MétaCan
Menu
Back to cohort
Record W3009511253 · doi:10.18374/jibe-20-1.2

BOARD COMPOSITION OF INNOVATIVE FIRMS: A PORTRAIT AND GEOGRAPHICAL COMPARISON

2020· article· en· W3009511253 on OpenAlexaff
Ramzi Belkacemi

Bibliographic record

VenueJournal of International Business and Economics · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCorporate governanceBusinessShareholderComposition (language)Relevance (law)AccountingSample (material)Focus (optics)MarketingFinancePolitical science

Abstract

fetched live from OpenAlex

The board of directors is the highest internal governance body and is not only in charge of aligning the interests of shareholders and managers, but also of shaping the strategy of its organization. Thus, directors can potentially have an impact on many aspects, including their firm's performance. However, up until now, the empirical evidences on this subject mainly focus on organizational outcomes such as financial performance and rely on specific geographical contexts like the USA. These facts highlight the relevance of the present study to analyse innovation performance and to be based on an international sample. The aim of this research is twofold: documenting the composition of the board of directors of the most innovative companies in the world and making a geographical comparison between them. This approach allowed us to make several observations and recommendations, particularly regarding the profile of the directors, which can be of great use for companies wishing to innovate and enriches both the literature in corporate governance and innovation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.019
GPT teacher head0.217
Teacher spread0.198 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of International Business and EconomicsSame topicCorporate Finance and GovernanceFrench-language works237,207