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Record W2951011315 · doi:10.5539/ibr.v12n7p57

Role of Information and Communication Technology in Applying Quality Control Procedures in Audit Offices in the Hashemite Kingdom of Jordan

2019· article· en· W2951011315 on OpenAlexvenueno aff
Reem Aqab

Bibliographic record

VenueInternational Business Research · 2019
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsContinuanceAuditBusinessQuality auditControl (management)Quality (philosophy)Sample (material)Information technologyInformation technology auditOperations managementAccountingJoint auditKnowledge managementInternal auditComputer scienceEngineeringPsychology

Abstract

fetched live from OpenAlex

The study aims to determine the impact of information technology on quality control elements and procedures, including vocational requirements, personal management procedures, client acceptance and continuance, audit performance, and following up and monitoring procedures used by auditing offices in Hashemite Kingdom of Jordan. The researcher has used descriptive analytical approach for conducting relevant literature reviews. In addition, a questionnaire has been distributed to study sample (i.e audit offices) in order to identify to which extent information technology affects audit quality control. The recent study has found that information technology affects highly quality control procedures and elements including vocational requirements, personal management procedures, client acceptance and continuance, plus audit performance in audit offices. In addition, it has concluded that information technology has a medium impact on following-up and monitoring procedures used by audit offices moreover, the study showed that using information technology has contributed to achieve quality control goals, desired.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.049
Threshold uncertainty score0.175

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.025
GPT teacher head0.331
Teacher spread0.306 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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