A Framework for the Contract Management System in Cloud-Based ERP for SMEs in the Construction Industry
Bibliographic record
Abstract
Small and medium-sized enterprises (SMEs) account for a large percentage of market structure in the construction industry; however, adoption and diffusion of innovation associated with information technology (IT) in these types of enterprises are slow compared with large-sized enterprises. During the project lifecycle, contract management, as the core business of enterprises, is complex and has a profound influence on project schedule, cost, and risk control. However, few studies have focused on IT innovation and application in contract management related to data management, information integration, and communication from the enterprise management perspective. Therefore, a framework for a contract management system in cloud-based enterprise resource planning (ERP) is proposed for SMEs in the construction industry which integrates the database management system (DBMS), cloud-based ERP, and feature-based modeling. An illustrated example of a medium-sized real estate enterprise is provided to demonstrate applicability of the framework to facilitate contract management in the construction industry.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".