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Record W3139440659 · doi:10.51325/ijbeg.v4i2.64

<b>The Importance of Strategic Agility to Business Survival During Corona Crisis and Beyond</b><b></b>

2021· article· en· W3139440659 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuroMid Journal of Business and Tech-innovation (EJBTI) · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCollaboration in agile enterprises
Canadian institutionsConcordia University
Fundersnot available
KeywordsCompetitor analysisAgile software developmentStrategic managementBusinessCompetitive advantageSustainabilityExcellenceBusiness environmentIndustrial organizationProcess managementMarketingEconomicsManagementPolitical scienceBusiness administration

Abstract

fetched live from OpenAlex

Strategic Agility is seen by many researchers and analysts as an innovative newly developed management paradigm adopted by contemporary organizations to achieve distinction and outperform competitors under conditions of environmental instability and uncertainty. This article is an attempt to introduce the concept of Strategic Agility and to demonstrate its basic characteristics and the importance of adopting it by various organizations to achieve excellence and sustainability. In a competitive environment, characterized by acute turbulence and continual shocks, as in the current environment of COVID-19, strategic agility offers a viable means to harness non-linear scientific and technological breakthroughs with a view to profiting from both the dislocation in the consumer sentiment and behavior and the breakdown in supply chains. Moreover, the article highlights the interaction between strategic agility and firm performance and emphasizes the need to create agile organizations that will thrive in a volatile and uncertain world.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.805
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.008
Science and technology studies0.0010.000
Scholarly communication0.0010.002
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 head0.024
GPT teacher head0.240
Teacher spread0.216 · 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