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Record W4372239016 · doi:10.2308/jfr-2021-024

Alignment between Compensation-Contracting and Value-Relevance Roles of Revenues

2023· article· en· W4372239016 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 Financial Reporting · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRevenueEarningsValuation (finance)BusinessRevenue recognitionRevenue modelEquity (law)FinanceRevenue assuranceIndustrial organizationAccountingAccounting information system

Abstract

fetched live from OpenAlex

ABSTRACT Revenue is the closest proxy in financial statements for market size and dominance, factors that determine the survival and future profits of modern corporations. Hence, revenue may contain value-relevant information, incremental to information contained in earnings. We find that revenue is used as a performance metric in executive compensation contracts when it provides information on equity valuation beyond the information provided by earnings. We call this occurrence an alignment between revenues’ contracting and the valuation roles. The alignment is higher for firms in newer industries, with investors who focus on revenue targets, with managers who provide revenue guidance, and with analysts who issue revenue forecasts. This alignment seems efficient because revenue is more informative of future profits when it carries higher weight in executive compensation contracts. We conclude that modern corporations increasingly incentivize managers to create new markets and defend existing market shares, in addition to maximizing current profits. JEL Classifications: J3; L2; 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)0.003
metaresearch head score (Gemma)0.065
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 score0.320
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.065
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.021
GPT teacher head0.261
Teacher spread0.241 · 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