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Record W3123321552 · doi:10.1506/9728-4yg8-gc3l-fpfa

Determinants of Revenue‐Reporting Practices for Internet Firms*

2002· article· en· W3123321552 on OpenAlexvenueno aff
Robert M. Bowen, Angela K. Davis, Shivaram Rajgopal

Bibliographic record

VenueContemporary Accounting Research · 2002
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBarterRevenueBusinessDiscretionAccountingRevenue recognitionFinanceThe InternetEconomicsAccounting information systemFinancial accounting

Abstract

fetched live from OpenAlex

Abstract The financial press and accounting regulators (e.g., the Securities and Exchange Commission and Financial Accounting Standards Board) have expressed concern about pressures on Internet firms to report high levels of revenue. This study verifies the association between market capitalization and revenue, and examines economic factors that potentially influence Internet company managers' decisions to adopt allegedly aggressive revenue‐recognition policies. Specifically, we examine factors hypothesized to influence the reporting of advertising barter revenue and grossed‐up sales levels. We begin by providing descriptive evidence on the use of barter and grossed‐up revenue across Internet sectors. Although common in some sectors, we find that the use of these accounting policies is not pervasive overall. We limit our empirical analyses to Internet companies that have the opportunity to report grossed‐up or advertising barter revenue. Our cross‐sectional predictions are based on both external and internal incentives to maximize revenues as well as constraints that may limit management's discretion. We predict that the following factors increase the likelihood that a firm will report grossed‐up and/or barter revenue: shorter time before needing additional external financing, more active individual investor interest in the firm's stock, more active pursuit of growth via acquisitions, and greater use of stock options in employee compensation. We also posit that barter transactions might be an inexpensive way for firms to evaluate the viability of future marketing or content alliances with potential partners. Finally, we predict that constraints on management discretion are related to the reputation/quality of the firm's auditor and underwriter and the extent of management ownership. We find that firms with greater cash burn rates and higher levels of activity on Motley Fool message boards are consistently associated with barter and grossed‐up revenue reporting.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
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 head0.136
GPT teacher head0.364
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), 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

Citations88
Published2002
Admission routes1
Has abstractyes

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