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Record W57094597

Profitability, Growth, and Different Flow Ratio Concepts: Implications for Failing Firms 1

2012· article· en· W57094597 on OpenAlexvenueno aff
Erkki K. Laitinen

Bibliographic record

VenueReview of Economics and Finance · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Reporting and Valuation Research
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexDepreciation (economics)RevenueCash flowEarningsEconomicsEarnings growthFlow (mathematics)Monetary economicsEconometricsMicroeconomicsFinanceMathematics
DOInot available

Abstract

fetched live from OpenAlex

The objective is to develop a mathematical model of the firm to show the relationship between profitability, growth, and financial flow concepts especially under conditions for failing firms. It is assumed that revenue flows are generated by periodic expenditures growing at a steady rate. These revenue flows are described in terms of profitability (internal rate of return), growth, and time lag between invested expenditure and generated revenue flow. Three kinds of financial flow concepts are drawn: revenue-expenditure flow (quick flow), revenue-expense flow (earnings), and cash flow. Earnings are drawn for three depreciation theories: proportional, rate of return, and compound interest depreciation. For each concept, flow ratios are drawn and compared with each other. Theoretical results are illustrated by empirical data from Finnish non-failing and failing firms. JEL Classifications: G G3 32, , M41 1, G G3 33, , C65

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.002
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.066
GPT teacher head0.331
Teacher spread0.265 · 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 designTheoretical or conceptual
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

Citations4
Published2012
Admission routes1
Has abstractyes

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