Supply chain ambidexterity, business performance and mediating role of lean and agile supply chain strategies
Bibliographic record
Abstract
Ambidexterity is a company's capability to manage operations and strategy simultaneously and effectively, facilitating innovation and adaptation to market changes. Companies must be able to maintain operational efficiency and stability while also innovating and adapting to market dynamics. Ambidexterity enables companies to manage operations and strategy effectively and efficiently while at the same time, facilitating innovation and adaptation to market changes. This leads to an increase in company performance, such as increased revenue, increased market, and increased operating efficiency. It is also necessary that there are several mediating variables, such as effective supply chain collaboration, supply chain management, and innovation capability, which influence the relationship between supply chain ambidexterity and firm performance. This study aims to determine the extent to which ambidexterity can influence supply chain performance and how the role of lean and agile supply chains mediates the relationship between these variables. The research method used in this study is a quantitative approach. The number of samples analyzed in this study was 225. The results of the study concluded that ambidexterity helps companies to overcome pressure to optimize short- and long-term performance, maintain agility and flexibility in adapting to changes in the business environment. Studies on ambidexterity and supply chain performance have shown that ambidexterity can help directly optimize supply chain performance but can also amplify the positive impact of practices such as lean supply chain and agile supply chain. The implications obtained from the findings are that companies are expected to improve operational efficiency and effectiveness and have the ability to adapt to environmental changes and market demands.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".