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Record W4377107696 · doi:10.5430/ijfr.v14n3p22

Does Working Capital Management Impact How Well a Company Performs? Panel Data Analysis on the Textile Industries of Bangladesh

2023· article· en· W4377107696 on OpenAlexvenueno aff
Manjurul Alam Mazumder

Bibliographic record

VenueInternational Journal of Financial Research · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWorking Capital and Financial Performance
Canadian institutionsnot available
Fundersnot available
KeywordsWorking capitalAccounts receivableAccounts payablePanel dataCash conversion cycleBusinessHausman testCollateralDeferralCapital expenditureFixed effects modelOperations managementFinanceEconomicsCash flowEconometricsOperating cash flow

Abstract

fetched live from OpenAlex

Managing working capital is vital to the expansion and development of manufacturing companies. The performance of Bangladeshi textile industries and the implications of working capital management are the main focus of this study. Working capital is represented by the inventory conversion period, receivable collection cycle, payable deferral cycle, and cash conversion cycle, whereas firm performance is determined by ROA. From 2013 to 2022 ten years panel data were collected from the annual reports of ten listed textile companies of Bangladesh. Panel Least Square (PLS), fixed affect, random effect, and the Hausman test were all executed using the STATA program to determine the influence of independent factors on the dependent factor. The ROA of Bangladesh's textile industries was found to be significantly affected by the Inventory Conversion time, Receivables Collection time, and Cash Conversion Circle, but not by the Payable Deferral time.

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 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)0.003
metaresearch head score (Gemma)0.001
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 score0.612
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
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 head0.118
GPT teacher head0.342
Teacher spread0.224 · 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 teacher head, 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

Citations0
Published2023
Admission routes1
Has abstractyes

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