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Record W2950195020 · doi:10.1108/ijmpb-12-2018-0284

Mediated effect of project management asset characteristics on firm performance

2019· article· en· W2950195020 on OpenAlexaff
Kam Jugdev, Gita Mathur, Tak Fung

Bibliographic record

VenueInternational Journal of Managing Projects in Business · 2019
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversity of CalgaryAthabasca University
Fundersnot available
KeywordsProject managementBusinessProject management triangleOriginalityCompetitive advantageSample (material)Asset (computer security)OPM3Resource-based viewProject portfolio managementKnowledge managementProcess managementMarketingComputer scienceEconomicsManagementCreativity

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to study how project-level performance mediates the effect of project management assets on firm-level performance by examining the direct and mediated relationships between the project management process characteristics: valuable, rare, inimitable and organizationally supported on project-level and firm-level performance outcomes. Design/methodology/approach This paper analyzes data from an online survey completed by 198 North American Project Management Institute® members. Linear regression and Sobel Tests are used to examine the relationships between nine factors extracted from an exploratory factor analysis that comprise project management asset characteristics, one factor that comprises project-level performance outcomes, and one factor that comprises firm-level performance outcomes. Findings Not only does project-level performance positively and significantly affect firm-level performance, but project-level performance also significantly mediates the effect of project management asset characteristics (for all nine factors) on firm performance. Research limitations/implications Limitations of this study include sample size and self-report bias, calling for a larger sample in ongoing research. Practical implications This study contributes to the stream of literature on project management assets as sources of competitive advantage and makes the case for sustained organizational investments in the project management process. Originality/value This paper contributes to the limited, but increasing interest in applying the resource-based view of the firm to project management capabilities 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.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.306
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.037
GPT teacher head0.349
Teacher spread0.312 · 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 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

Citations14
Published2019
Admission routes1
Has abstractyes

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