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Record W4408282233 · doi:10.3390/jrfm18030147

The Role of Organizational Culture in Digital Transformation and Modern Accounting Practices Among Jordanian SMEs

2025· article· en· W4408282233 on OpenAlexvenueno aff
Elina F. Hasan, Mohammad Abdalkarim Alzuod, Khalid Hasan Al jasimee, Sajead Mowafaq Alshdaifat, Areej Faeik Hijazin, Laith T. Khrais

Bibliographic record

VenueJournal of risk and financial management · 2025
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
FundersMiddle East University
KeywordsOrganizational cultureBusinessTransformation (genetics)AccountingDigital transformationKnowledge managementPolitical sciencePublic relationsComputer science

Abstract

fetched live from OpenAlex

This study investigates the impact of digital transformation on modern accounting practices among Jordanian SMEs, focusing on the moderating role of organizational culture. Digital transformation using AI, blockchain, and cloud computing improves operational efficiency, real-time financial reporting, and decision making. However, the integration of these technologies poses challenges such as skill gaps, cost constraints, and cultural resistance. A quantitative survey of 480 employees in managerial roles from Jordanian SMEs shows that organizational culture plays a dual role as a driver and moderator of digital transformation. The findings confirm the role of digital transformation in reshaping modern accounting practices. Also, this study shows that to get the most out of digital transformation in accounting, a culture of innovation and continuous learning is required.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.002
GPT teacher head0.190
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations34
Published2025
Admission routes1
Has abstractyes

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