Public Value Perspective
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
Abstract While government organizations continue to invest in e‐Government systems, there is still uncertainty as to the benefits that can be generated. Without clear expectations, it will be impossible for managers to measure and evaluate outcomes. This systematic literature review examines 60 empirical studies on the impacts of e‐Government published in the leading public administration and information systems journals. The impacts are classified using public value theory, first, by the role for whom value is generated and, second, by the nature of the impact. The results show that the most commonly studied impacts are productivity for the taxpayers and clients, client satisfaction and service quality for clients, and improved trust and communications for citizens. There are many areas where limited research has been conducted. We maintain that there is a complex network of immediate and indirect impacts that must be considered by public managers in their analysis of potential investments.
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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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