From hierarchical to matrix structure: tensions in negotiating shared leadership configurations
Bibliographic record
Abstract
Purpose Despite much attention being devoted to shared leadership, the negotiation of such arrangements remains underexplored. In parallel, the revival of interest in matrix structures reveals their challenges but neglects the dynamics of shared leadership. In this case study, the author analyzes the tensions experienced by senior managers of a healthcare organization transitioning from a hierarchical to matrix structure as they negotiate their leadership roles in this new arrangement. Design/methodology/approach The author interviewed 16 senior managers, observed their meetings and analyzed documents. These data were combined with secondary data including previous interviews and observations of this top leadership team. The author then conducted an inductive data analysis. Findings The author's analysis reveals that the tensions experienced by senior managers as they negotiate their roles reflect the co-existence of leadership surpluses (too much leadership) and deficits (too little leadership) in matrix organizations. The author argues that surpluses and deficits are not mutually exclusive but are interrelated and shows how leadership surpluses can create leadership deficits. Practical implications The author’s findings suggest that in contexts of leader abundance, actors should explore leadership voids. Particular attention should be paid to incidents of intrusion and exclusion, moments of transition and intense role negotiation, as those contexts are particularly conducive to leadership deficits. Originality/value While previous work on matrix structures focuses on leadership surpluses, the author discusses leadership deficits. The author explores how more leaders do not necessarily mean more leadership, but instead how more leaders may result in leadership voids.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.027 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| 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".