Engineering and Design for Sustainable Construction: A Bibliometric Analysis of Current Status and Future Trends
Bibliographic record
Abstract
The purpose of this study is to investigate the state of engineering and design research for sustainable construction. It aims to report the current status and future trends within this dynamic field, combining econometric and content analysis using the Bibliometrix R encapsulation tool. This study reviewed academic journals using bibliometric analysis. We selected articles by searching the Scopus database. Primarily relevant articles were identified and screened. The dataset comprised a substantial compilation of 731 journal articles from 278 sources published between January 2000 and June 2023, which formed the basis of the in-depth analysis. The importance of sustainable construction is gradually gaining more attention, and engineering and design are the significant phases of construction. This research identifies that sustainable construction is nothing in isolation; instead, it warrants the holistic integration of multiple factors, as illustrated in the Sankey diagram. Recycling, durability, life cycle assessment, innovative materials, and energy efficiency have emerged as central themes, reflecting global concern to enhance sustainability, reduce environmental impacts, and optimize resource utilization. This study is a valuable resource for researchers, practitioners, and policymakers, offering guidelines for collaborative efforts towards sustainable development. This paper paves the way for interdisciplinary cooperation and strategic alignment among diverse stakeholders, promoting innovative approaches to sustainable construction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.190 | 0.280 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".