Combining old and new tricks: ambidexterity in aerospace design and integration teams
Bibliographic record
Abstract
Purpose – This paper seeks to examine how aerospace design and integration teams in a highly partnered supply chain are able to leverage extant capabilities and develop new ones when faced with the necessity to adapt to organizational change. Design/methodology/approach – Building on the concept of contextual ambidexterity (Gibson and Birkinshaw), this research uses a combination of qualitative material and objective performance data to investigate the working context of five aerospace design and integration teams, their solutions to crisis-triggering events, and their subsequent schedule adherence. Findings – Team members enacted ambidextrous roles similar to those identified by Birkinshaw and Gibson. These behaviors allowed teams to create ambidextrous solutions when faced with crisis. Teams working in a supportive context were found to produce a greater diversity of ambidextrous solutions, which was found to relate to both overall ambidexterity and schedule adherence performance. Research limitations/implications – Although the results should be interpreted with care, the research answers Raisch and Birkinshaw's call for a more precise definition of organizational ambidexterity as the paper focuses on specific roles played by team members. The findings also point to a potential link between the diversity of ambidextrous behavioral roles and their ability to craft ambidextrous solutions. Practical implications – Teams that can quickly adapt to challenge through ambidextrous solutions are particularly useful in the context of highly partnered supply chains. Managers should therefore actively promote ambidextrous behaviors to ensure that the search for ambidextrous solutions becomes a conscious and deliberate process. Originality/value – This paper substantiates the ambidexterity concept by providing concrete examples drawn from highly partnered aerospace supply chains.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".