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Record W4401898350 · doi:10.1016/j.jenvman.2024.122293

Temporal evolution and thematic shifts in sustainable construction and demolition waste management through building information modeling technologies: A text-mining analysis

2024· article· en· W4401898350 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Environmental Management · 2024
Typearticle
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPrefabricationDemolition wasteDemolitionThematic analysisReuseBuilding information modelingEngineeringSustainabilityPopulationKnowledge managementComputer scienceCivil engineeringQualitative researchOperations managementSociologyWaste management

Abstract

fetched live from OpenAlex

Construction and demolition activities are significant contributors to waste generation worldwide. As population growth accelerates worldwide, the amount of construction and demolition waste (C&DW) will increase proportionally unless proactive measures are implemented. This study analyzes the evolving research landscape on utilizing Building Information Modeling (BIM) technologies to advance sustainable C&DW management practices. A comprehensive text-mining analysis is conducted on 493 scholarly publications covering evolutions from January 2009 to February 2024 using the PRISMA framework. The research objectives are: (i) to identify key themes in domain of BIM technology in C&DW management using VOSviewer, (ii) to map the temporal evolution of research focus using SciMAT, and (iii) to identify emerging thematic trends.Co-occurrence analysis reveals three major research themes: (i) the use of digital twins and prefabrication for waste reduction, (ii) integrating environmental impact assessments, and (iii) data-driven decision-making. Strategic diagrams produced by SciMAT software uncover shifting priorities over the study period, with “reuse and recycling” emerging as motor themes, and “Prefabrication” (CIT = 481), “Decision Making” (CIT = 66), “Material Passport” (CIT = 92), and “Digital Twin” (CIT = 44) emerging as high-centrality and transversal themes. Temporal evolution mapping unveiled progressive integration of BIM tools such as (i) digital twins (TLS = 34, OCC = 9) and (ii) prefabrication (TLS = 40, OCC = 14), presenting opportunities to optimize waste reduction. This study offers a robust overview of the field, aiming to inform a diverse audience, including researchers from various disciplines, policymakers and industry professionals interested in advancing sustainable practices in C&DW management through innovative digital solutions. • The integration of BIM tools in C&D waste studies is examined using text mining. • Four distinct periods are observed in WoS database from Jan 2009 to Feb 2024 • Co-occurrence node analysis identifies 3 distinct clusters among 493 studies. • Strategic diagram shows distinct theme developments in the third and fourth periods. • Trend analysis supports decision making by funding agencies and policy makers.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.187
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it