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Record W4385732832 · doi:10.1080/01446193.2023.2239381

Integration mechanisms for material suppliers in the construction supply chain: a systematic literature review

2023· article· en· W4385732832 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

VenueConstruction Management and Economics · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSupply chainSystematic reviewBusinessSupply chain managementProcess managementKnowledge managementComputer scienceMarketing

Abstract

fetched live from OpenAlex

The construction industry has long been criticized for its fragmented, inefficient, and uncoordinated supply chain. Thus, construction companies are actively looking for new strategies to overcome these issues and to improve their productivity. Supply chain integration is one strategy and many articles have addressed the mechanisms to help integrate the construction supply chain. However, little interest has been paid to material supplier integration despite their important role and their vast experience in the market. Hence, this study aims to identify the mechanisms that could contribute to facilitate material supplier integration in the construction supply chain. A systematic literature review was conducted to uncover the studies on this topic. A total of 310 articles were reviewed and analyzed to first reveal six integration mechanism categories: supplier qualification, supplier development program, contractual and relational policies, information sharing and integration systems, joint team working and problem solving, as well as supplier integration evaluation. Secondly, this study proposes a roadmap to illustrate when these mechanisms should be implemented in a construction project, according to both the project phases and the project delivery system. Finally, research gaps in the field are identified as well as future research directions that could be further explored by researchers and professionals.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.015
GPT teacher head0.213
Teacher spread0.199 · 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