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Record W3121234854

The Relationship between an Innovation Orientation and Competitive Strategy

2010· article· en· W3121234854 on OpenAlexaffabout
C. Brooke Dobni

Bibliographic record

VenueSSRN Electronic Journal · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Strategy and Culture
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsBusinessMarket orientationReputationService (business)Competitive advantageContext (archaeology)MarketingEntrepreneurial orientationProduct innovationService-orientationSample (material)Service innovationProduct (mathematics)Knowledge managementIndustrial organizationEntrepreneurshipComputer science
DOInot available

Abstract

fetched live from OpenAlex

The strategy chosen in organizations is related to several factors including the organization's mission, objectives, resources, and its innovation orientation. Using a sample of Canadian organizations, this study examines the relationships between an organization's innovation orientation and the types of competitive strategies they pursue.An innovation orientation describes how innovative an organization is and the results suggest that such an orientation provides a context for the implementation of proactive growth-based strategies. Organizations that possess high innovation orientations engage in value creation strategies such as market segmentation, developing new products/services for new markets, and product or service customisation. Those organizations possessing low innovation orientations generally practice less aggressive and internally focused strategies, de-emphasising such things as customer service, brand reputation, and co-operation based strategies such as joint ventures and alliances.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.249
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), 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

Citations28
Published2010
Admission routes2
Has abstractyes

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