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Record W1955961943 · doi:10.5539/ass.v11n23p59

The Effect of Working Capital Strategies on Performance Evaluation Criteria

2015· article· en· W1955961943 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWorking Capital and Financial Performance
Canadian institutionsnot available
Fundersnot available
KeywordsWorking capitalMultivariate statisticsReturn on capital employedEconometricsInvestment (military)Return on assetsReturn on investmentLinear regressionValue (mathematics)Capital (architecture)Regression analysisActuarial scienceBusinessEconomicsFinanceStatisticsHuman capitalMathematicsMicroeconomicsFinancial capitalCapital formation

Abstract

fetched live from OpenAlex

The main aim of the present study is to explore the effect of working capital strategies on performance evaluation criteria. To this end, a number of 658 companies were selected during the period of 2007. For testing research hypotheses, multivariate linear regression statistical technique was used. The results indicate that investment strategies have a significant effect on return on assets and Tobin Q indicator. However, these strategies do not have any significant effect on Market Value Added. Financing strategies also have only a significant effect on Return on Assets.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.947
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.030
GPT teacher head0.276
Teacher spread0.246 · 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