Intangible project management assets as determinants of competitive advantage
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.
Bibliographic record
Abstract
Purpose To explore the role of intangible project management assets in achievement of competitive advantage from the project management process through it being valuable, rare, inimitable, and having organizational support. Design/methodology/approach Data were collected on tangible and intangible project management process assets and competitive characteristics of the project management process using an online survey of North American Project Management Institute™ members. Three key tangible asset factors, one intangible asset factor, and three competitive characteristics were identified using exploratory factor analysis. The relationship between these project management assets and project management process characteristics are examined using multivariate analysis. Findings Intangible project management assets are found to be a source of competitive advantage, directly and through a mediating role in the relationship between tangible project management assets and the competitive characteristics of the project management process. Practical implications This study highlights the importance of developing intangible project management assets, in addition to investment in tangible project management assets, to achieve competitive advantage from the process. Research limitations/implications This was an exploratory study. The authors expect to further develop the instrument, refine the model and constructs, and test it with a larger sample. Originality/value Few papers have used the Resource Based View lens and applied it to project management. 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.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it