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Record W2511315264 · doi:10.1080/10438599.2016.1203084

Does organizational innovation moderate technical innovation directly or indirectly?

2016· article· en· W2511315264 on OpenAlexaff
Brian Paul Cozzarin, Weonseek Kim, Bonwoo Koo

Bibliographic record

VenueEconomics of Innovation and New Technology · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsEndogeneityContext (archaeology)ProductivityDivergence (linguistics)Organizational performanceIndustrial organizationControl (management)Organizational learningEconomicsStructural equation modelingKnowledge managementBusinessEconometricsMarketingComputer scienceManagement

Abstract

fetched live from OpenAlex

We find a divergence in the literature regarding the treatment of how organizational innovation affects innovation and performance. One point of view suggests that organizational innovation impacts performance only, while the other suggests that it impacts technical innovation and firm performance. We use the framework of Crepon-Duguet-Mairesse (CDM) to control for endogeneity; we also use two different measures for organizational innovation. Our contributions to the literature are: the CDM framework in this context is novel; prior research either did not/could not control for endogeneity whereas the CDM framework mitigates this. To discriminate between the direct and indirect approach, we implemented AIC and BIC tests. We find that for the innovation equations in all cases and regardless of which organizational innovation variable is used the direct model is preferable. In contrast, for the productivity equations, we find that in all cases the indirect model is preferable. Thus we do not have a definitive statistical test for which model is superior. Yet, it is our contention that organizational innovation is a new routine within the firm that should impact technical innovation. Furthermore, organizational design theories deduce that organizational innovation should impact technical innovation-implying that the direct model is indeed preferable.

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.008
Science and technology studies0.0000.000
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 head0.028
GPT teacher head0.230
Teacher spread0.202 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations19
Published2016
Admission routes1
Has abstractyes

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