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Business Continuity Planning and Supply Chain Management

2007· article· en· W388526994 on OpenAlexaff
Morad Benyoucef, Samer Forzley

Bibliographic record

VenueSupply Chain Forum an International Journal · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain Resilience and Risk Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSupply chainBusiness continuityProcess managementSupply chain managementSupply chain risk managementPlan (archaeology)BusinessBusiness system planningService managementSales and operations planningBusiness processComputer scienceOperations managementMarketingEngineeringComputer security

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.265
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2007
Admission routes1
Has abstractyes

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