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Record W2164770215 · doi:10.5539/ibr.v5n12p202

Firm Governance and Organizational Resiliency in a Crisis Context: A Case Study of a Small Research-based Venture Enterprise

2012· article· en· W2164770215 on OpenAlexaffvenue
Alidou Ouédraogo, Michel Boyer

Bibliographic record

VenueInternational Business Research · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRisk Management in Financial Firms
Canadian institutionsUniversité de SherbrookeUniversité de Moncton
Fundersnot available
KeywordsCorporate governanceCrisis managementContext (archaeology)BusinessSetbackResilience (materials science)Face (sociological concept)Financial crisisProcess (computing)Psychological resilienceAccountingManagementEconomicsFinancePolitical scienceSociologyPsychology

Abstract

fetched live from OpenAlex

Very small companies that are derived from research projects face numerous crises throughout their lifetimes. These crises are presented in the literature as negative setback situations for the growth of these companies. However, some recent studies emphasize the role that a crisis can play as an agent of change by undergoing a thorough analysis of what transpired and proposing new avenues to avoid repeating such errors. This new approach to crisis management suggests that the crisis period be considered as an outstanding opportunity to learn, along with organizational resilience. Our study is part of this new approach towards crisis management and seeks to study the impact of crisis management on the resiliency of very small research-based company. The results show that a process of learning and resiliency transpires during the post-crisis period and represents three types of governance: financial, managerial and strategic.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.065
GPT teacher head0.348
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations17
Published2012
Admission routes2
Has abstractyes

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