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Record W4246012382 · doi:10.1504/ijtm.2017.10004009

Does national culture influence exploratory and exploitative innovation?

2017· article· en· W4246012382 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

VenueInternational Journal of Technology Management · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHofstede's cultural dimensions theoryExploratory researchCulture theorySociologyEmpirical researchKnowledge managementBusinessEpistemologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

This paper combines Hofstede's theory of cultural differences with exploration/exploitation theory in a culture, exploration, exploitation (CEE) model then uses the model to organise existing theory and research on the relationship between national culture and innovation. A literature review found near consensus on the theory about culture and exploratory innovation as captured in the CEE model but mixed empirical support. Future research on culture and innovation should be designed to account for the exploratory/exploitative distinction in both theory and methodology. The dearth of research on exploitative innovation and on how cultural differences are enacted in the operational processes of organisations should be remedied. The CEE model with it is widely agreed upon theoretical propositions drawing upon two highly influential theories provides an improved theoretical platform for ongoing research on culture 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.

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)0.000
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 score0.565
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
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 head0.017
GPT teacher head0.291
Teacher spread0.274 · 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