Managing supply chain resilience to pursue business and environmental strategies
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
Abstract Resilience has become a crucial topic in the field of strategic management as it requires companies to design resilient business models to tackle managerial and environmental disruptions of individual firms and supply chains. However, extant research still lacks deep insights into how companies design and manage supply chains according to the resilience principles. With this premise, this paper aims at conducting a state of the art review on supply chain resilience (SCR) considering 125 relevant papers collected from Scopus and Web of Science academic search engine. Starting from the results of the literature review, this study proposes a systemic framework of SCR assessment and contributes to improve the understanding of the impact of different empirically tested constructs on the development of the resilience concept. Further, the findings are summarized in several areas including barriers in developing resilience, metrics to measure the resilience performance, and effective strategies to foster the SCR. Finally, this study outlines promising future research directions for scholars and practitioners.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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