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Record W1561634609

How does profitability get affected by working capital management in food and beverages industry

2013· preprint· en· W1561634609 on OpenAlexaboutno aff
Priya Darshini Pun Thapa

Bibliographic record

VenueMunich Personal RePEc Archive (Ludwig Maximilian University of Munich) · 2013
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicWorking Capital and Financial Performance
Canadian institutionsnot available
Fundersnot available
KeywordsWorking capitalProfitability indexIndex (typography)Cash conversion cycleLeverage (statistics)BusinessFree cash flowEconomicsCash flowFinanceOperating cash flowMathematicsStatistics
DOInot available

Abstract

fetched live from OpenAlex

This study examines the working capital management of the Food and Beverage Corporations from the U.S.A. and Canada during the 10 years study period from year 2000 to 2009. Firstly, unlike previous studies which advocate a linear relationship between the working capital management and profitability, it investigates the existence of a possible non-linear relationship. Secondly, the efficiency of working capital management was checked using performance index, utilization index and efficiency index rather than using the conventional turnover ratios. Thirdly, the distribution of working capital measure i.e. cash conversion cycle and factors affecting viz. leverage, growth, size, age, cash flow and fixed assets to total assets ratio has been studied. The results suggest the existence of concave relationship between the working capital management and profitability. The findings also revealed that the corporations were efficient during the study period.

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)0.003
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 score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.173
Teacher spread0.163 · 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

Citations13
Published2013
Admission routes1
Has abstractyes

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