From a rugged to a smooth supply chain performance landscape: a complementarity perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We draw on complementarity and performance landscape perspectives to reason why and how supply chains should shift from a rugged to a smooth performance landscape. We analysed the organisation of supply chain-oriented firms by conceptualising them as a set of interdependent elements whose complementarity interaction generates desirable performance outcomes. We collected perceptual data from 139 firms. After establishing the psychometric properties of the measures, we employed two econometric methods that enabled us to examine the complementary interaction using performance differences among five SCM practices. Overall, we find empirical evidence for complementarity among the SCM practices. We also find interesting results from the two econometric approaches allowing us to articulate the distinction between practice contextuality and interaction contextuality. Our study offers empirical evidence for supply chain managers to find a promising position in the rugged supply chain performance landscape. In addition, we offer noteworthy managerial insights on managing the supply chain towards a smoother supply chain performance landscape.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it