Project management resources and outcomes: a confirmatory factor analysis
Bibliographic record
Abstract
Purpose The purpose of this paper is to draw on the resource-based view of the firm from strategic management and apply it to a study of competitive advantage in the project management context. Confirmatory factor analysis (CFA) is used to examine the factors that constitute strategic characteristics of project management resources and outcomes of the project management process. Design/methodology/approach This study gathered data from 437 North American project management professionals using an existing survey tool from prior research involving a smaller sample. Findings The final model derived from CFA demonstrated construct validity, meaning acceptable convergent and discriminant validity. It showed only minor differences from a prior exploratory factor analysis (EFA). The final model consisted of two factors representing valuable project management characteristics, one factor representing rare project management characteristics, one factor representing inimitable project management characteristics, three factors representing organizational support for project management assets, one factor representing project-level performance and one factor representing firm-level performance. Research limitations/implications Limitations of the study include self-report bias and the use of a panel for data collection. Practical implications This study draws managerial attention to project management characteristics that constitute a source of competitive advantage. Originality/value The study validates a survey tool from previous research, reflects few deviations from factor structure of the prior EFA, and sets the stage for future research to elaborate on the conceptual model. It extends understanding of the characteristics of project management assets that lead to a firm’s competitive advantage.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".