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Record W2894942650 · doi:10.14288/1.0371611

Measuring strengths, weaknesses, and the value of project management in construction projects : a project management assessment tool

2018· article· en· W2894942650 on OpenAlexaff
Sanjuan Quintero

Bibliographic record

VenueOpen Collections · 2018
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsStrengths and weaknessesProject managementProgram managementEngineering managementProcess managementEngineeringSystems engineering

Abstract

fetched live from OpenAlex

The objective of this research is to develop a project management (PM) assessment tool that incorporates the following characteristics: 1) the unit of study is an individual construction project, it measures the degree to which various PM practices were implemented on a specific project; 2) project outcomes are also assessed, allowing the relationship between PM practices and project outcomes—and thereby the value of PM—to be explored; 3) project context is also assessed, allowing relevant comparisons between different projects and the opportunity for benchmarking and identification of best practices, 4) it is not tied into one particular PM standard, but draws content from a range of several leading PM standards; and 5) it uses an evidence-based approach to rate the relative importance of different PM practices to aggregate each individual PM practice into an overall PM performance indicator. This research implemented a combination of qualitative and quantitative research methods using multiple project cases, interviews, and archival methods. One of the most important contributions was to find a different way to measure the value of PM, which was from the perspective of the actual PM implementations in a project and the respective project outcomes. A second contribution is that the PM assessment tool can be used to benchmark PM best practices in construction organizations, based on the fact that the assessment tool is built on the foundation of the most accepted and used international standards in North America and in the construction industry. A third contribution of this study is that an integrated framework of PM best practices was created. The new framework was built based on the mapping and integration of four international PM standards. Following a process and a methodology, the assessment tool used the critical success factors (CSFs) to weight the survey questions. One final relevant contribution of this study was that the results corroborated the general assumption that PM practices are strongly positively correlated with the outcomes of the projects of cost, time, and client satisfaction, among others.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.761
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
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 head0.081
GPT teacher head0.376
Teacher spread0.295 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2018
Admission routes1
Has abstractyes

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