Business Continuity Planning and Supply Chain Management
Bibliographic record
Abstract
Business Continuity Planning (BCP) has evolved significantly and gained acceptance since the events of September 11, 2001. It is defined in the literature as an integrated set of formalized procedures used by an organization to recover from events that disrupt business operations. These procedures call for vertical and horizontal integration of all functional groups within the organization as well as with all external groups that interact with it. Information technology (IT) plays a central role in that integration. This paper reviews and discusses the current state of business continuity planning as it applies to the supply chain and points to the efforts undertaken by business and government to mitigate the risks of supply chain disruptions. The organization’s supply chain continuity plan must extend to all supply chain participants, as illustrated by real-life examples. The most advanced business continuity planning requires equally advanced IT tools to increase visibility both inside and outside the organization and to automate supply chain planning and execution. The paper therefore extends a framework for supply chain continuity to include an IT component that runs supply operations and supports a plan for their continuity.
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.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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 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".