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Record W4411604486 · doi:10.2308/jmar-2023-003

Accounting Transparency and Foreign Market Entry Mode Choices

2025· article· en· W4411604486 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Management Accounting Research · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting Theory and Financial Reporting
Canadian institutionsTrent University
Fundersnot available
KeywordsTransparency (behavior)AccountingBusinessMode (computer interface)Industrial organizationComputer science

Abstract

fetched live from OpenAlex

ABSTRACT This study documents that U.S. firms are more likely to form joint ventures with local firms than simply acquiring them when entering foreign countries characterized by lower accounting transparency. Cross-sectional analyses further show that our finding is more pronounced for investments made in countries with other information barriers to U.S. investors, such as greater differences in accounting standards and fewer local firms cross-listed on U.S. stock exchanges, and in countries with weaker protections for outside investors. Using the staggered mandatory adoption of International Financial Reporting Standards (IFRS) as a quasi-experiment that exogenously improves country-level accounting transparency, we find that U.S. firms reduce joint venture investments to a greater extent in IFRS-adopting countries than in nonadopting countries. Finally, we show that the market reacts more favorably to joint ventures than to acquisitions when cross-border investments take place in countries with lower accounting transparency. Data Availability: Data are available from the sources cited in the text. JEL Classifications: D23; F23; G30; G32; G34; M41.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0020.004
Open science0.0010.001
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 head0.027
GPT teacher head0.323
Teacher spread0.296 · 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