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Record W3120566820 · doi:10.5267/j.ac.2020.12.013

Influences of the environmental factors on the intention to adopt cloud based accounting information system among SMEs in Jordan

2021· article· en· W3120566820 on OpenAlexvenueno aff
Malek Hamed Alshirah, Abdalwali Lutfi, Ahmad Farhan Alshira’h, Mohamed Saad, Nahla Ibrahim, Fatihelelah Mohammed Ahmed Mohammed

Bibliographic record

VenueAccounting · 2021
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCloud computingAccounting information systemBusinessAccountingKnowledge managementProcess managementComputer science

Abstract

fetched live from OpenAlex

The objective of this study is to examine the role of external factors including MP, CP, and NP on the intention to adopt Cloud Based Accounting Information System (CB-AIS). The study proposes a theoretical framework based on institutional theory (INT). The data were collected from small and medium sized enterprise (SMEs) operating in Jordan. A total of 600 questionnaires were distributed to selected SMEs and only 142 were returned and used for the analysis. The empirical data were analyzed using the PLS-SEM modelling. The findings showed that MP, CP, and NP had significant direct associations with the CB-AIS intention to adopt. The results provide important insights to managers, researchers and policymakers to help them understand the importance of CB-AIS adopting to enhance firm performance.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

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)0.0030.000

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 head0.008
GPT teacher head0.183
Teacher spread0.175 · 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

Citations114
Published2021
Admission routes1
Has abstractyes

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