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Record W3008723265 · doi:10.2308/tar-2017-0082

Do Innovative Firms Communicate More? Evidence from the Relation between Patenting and Management Guidance

2020· article· en· W3008723265 on OpenAlexaff
Sterling Huang, Jeffrey Ng, Tharindra Ranasinghe, Mingyue Zhang

Bibliographic record

VenueThe Accounting Review · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIntuitionVoluntary disclosureBusinessInformation asymmetryPublic disclosureCompetition (biology)Industrial organizationAccountingMarketingFinance

Abstract

fetched live from OpenAlex

ABSTRACT Successful innovations could induce more disclosure if the information asymmetry between the firm and its investors about post-innovation outcomes leads investors to demand more information. However, such innovations also likely entail greater proprietary cost concerns, which deter disclosure. This paper uses patent grants to examine the effect of innovation success on management guidance behavior. We find that more management guidance follows patent grants, suggesting that despite disclosure cost concerns, firms with successful innovations do respond to information demand. This association is stronger after enactment of Regulation Fair Disclosure and for firms with greater institutional investor ownership, further highlighting the role of information demand. The association is weaker for firms with more competition, consistent with proprietary cost concerns having a moderating impact. Overall, our findings suggest that innovation creates demand for more voluntary disclosure, and firms' disclosure decisions following innovation outcomes vary in ways that disclosure theory and economic intuition predict. JEL Classifications: G30; G32; G38; M41; M48. Data Availability: All data are available from the public sources identified in the paper.

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)0.003
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0020.003
Research integrity0.0000.001
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 head0.059
GPT teacher head0.275
Teacher spread0.216 · 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 designObservational
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

Citations91
Published2020
Admission routes1
Has abstractyes

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