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Record W4380537681 · doi:10.5267/j.ijdns.2023.5.017

The impact of accounting information systems on enhancing financial information security in Jordanian banks

2023· article· en· W4380537681 on OpenAlexvenueno aff
Thaer Ahmad Abutaber

Bibliographic record

VenueInternational Journal of Data and Network Science · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsnot available
Fundersnot available
KeywordsAccounting information systemBusinessAccountingInformation securityCorporate governanceInformation systemSample (material)Work (physics)Information security managementInformation technologyInformation systems securityInformation governanceFinanceManagement information systemsComputer securityComputer scienceSecurity information and event managementEngineeringCloud computing security

Abstract

fetched live from OpenAlex

The aim of the current study is to examine the impact of accounting information systems (AIS) on enhancing financial information security in Jordanian banks by the moderating role information technology (IT) governance. The sample of the study includes 149 administrative employees in banks operating in Jordan and a questionnaire is used as the tool of the study. The results indicate that there is an effect for accounting information systems on enhancing financial information at operating banks in Jordan on information systems' operating, inputs, and outputs. The results also indicated in effect the level for information technology governance on the relationship between accounting information systems in achieving information security at the banks operating in Jordan. Considering the result obtained, the study concluded with a group of recommendations the most important among which was to work on establishing departments to protect and secure accounting information, as well as securing qualified cadres to monitor the systems.

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)0.003
metaresearch head score (Gemma)0.012
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 score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.279
Teacher spread0.264 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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