Strategic intelligence as a resilience capability of global supply chains: Proposal of a conceptual framework based on a systematic literature review
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
Purpose This study aims to develop an integrative framework for strategic intelligence (SI) tailored to guide companies navigating systemic disruptions within global supply chains, identifying key determinants for its effective deployment. Current literature on management systems addresses SI components individually, hindering a precise definition and implementation strategy. This systematic review aims to fill these gaps by establishing a conceptual model of SI capability, emphasizing the interdependence of its dimensions. Design/methodology/approach Following the Joanna Briggs Institute (JBI) mixed-method analysis approach and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, this systematic review synthesizes empirical studies, conceptual papers, mathematical models and literature reviews on SI capability dimensions. It adopts a flexible approach to explore SI within supply chain resilience during systemic crises. Findings The study enhances and broadens the field of dynamic capabilities (DCs) by advancing knowledge on SI as a dynamic capability inducing resilience within supply chains facing systemic risks. Additionally, it synthesizes and offers perspective on a rapidly expanding body of literature from the past three years, identifying emerging trends and gaps. Research limitations/implications This research focused on three capacities: Supply Chain Visibility (SCV), Environmental Detection (ED) and Timely Seizing and Decision-Making (TSDM). While other dynamic capabilities may enhance SC resilience (SCR), this study emphasized the analytical and decision-making dimensions critical for improving SCR. Originality/value This systematic literature review introduces a novel conceptual framework, providing a foundation for empirical investigations. By offering an integrated theoretical perspective, the study proposes actionable research propositions and insights into SI’s strategic role in crisis management within supply chains.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it