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Record W4387131254 · doi:10.5539/ibr.v16n10p10

Risk Management Culture, Structure, and Process – Theoretical Insights and Empirical Evidence

2023· article· en· W4387131254 on OpenAlexvenueno aff
Minela Nuhić-Mešković, Admir Mešković

Bibliographic record

VenueInternational Business Research · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRisk Management in Financial Firms
Canadian institutionsnot available
Fundersnot available
KeywordsRisk managementBusinessLikert scaleStock (firearms)Empirical researchMarketingOperations managementRisk analysis (engineering)EconomicsFinanceEngineeringPsychology

Abstract

fetched live from OpenAlex

In the contemporary business environment, companies face a wide range of risks that necessitate effective risk management strategies. Risk management can be approached through either a traditional or integrated concept, which hinges on a company's ability to avoid, reduce, and transform risks into opportunities. This research aims to investigate the risk management practices employed by joint-stock companies in Bosnia and Herzegovina. The study will focus on evaluating the risk management culture, structure, and processes implemented by these companies. The research was conducted using a questionnaire distributed to a sample of 141 companies listed on two stock exchanges in B&H. The survey included 31 identified risk management components related to culture, processes, and organizational structure. To enhance accuracy, the survey responses were improved using a Likert scale, replacing the previous "Yes – No" dummy approach. Before administering the survey, all components were validated by a group of experts. The findings revealed that companies in Bosnia and Herzegovina (B&H) have inadequately developed components of an integrated risk management concept. The research results suggest that B&H companies primarily rely on traditional risk management approaches, failing to keep up with the global trend of implementing risk management standards. This situation may lead to adverse implications for BH companies and its economy.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
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 head0.075
GPT teacher head0.381
Teacher spread0.305 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations3
Published2023
Admission routes1
Has abstractyes

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