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Record W4255709917 · doi:10.3386/w23138

Endogenous Appropriability

2017· report· en· W4255709917 on OpenAlexaff
Joshua S. Gans, Scott Stern

Bibliographic record

VenueNational Bureau of Economic Research · 2017
Typereport
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Policies and Impacts
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEndogenyMedicineInternal medicine

Abstract

fetched live from OpenAlex

The appropriability of innovation depends not only on the instruments available to an innovator to protect private returns, but how those instruments interact with each other as part of the firm's entrepreneurial strategy. We consider the interplay between two appropriability mechanisms available to start-up innovators: control, whereby the innovator earns rents from their establishment of formal intellectual property rights, versus execution, whereby innovators earn returns through a first-mover advantage that yields dynamic benefits allowing the firm to "get ahead, stay ahead." While most prior work has taken these instruments to be independent, we establish that these two alternative appropriability instruments are substitutes on the margin. For example, if the learning advantage from execution is sufficiently high, an entrepreneur might choose not to invest in a patent, even if intellectual property protection is costless. Moreover, the endogenous choice between control and execution is interdependent with other strategic choices of start-up innovators, such as the choice to pursue a narrow or broad customer segment, or whether to commercialize a "minimal viable product" version of their innovation versus delay commercialization until a product is available with a higher level of technical functionality and reliability.

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)0.013
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.665
GPT teacher head0.505
Teacher spread0.160 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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