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Record W3042473511 · doi:10.1080/00472778.2020.1775466

How do institutional innovation systems affect open innovation?

2020· article· en· W3042473511 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

VenueJournal of Small Business Management · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOpenness to experienceOpen innovationContext (archaeology)Emerging marketsBusinessIndustrial organizationAffect (linguistics)Panel dataEconomicsEconomic systemMarketingMacroeconomics

Abstract

fetched live from OpenAlex

<p>It is well known that innovation benefits firms and that openness may enhance these benefits. Yet few studies consider how a firm’s institutional context and different economic systems moderate openness and innovation outcomes in new ventures, which arguably are most exposed to institutional constraints. Comparing data from a liberal (Australia) and central market economy (China), and using search breadth as a measure of openness, we empirically tested the influence of external firm pressures on the relationship between openness and innovation outcomes in new ventures. Our results show that the well-established positive relationship between openness and innovation is market dependent and that, in emerging economies, it can be negative. Our findings demonstrate the importance of institutions and national economic systems in explaining open innovation in different contexts–a point not yet addressed in the open innovation literature.</p>

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 categoriesScholarly communication
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 score0.946
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0000.000
Scholarly communication0.0030.004
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 head0.068
GPT teacher head0.251
Teacher spread0.183 · 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