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Record W3203842946

DOES WORKING CAPITAL MANAGEMENT AFFECT THE PROFITABILITY OF SMALL AND MEDIUM SIZED ENTERPRISES IN JORDAN

2021· article· en· W3203842946 on OpenAlexvenueno aff
Dima Waleed Hanna Alrabadi, Wasfi Al Salamat, Abdallah Hatamleh

Bibliographic record

VenueInternational Journal of Economics and Finance · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWorking Capital and Financial Performance
Canadian institutionsnot available
Fundersnot available
KeywordsWorking capitalProfitability indexLeverage (statistics)BusinessPanel dataCapital structureCash conversion cycleSmall and medium-sized enterprisesContext (archaeology)FinanceInvestment (military)Sustainable growth rateMonetary economicsCashEconomicsEconometricsOperating cash flow
DOInot available

Abstract

fetched live from OpenAlex

This study aims to explore the impact of working capital management on Small and medium sized enterprises profitability in the context of Jordan through the period (2005-2018) after controlling for the size of firm, sales growth, and financial leverage. Balanced panel data regression is used for data analysis. The sample consists of 11 firms with a total of 154 annual observations. The results show that cash conversion cycle and financial leverage have a statistically significant negative effect on ROA of Jordanian SME’s. However, the following variables (investment policies of working capital, financing policies of working capital, the size of firm, and sales growth) have a statistically significant positive effect on ROA of Jordanian SMEs. Interestingly firm risk is also positive and significantly associated with the ROA.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.010
GPT teacher head0.200
Teacher spread0.190 · 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

Citations9
Published2021
Admission routes1
Has abstractyes

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