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Record W2971737747 · doi:10.5430/ijfr.v10n6p133

Efficiency of Working Capital Management and Firm Value: Evidence From Chinese Listed Firms

2019· article· en· W2971737747 on OpenAlexvenueno aff
Ratnam Vijayakumaran

Bibliographic record

VenueInternational Journal of Financial Research · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWorking Capital and Financial Performance
Canadian institutionsnot available
Fundersnot available
KeywordsWorking capitalAccounts receivableProfitability indexPanel dataEnterprise valueValue (mathematics)Cash conversion cycleBusinessMarket value addedTobin's qInvestment (military)EconomicsFinanceCash flowMonetary economicsEconometricsOperating cash flow

Abstract

fetched live from OpenAlex

This paper examines the relationship between the efficiency of working capital management (WCM) and the firm value, focusing on a large panel of Chinese listed companies. WCM which involves a trade-off between profitability and risk is a very important element of the financial management of the firm. The net trade cycle (NTC) and its components are used to measure efficiency of WCM, while the firm value is measured by the Tobin’s Q ratio. The study makes use of the panel data methodology to estimate the regression models. This study reports that the net trade cycle is negatively associated with firm value. More specially, the study finds that firm value is adversely affected by the number of days accounts receivable and inventories, indicating that working capital provides a real opportunity for financial executives to release cash and improve firms’ value. The findings of this study are consistent with the idea that managers can enhance firm value by efficiently managing the investment in working capital.

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 score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
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 head0.042
GPT teacher head0.310
Teacher spread0.269 · 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

Citations30
Published2019
Admission routes1
Has abstractyes

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