Too busy to balance? A longitudinal analysis of board of director busyness and firms’ ambidextrous orientation
Bibliographic record
Abstract
Abstract Studies commonly highlight the informational upside of a board of directors’ connections to its external environment. Through their seats on multiple outside boards, directors are positioned to bring valuable informational resources to complex internal tasks on a focal firm. Crafting an ambidextrous strategic orientation is such a task, requiring great informational resourcing from a board to reconcile contradictions of exploration and exploitation. Yet, we assign an important boundary condition to this expectation by unpacking the idea of “busyness” as an important consideration in a board’s (in)ability to apply their informational resources. We complement Resource Dependence Theory with insights from bounded rationality and bounded reliability, to challenge the “more is better” assumption of the benefits of outside board seats. We develop corresponding hypotheses on the extent to which busyness of different director types (exemplified here via the busyness of non-executives, executives, and women directors) is related to the ambidextrous strategic orientation of a firm. Our results from a robust longitudinal panel analysis of publicly listed UK firms uncover complex patterns and provide evidence that boards with busy non-executives have a negative influence on the ambidextrous strategic orientation of firms, whereas boards with busy executive directors do not seem to exert an influence. We further find that boards with busy women directors show an inverted U-shaped relation with ambidextrous strategic orientation. We discuss implications for theory and practice.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".