MétaCan
Menu
Back to cohort
Record W4391734241 · doi:10.53935/jomw.v2021i1.135

Integrated Knowledge Management, Organisational Learning and Innovation Model for the Construction Industry

2022· article· en· W4391734241 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.

Bibliographic record

VenueJournal of Management World · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsGeorge Brown College
Fundersnot available
KeywordsKnowledge managementBusinessLearning organizationConstruction industryProcess managementEngineering managementEngineeringComputer scienceConstruction engineering

Abstract

fetched live from OpenAlex

Knowledge Management (KM) is an important part of the construction industry. Knowledge management principles are a set of principles that have been put forward by various researchers to elicit their conceptualisation of knowledge management. However, most of the existing knowledge management models do not take into account the social and learning processes within the organisation. This paper proposes an integrated knowledge management, organisational learning and innovation model that, if not completely, but still provides a fair deal of insight into the organisational processes when knowledge management is implemented. The model illustrates how knowledge management initiatives successfully set the organisation on the path of learning and success by bridging a gap between the scientific and social paradigms, and ensure the consistent flow of knowledge. This model is also an attempt to illustrate the current state of the management of innovation in the industry and depicts how construction industry could benefit from the knowledge management in this time. The main focus is made on how appropriate organizational learning and innovation can contribute to improving, developing and improving professional expertise in the construction sector.

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)0.004
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.729
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.106
GPT teacher head0.369
Teacher spread0.263 · 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