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Record W2901394394 · doi:10.21608/auej.2017.19281

A SURVEY OF PROJECT MANAGEMENT MATURITY FOR CONSTRUCTION CONTRACTORS IN EGYPT: THE CURRENT STATUS

2017· article· en· W2901394394 on OpenAlexaboutno aff
Mohamed Moutawei, Ahmed F. Mohamed, Moheeb Ibrahim, Mohamed Bakry

Bibliographic record

VenueJournal of Al-Azhar University Engineering Sector · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsMaturity (psychological)Capability Maturity ModelDocumentationExcellenceService Integration Maturity ModelVariety (cybernetics)Operational excellenceProcess managementBusinessProject managementProgram managementBest practiceOperations managementMarketingEngineeringComputer scienceEconomicsManagementSystems engineering

Abstract

fetched live from OpenAlex

Project Management is considered now one of the most dynamic and growing professions worldwide. Effective project management not only reduces unnecessary costs of doing business, but also has become as a crucial factor to gain a competitive advantage and determines the success and survive of organizations. In the last decade, there is a global international interest and attention for organizations to evaluate and improve the effectiveness of its project management practices. Given such background, this clarifies the dramatic increase in the attention, research and practices of the project management maturity and the maturity models. Maturity Models has taken on greater significance not only in assessing organization’s current project management capabilities and efficiency, but also as a path for achieving excellence in project management and further performance improvement. The capability maturity model, the first maturity model developed, has achieved a wide success and Organizations implementing this approach experience and report significant benefits and return on investment. Various models have since been developed and proposed, and they are most commonly implemented in developed countries such as USA, UK, Canada, Europe, etc. The excessive variety of maturity models has made the choice between them difficult and need careful attention and consideration in both the model choice and implementation in the business. In Egypt, there is a lack of documentation available on the current status, awareness and utilization of maturity models in the contracting organizations working in the construction sector and this study aims to fill this gap. To achieve this, it was necessary to consult project management experts and professionals to get an understanding of how these organizations view maturity models and project management standards and to establish the most common business practices and so propose the basis of a maturity model for Egyptian construction contractors that best fits the current status. Based on the analysis of the survey conducted, it was concluded that project management tools and methodologies have not yet been utilized effectively in the Egyptian construction contracting organizations and that there is much room for improvement regarding project management practices in these organizations in order for Egypt to develop the contracting construction sector as a pillar for the Egyptian economy.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.079
GPT teacher head0.334
Teacher spread0.255 · 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 designObservational
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

Citations1
Published2017
Admission routes1
Has abstractyes

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