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Record W2073834354 · doi:10.1108/mrr-05-2013-0112

The relationship between project management process characteristics and performance outcomes

2014· article· en· W2073834354 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

VenueManagement Research Review · 2014
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversity of CalgaryAthabasca University
Fundersnot available
KeywordsBusinessProject managementOPM3Project management triangleCompetitive advantageAsset (computer security)Knowledge managementSample (material)Process managementProcess (computing)MarketingComputer scienceEconomicsManagement

Abstract

fetched live from OpenAlex

Purpose – The aim of this paper is to examine the links between project management process characteristics and project-level and firm-level performance outcomes to test the hypotheses that project management assets being valuable, rare, inimitable and having organizational support leads to competitive advantage. Design/methodology/approach – This paper analyzes data from responses to an online survey by 198 North American Project Management Institute® members. Regression analysis is used to examine the relationship between six factors extracted from an exploratory factor analysis that comprise the three project management asset characteristics – valuable, rare and inimitable, three factors that comprise organizational support for the project management process, and two factors that comprise project management performance outcomes – project-level and firm-level performance. Findings – Organizational support for the project management process, specifically project management integration, was found to significantly contribute to both project-level and firm-level performance. Of the asset factors examined, valuable project management knowledge was found to contribute to project-level and firm-level performance, though information technology (IT) tools did not. Inimitable proprietary tangible assets were found to contribute to both project-level and firm-level performance, and inimitable embedded intangible assets were also found to contribute to firm-level performance. Rare knowledge sharing tools and techniques were found to negatively contribute to project-level performance. Research limitations/implications – Limitations of this study include sample size, response rate and self-report bias, calling for a larger sample in ongoing research. Practical implications – This study draws managerial attention to project management assets as sources of competitive advantage, highlighting the need to have organizational support for the project management process through organizational integration, and emphasizing the importance of valuable project management knowledge-based assets and inimitable project management assets that are proprietary and tangible as well as those that are embedded and intangible. Originality/value – Few papers have applied the resource-based view of the firm to examine project management capabilities as a source of competitive advantage. This paper contributes to the literature on the resource-based view of the firm and to an improved understanding of project management as a source of competitive advantage.

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)0.023
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.518
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0020.001
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 head0.412
GPT teacher head0.512
Teacher spread0.100 · 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