The Assessment of the Maturity of Informatization in Assembly-Building Projects Utilizing the CMM-CME Methodology, Taking a Project in China as an Illustration
Bibliographic record
Abstract
Owing to its rapid advancement, information technology has emerged as a critical tool in assembly construction for addressing market demands, improving project quality, and reducing costs. However, the absence of unified informatization standards within the assembly construction industry has led to the adoption of different technologies and systems by various businesses during the development of informatization systems; this has generated issues such as unbalanced development and mutual incompatibility. While researchers have examined these issues, a comprehensive assessment of the maturity of informatization in assembly-building projects is lacking. Assessment of the maturity of informatization can provide evaluation standards and methods for the development of informatization of assembly buildings, explore the important and difficult points of applying informatization technology to assembly buildings, and put forward corresponding countermeasures and suggestions to promote the benign development of informatization of assembly buildings. Therefore, this study strives to develop a model for assessing the maturity of informatization of assembly-building projects. This study begins by determining the level of the maturity level of informatization, key process areas, and key practices for assembly-building projects using the capability maturity model (CMM). On this basis, the maturity evaluation index system was constructed through expert interviews and questionnaires. Furthermore, in order to assign weights to the indicators comprehensively, the ordinal relationship method and entropy weight method were implemented. The evaluation criteria were determined by consulting the relevant literature and expert opinions. Followingly, an evaluation model was established based on the cloud matter element (CME) theory. Finally, a case study demonstrates that the methodology can be utilized to quantify the maturity of project informatization. In conclusion, this study unearths a system for assessing the level of maturity of informatization of assembly-building projects, which provides a valuable reference for promoting the continuous development of the maturity of informatization in assembly-building projects.
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.
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 | 0.002 | 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 | 0.000 |
| 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".