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Record W2607730297 · doi:10.3386/w24448

Control Versus Execution: Endogenous Appropriability and Entrepreneurial Strategy

2018· report· en· W2607730297 on OpenAlexaff
Kenny Ching, Joshua S. Gans, Scott Stern

Bibliographic record

VenueNational Bureau of Economic Research · 2018
Typereport
Languageen
FieldDecision Sciences
TopicAuction Theory and Applications
Canadian institutionsKellogg's (Canada)University of TorontoSimon Fraser University
Fundersnot available
KeywordsIndustrial organizationBusinessControl (management)Operations managementCommerceEconomicsManagement

Abstract

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This paper considers the role of Rosenbergian uncertainty (i.e., economic uncertainties that arise after successful invention) in shaping appropriability for start-up innovators. Rather than assuming that the appropriability regime surrounding an innovation is exogenous, we focus on the endogenous choice entrepreneurs face between investing in ensuring control-based appropriability versus investing in the execution and operation of their fledgling businesses. Investment in execution allows entrepreneurs to advance more quickly than competitors, while control requires delays in commercialization. Control and execution are strategic substitutes as they represent alternative paths to earning future rents. Because the size and likelihood of these rents is uncertain, entrepreneurs may be unable to rank these alternative paths in advance, and so their endogenous choice will be grounded in factors such as individual preferences, capabilities, or coherence with their overall entrepreneurial strategy. A subtle consequence is that the appropriability regime ultimately governing an innovation will be the result of the endogenous choices of the entrepreneur rather than more traditional environmental factors. Motivated by notable historical examples such as the invention and commercialization of the telephone, we explore these ideas by considering the choice of appropriability regime among a sample of academic entrepreneurs: within a sample of ventures that could have been developed by either faculty or students (or both), we find that faculty-led ventures are much more closely associated with formal intellectual property, student-led ventures are more rapid in their commercialization activities, and, relative to faculty-led ventures, student-led ventures display a tradeoff between patenting and commercialization speed.

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)0.023
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
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 score0.971
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.011
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.737
GPT teacher head0.598
Teacher spread0.140 · 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.

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

Citations11
Published2018
Admission routes1
Has abstractyes

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