MétaCan
Menu
Back to cohort
Record W7065445970

Effect of working capital management in Toronto exchange on oil and gas sector profitability / Noor Syazwani Hayati Azman

2017· other· en· W7065445970 on OpenAlexaboutno aff

Bibliographic record

VenueUiTM Institutional Repositories (Universiti Teknologi MARA) · 2017
Typeother
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionDemotionWork (physics)WindageCircumstantial evidence
DOInot available

Abstract

fetched live from OpenAlex

Working capital is a crucial element in order to manage the liquidity of the firms effectively. Working capital used to track the asset and liabilities of companies. It is also necessary which helping companies to make short-term decisions. The aim of carried out this research is to examine the factor affecting working capital management of oil and gas sector in Toronto Exchange that is cash conversion cycle (CCC), current ratio (CR), debt ratio (DR) and sales growth (SG) toward the return on total asset (OI) of the firms. A panel data of 10 firms selected based on its price to book value consists of five (5) from oil and gas companies and another five (5) from energy services companies. This research will be conduct in period of fifteen (15) years that is from year 2002 to 2016. This research use Ordinary Least Square (OLS) method of analysing the panel data. From this, it will be estimate that the variables of cash conversion cycle (CCC) and sales growth (SG) will have a positive relationship with profitability of firms. While variables of current ratio (CR) and debt ratio (DR) will have a negative relationship toward return on total asset. Thus, the length of period taken to liquid their asset and sales generated by companies related to improve the performance of the firms.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.869
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.011
GPT teacher head0.218
Teacher spread0.207 · 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.

Study designNot applicable
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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueUiTM Institutional Repositories (Universiti Teknologi MARA)Same topicSilicon and Solar Cell TechnologiesFrench-language works237,207