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Record W2471000913 · doi:10.1177/0266242616654957

Appropriation strategies and open innovation in SMEs

2016· article· en· W2471000913 on OpenAlexaff
Mark Freel, Paul Robson

Bibliographic record

VenueInternational Small Business Journal Researching Entrepreneurship · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAppropriationOpenness to experienceOpen innovationBusinessIntellectual propertyIndustrial organizationMarketingPolitical sciencePsychology

Abstract

fetched live from OpenAlex

Drawing upon data from the fifth UK Innovation Survey, this article sheds light on how management choices on the nature of appropriation relate to management choices on the degree of openness within small and medium-sized enterprises (SMEs). To this end, our findings indicate a threshold effect of both informal and formal appropriation mechanisms on the likelihood of engaging in both coupled and inbound open innovation. That is, an emphasis on appropriation appears to be important in shifting firms from a closed to an open strategy. There is, however, little evidence that either approach to appropriation increases the extent of open innovation. In this, only informal intellectual property (IP) protection mechanisms associate with an increasing extent of inbound open 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)0.002
metaresearch head score (Gemma)0.002
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 score0.448
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.081
GPT teacher head0.319
Teacher spread0.238 · 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 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

Citations111
Published2016
Admission routes1
Has abstractyes

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