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Record W2887527287 · doi:10.1111/1911-3846.12446

Public Disclosures in the Presence of Suppliers and Competitors

2018· article· en· W2887527287 on OpenAlexvenueno aff
Anil Arya, Brian Mittendorf, Dae‐Hee Yoon

Bibliographic record

VenueContemporary Accounting Research · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsnot available
Fundersnot available
KeywordsCompetitor analysisBusinessPremiseIndustrial organizationProduct (mathematics)Market powerMarketingMonopolyMicroeconomicsEconomics

Abstract

fetched live from OpenAlex

ABSTRACT Firms’ reluctance at times to publicly disclose financial information is often attributed to concern that the information may be used against them by self‐interested outside parties. These outside parties may interact with the firm in the horizontal realm (e.g., retail competitors) or in the vertical arena (e.g., wholesale suppliers). This article is built on the premise that fully understanding the strategic consequences of disclosure requires joint consideration of horizontal and vertical relationships. When both rivals and suppliers are accounted for, we demonstrate that (i) lower intra‐industry correlation in product demand favors disclosure, with the precise correlation‐cutoff dependent on the firm's use of input suppliers; and (ii) the more a firm relies on input suppliers with pricing power, the less attractive is disclosure.

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)0.006
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.677
Threshold uncertainty score0.588

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.000
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 head0.123
GPT teacher head0.316
Teacher spread0.193 · 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 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

Citations27
Published2018
Admission routes1
Has abstractyes

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