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Record W3217272345 · doi:10.1680/jmapl.21.00019

Diffusion of platform thinking as an innovation in the construction supply chain

2021· article· en· W3217272345 on OpenAlexfundno aff
Stuart Grabham, Emmanuel Manu

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Management Procurement and Law · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsnot available
FundersTrent UniversityNottingham Trent University
KeywordsSupply chainProduct (mathematics)Systems thinkingAdversarial systemKnowledge managementSupply chain managementRelation (database)Computer scienceCriticismFocus (optics)Data scienceBusinessProcess managementMarketingPolitical scienceArtificial intelligenceDatabase

Abstract

fetched live from OpenAlex

The construction industry has received long-standing criticism over its fragmented approach to supply chain management, adversarial relationships and ongoing defects. Platform thinking has been observed in other industries as a phenomenon that offers reinvention from the traditional perspectives on the supply chain. In this study, a literature review of platform thinking is presented. A database search of 656 papers across 15 journals, along with 3 sources from a Google search and 12 sources from a manual review of the reference lists were reviewed in relation to platform thinking in construction. While many variants of platforms exist, the literature review demonstrates a focus on product platforms that has historical precedents. This paper highlights the benefits of platform thinking while linking to the lessons of the past. This also provides a valuable insight for future implications of platform thinking and contributes to the limited literature on platform thinking in the construction industry by linking historical examples with present and potential future investigation.

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 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 score0.356
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.215
Teacher spread0.200 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2021
Admission routes1
Has abstractyes

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