Exploring the supply chain ambidexterity: a multilevel micro-foundational perspective
Bibliographic record
Abstract
Purpose This study aims to introduce a multilevel micro-foundational perspective on supply chain (SC) ambidexterity, grounded in organizational learning and adaptation research. It investigates the interplay of contextual factors, strategic orientation and a bundle of supply chain management practices to foster ambidextrous performance. Design/methodology/approach Leveraging a blend of perceptual and objective data and measures, this study explores the intricacies of macro and micro factors at multiple levels, offering empirical support for the research framework. The interrelationships among these factors are scrutinized through three analytical approaches: selection, interaction and system forms of interdependence analysis. Findings First, the authors offer empirical support for their conceptual model, illustrating that ambidexterity behavior and outcomes in the SC emanate from intricate interactions between macro and micro factors across various levels. Second, the authors present robust empirical evidence endorsing a system/gestalt form of interdependence analysis in capturing SC ambidexterity and performance. This analytical approach effectively captures the complementarity and contradictory interdependence among the opposing poles of efficiency and responsiveness. Originality/value The organizational and SC activity configuration faces numerous paradoxical tensions, such as profitability versus sustainability. This study offers valuable insights into establishing an ambidextrous system capable of navigating and addressing these paradoxical situations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".