Selecting a priority strategy to enhance the ambidextrous leadership competence of project managers in the telecommunication industries
Bibliographic record
Abstract
The author's previous research has found a strong link between project managers adopting an ambidextrous leadership style and improved project performance in the telecommunications industry. This leadership approach, blending Transactional and Transformational elements, has proven to be impactful. Therefore, it is essential to devise methods for enhancing project managers' adeptness in ambidextrous leadership. This study aims to create a prioritized strategy program to enhance project managers' ambidextrous leadership skills in Indonesia's telecommunications sector. The Fuzzy Analytical Hierarchy Process (Fuzzy AHP) involved 15 experts as respondents, ensuring a comprehensive perspective from academics, consultants, and practitioners. The study's findings underscore the importance of Ambidextrous Leadership skills, followed by managing stakeholder relationships. The key factor is the Project Manager's role, supported by backing from the company or institution. The primary goal is to enhance Project Performance and improve adaptability to change. The recommended strategy prioritizes a Leadership Development Program followed by a Change Management Development Program. This study emphasizes the practical approach to developing project managers' ambidextrous leadership skills to enhance project performance in Indonesia's telecommunications sector. The focus is on the Leadership Development Program, offering actionable insights for industry professionals.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".