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Record W1972540814 · doi:10.5539/ibr.v1n4p94

Partnering Project Success Criteria in Malaysia

2009· article· en· W1972540814 on OpenAlexvenueno aff
Hj. Kamaruzaman Jusoff, Hamimah Adnan

Bibliographic record

VenueInternational Business Research · 2009
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsProcurementBusinessRisk managementQuality (philosophy)Integrated project deliveryProcess managementProcess (computing)Project risk managementOperations managementRisk analysis (engineering)Critical success factorProject managementFinanceProject management triangleMarketingEngineeringComputer scienceEconomicsManagement

Abstract

fetched live from OpenAlex

Partnering is used as an approach in the procurement system as it could lead towards improving the performance of the construction industry. Organizations which used the partnering approach in their past construction projects are now reporting favorable results, which include decrease in project costs, delivery of project to program, time quality and buildability. Despite these benefits, there remain are still risks associated with this mode of procurement. Risk management process and partnering are critical to the succession of the construction project. Three (3) case studies were looked into to support this study. The opinions and techniques of risk mitigation were gathered. It was found that the most critical construction partnering risk is the partner’s financial resources, the clients’ problems and economic conditions and financial problems with one of the partner. It is hoped that the risk management programme will help to reduce such risks.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.006
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.285
GPT teacher head0.535
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations6
Published2009
Admission routes1
Has abstractyes

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