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Record W2139231821 · doi:10.1177/1476127008096363

When is the whole bigger than the sum of its parts? Bundling knowledge stocks for innovative success

2008· article· en· W2139231821 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 Organization · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Capital and Performance Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsStock (firearms)Pairwise comparisonBusinessHuman capitalInterdependenceIntellectual capitalKnowledge flowIndustrial organizationMarketingKnowledge managementEconomicsComputer scienceFinanceEngineeringMarket economy

Abstract

fetched live from OpenAlex

As firms engage in building different R&D capabilities, they confront a crucial question: what configuration of knowledge stocks is most likely to increase innovative success? This article argues that the impact of one knowledge stock may depend not just on its level but also on the level of other stocks; furthermore, the interdependencies of firms' existing knowledge stocks might explain performance differences.The authors measure the effects of three pairwise combinations of knowledge stocks on firm innovative success, and find, using an event-history analysis of 843 dedicated biotechnology firms during 1973—99, that one pair is complementary (i.e. intellectual and collaborative capital) and two pairs are substitutive (i.e. human and intellectual and human and collaborative capital).Viewing knowledge complementarities through such a lens gives rise to systems effects and explains when the whole is bigger (or smaller) than the sum of its parts.

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)0.000
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 score0.291
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.245
Teacher spread0.206 · 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