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Record W2620611562

Determinants of Internet Financial Reporting by Egyptian Companies

2017· article· en· W2620611562 on OpenAlexfundno aff
Laila Samy Aboutera, Amani Hussein

Bibliographic record

VenueJournals & Books Hosting (International Knowledge Sharing Platform) · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
FundersEuropean CommissionEmerald PublishingMcGill University
KeywordsStock exchangeBusinessThe InternetLeverage (statistics)AccountingProfitability indexMarket liquidityAuditFinancial ratioAnnual reportFinanceSample (material)
DOInot available

Abstract

fetched live from OpenAlex

This research aims at examining the determinants of internet financial reporting by Egyptian companies through measuring the extent of internet financial reporting (IFR) practices in Egypt and the association between IFR and the Egyptian listed companies' characteristics.The research sample consists of 133 Egyptian companies listed on the Egyptian stock exchange as well as Nile stock exchange.The sample includes only those companies that disclose financial information on the internet.This research considers; company's size, profitability, liquidity, leverage, company's age, auditor type and ownership structure as the independent variables that might impact the company's' corporate IFR practices.Moreover, a disclosure checklist of 56 voluntary items is adopted to measure the level of IFR.The findings of the multiple regression models revealed that three independent variables were found significantly associated with the level of Internet Financial Reporting including; company's size, auditor type and the company's age.However, other company characteristics were found insignificant such as liquidity, leverage, profitability and ownership structure.

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)0.002
metaresearch head score (Gemma)0.034
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.315
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0020.002
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 head0.049
GPT teacher head0.306
Teacher spread0.257 · 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 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

Citations4
Published2017
Admission routes1
Has abstractyes

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