The influence of organizational culture on project portfolio management practices within the healthcare sector
Bibliographic record
Abstract
This study examines the impact of organizational culture on the effectiveness of Project Portfolio Management (PPM) practices. Organizational culture influences employee behavior and their way of working by providing a conducive work environment. Thus, managers are able to delegate better while ensuring a balanced workload, collaborative team efforts, and prudent resource allocation to achieve desired project portfolio deliverables. By shaping practices and values, a supportive culture enables efficient task performance, effective delegation, teamwork, and resource allocation toward project goals. Conducted with 35 individuals in a healthcare organization’s data and digital unit in New Zealand, the study used convenience sampling and email surveys. Regression analysis was performed in IBM SPSS Statistics to test the research hypothesis. Findings suggest that supportive organizational culture significantly enhances PPM execution and informs policy-making for improved PPM practices. This study facilitates directors, strategists, and managers in taking steps to form a culture that ensures effective execution of PPM practices to achieve better results. Future research could explore this topic with larger samples and alternative methodologies to deepen insights into culture’s role in PPM effectiveness.
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 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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".