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Record W1982213224 · doi:10.1002/smj.387

R&D, organization structure, and the development of corporate technological knowledge

2004· article· en· W1982213224 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

VenueStrategic Management Journal · 2004
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTransaction costControl (management)Industrial organizationDatabase transactionBusinessKnowledge managementEmpirical researchRange (aeronautics)Computer scienceEconomicsManagementMathematicsEngineeringDatabaseFinance

Abstract

fetched live from OpenAlex

Abstract We explore the link between a firm's organization of research—specifically, its choice to operate a centralized or decentralized R&D structure—and the type of innovation it produces. We propose that by reducing the internal transaction costs associated with R&D coordination across units, centralized R&D will generate innovations that have a larger and broader impact on subsequent technological evolution than will decentralized research. We also propose that, by facilitating more distant (‘capabilities‐broadening’) search, centralized R&D will generate innovations that draw on a wider range of technologies. Our empirical results provide support for our predictions concerning impact, and mixed results for our predictions concerning breadth of search. We also find that control over research budgets complements direct authority relations in contributing to innovative impact. We propose several extensions of this research. Copyright © 2004 John Wiley & Sons, Ltd.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.747
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.043
GPT teacher head0.237
Teacher spread0.194 · 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