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Record W1973823380 · doi:10.5539/mas.v3n7p103

Malaysian Practitioner’s Perception on Knowledge Management in Construction Consulting Companies

2009· article· en· W1973823380 on OpenAlexvenueno aff
Ade Asmi, Amran Rasli, Muhd Zaimi Abd Majid, Ismail Abdul Rahman

Bibliographic record

VenueModern Applied Science · 2009
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionBusinessVariety (cybernetics)Knowledge managementPublic relationsMarketingPsychologyComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Construction consulting companies of today are a part of what has been called the knowledge society. The reason behind this name is the increasing importance of intangible assets as the major source of wealth creation in construction industry. As such, Knowledge Management (KM) has become a critical concern for construction consulting companies to improve project performance. The purpose of this paper is to analyse Malaysian practitioner’s perception on KM in the construction consulting companies. The finding of this study was based on an analysis of transcribed data from semi-structured interviews conducted on Malaysian practitioners in the construction consulting companies to identify pattern and themes accordingly. The findings of the study indicate that all participants have expressed the significant contributions of KM to their success as a professional construction consultant in Malaysia. These participants shared a common characteristic of being professional in construction industry such as they agreed that manage database (data record) and filing system is perceived as important and also the professionals must build extensive social and business networks both locally and overseas that were relevant and have impact on their business success. The professionals have a personal desire to learn and they preferred to learn informally from a variety of people that they can access usually through discussion, seminar/conference and media. Learning from personal experience and experiences from others through learn on job and mentoring were a common characteristics among all the professionals and all of them strongly prescribed that such transfer of learning’s will enable one to shortcut learning and improve their knowledge. However, both internal and external environmental factors have equal impact on the transfer of knowledge in construction consulting companies. Internally, personal interest has the biggest impact followed by culture, commitment from management, incentive or reward for the staff and openness or willingness (more on trust) to share and listen. Externally, business factor/competition has the biggest impact on transfer of knowledge in construction consulting companies.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.837
Threshold uncertainty score0.830

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.067
GPT teacher head0.363
Teacher spread0.296 · 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 designOther design
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

Citations8
Published2009
Admission routes1
Has abstractyes

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