MétaCan
Menu
Back to cohort
Record W3130901419 · doi:10.5267/j.ac.2021.2.008

Liquidity variations and variability cohesiveness with revenue and profitability: A case of Saudi energy sector companies

2021· article· en· W3130901419 on OpenAlexvenueno aff
Anis Ali

Bibliographic record

VenueAccounting · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
FundersDeanship of Scientific Research, Prince Sattam bin Abdulaziz UniversityPrince Sattam bin Abdulaziz University
KeywordsMarket liquidityLiquidity riskAccounting liquidityLiquidity crisisBusinessProfitability indexCurrent assetFinanceLiquidity premiumGroup cohesivenessRevenueCurrent ratioWorking capitalDebtFinancial systemMonetary economicsEconomics

Abstract

fetched live from OpenAlex

Liquidity refers to the paying ability of the business organization while profitability assesses the profit earning capacity of the business organization. The liquidity of the business organization can be bifurcated into two based on time i.e., short-term and long-term liquidity. The short-term liquidity reveals the operational efficiency while long-term liquidity refers to the financial capability to repay the long-term debts of the business organization. The short-term paying ability is the management of the working capital or efficient management of the current assets and current liabilities. The current assets and current liabilities are directly related to the revenue of the business and further affected by the profitability, indirectly. The long-term paying ability or financial health of the business organization is reflected by the debts and equity ratio. The energy sector of Saudi Arabia is a prominent sector and contributes to the economy progressively. The study is based on secondary data and reveals the long-term and short-term liquidity variations and the cohesiveness of long-term and short-term liquidity with the revenue and profitability of energy sector companies. The study reveals the significant variations in the short-term and long-term liquidity and cohesiveness between the revenue, profitability, and short-term and long-term liquidity of the energy sector companies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.621

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.203
Teacher spread0.188 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAccountingSame topicCorporate Finance and GovernanceFrench-language works237,207