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Record W2233226608

Strategic Risk, Risk Perception and Risk Behaviour: Meta-Analysis

2011· article· en· W2233226608 on OpenAlexaff
Tom Cooper, Alex Faseruk

Bibliographic record

VenueSSRN Electronic Journal · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRisk Management in Financial Firms
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCLARITYRisk perceptionExtant taxonPerceptionMeta-analysisRisk managementFinancial risk managementRisk analysis (engineering)BusinessPsychologyFinanceMedicine
DOInot available

Abstract

fetched live from OpenAlex

We examine the effects of strategic risk perception on behaviour through the meta-analysis of five studies. The extant literature suggests that if risk perception is high it can decrease risk-taking behaviour. The direction of the impact is generally accepted in the business and research community, however, the strength of that direction is not very clear. Using meta-analysis, five strategic risk studies are synthesized to gain clarity on this issue. The results reveal that high-risk perceptions exhibit a negative relationship with risk-taking behaviour. This effect should be understood and closely monitored when formally evaluating strategic risk in business decisions, projects and management.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.233
Teacher spread0.189 · 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

Citations8
Published2011
Admission routes1
Has abstractyes

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