MétaCan
Menu
Back to cohort
Record W3120426549 · doi:10.5267/j.ac.2020.12.019

Profitability of energy sector companies of Saudi Arabia: Mutual analysis based on revenue and investment

2021· article· en· W3120426549 on OpenAlexvenueno aff
Anis Ali, Mohammad Zulfeequar Alam

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
KeywordsProfitability indexRevenueBusinessInvestment (military)Industrial organizationProfit (economics)Return on investmentFinanceEconomicsMicroeconomics

Abstract

fetched live from OpenAlex

The profitability of the business organization is the relative measurement and explores the profit earning capacity. There are two concepts of measuring profitability, which are profitability based on revenue, and investments. Gross and net profitability are the means of expression of the profitability based on revenue while investment profitability can be measured based on owners’ investment and total investment or total assets. Secondary data from the websites of the energy sector companies are taken for the study and ratio analysis, rank correlation is applied to get the similarity or differences in the profitability and relational relationship of the energy sector companies of Saudi Arabia. The study reveals that there was a significant difference in the profitability of the energy sector companies. Possibly, internal and external factors of the business organizations govern the profitability. There is a perfect and positive relational correlation between revenue and profitability while a highly negative correlation exists between profitability and investments. This may be due to overcapitalization or underutilization of the resources. Enhancement of velocity of operational activity is necessary to enhance the operational level of energy sector companies of Saudi Arabia. There is a need to control the indirect manufacturing and administrative expenses in smaller organizations and further investment in the energy sector companies is not advisable.

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 score0.012
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.017
GPT teacher head0.206
Teacher spread0.189 · 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