Prioritization criteria for enterprise resource planning systems selection for civil construction companies: a multicriteria approach
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
In this study, as a first step, a set of criteria and subcriteria was proposed for enterprise resource planning (ERP) systems selection for companies in the civil construction industry that is based on a review of the literature concerning the application of multicriteria models for evaluating ERP systems. Subsequently, after validation of these criteria by a group of information technology specialists, a field survey was developed based on the administration of a questionnaire and the use of the analytic hierarchy process. This survey enabled us to perform an analysis of the judgment consistency of the 11 respondents who participated in this study and to capture their perceptions of criteria importance. The survey revealed that respondents considered the software criterion to be the most important and showed the importance of subcriteria within groups of criteria, which greatly contributed to the decision-making process in ERP systems selection.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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