Linking Supply Chain Disruption Orientation to Supply Chain Resilience and Market Performance with the Stimulus–Organism–Response Model
Bibliographic record
Abstract
Since 2020, supply chain disruptions have emerged as an ever-present challenge. This research provides a glimpse into the organizational structures that develop supply chain resilience and market performance amid continuous supply chain disruptions. Utilizing psychosomatic variables and empirical modeling, a model was constructed through a review of extant literature and tested with PLS-SEM analysis. Uniquely, this research model is framed with the stimulus–organism–response model; thus, placing a firm within the context of a tumultuous environment where stimuli elicit responses from an organization that behaves as an organism. Results demonstrate that organizational culture plays a critical role in developing supply chain resilience amid supply chain dynamism. Market performance was also developed but only through supply chain resilience; supply chain disruption orientation alone did not improve market performance. Mediation effects highlight the importance of supply chain disruption orientation, a strategic orientation that cements an organization’s ability to develop supply chain resilience.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".