Sustainability, Whole Life Costs, and Information and Communication Technologies: A Review of Published Works
Bibliographic record
Abstract
This paper reviews research work that has attempted to assess the financial benefits of adopting sustainable design and construction practices, and identifies a connection to information and communication technology (ICT) used to facilitate the adoption of those practices. A review of the literature found that: researchers disagree on the precise impact of sustainability upon the whole life costs (WLC) of buildings; the impact of sustainability upon usage costs tends to be ignored despite their considerable size; and the use and adoption of ICT tools remains costly, limited and inefficient in sustainable projects. Future research needs therefore to focus on: investigating a sufficient number of conventional and sustainable buildings, assessing all types of long-term costs incurred in those buildings, evaluating buildings' usage costs in more details, and using empirical documented cost data whenever these are available. Future research also needs to show ways of improving sustainable design and construction processes by: assessing the specific impact of ICT tools on related processes, assessing the collaborative decision-making process in general, and developing a comprehensive model to ensure effective adoption and implementation of ICT solutions that have shown to improve design and construction processes.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.009 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".