MétaCan
Menu
Back to cohort
Record W4311783342 · doi:10.5267/j.ijdns.2022.8.011

Antecedents of mobile banking app adoption during COVID19: A perspective of Jordanian consumer

2022· article· en· W4311783342 on OpenAlexvenueno aff
Dmaithan Almajali, Ahmad Tawfig Al-Radaideh, Nour Ali Nussir, Ali Ibrahim Abu Eid, Fu’ad Abdallah Al-Fakeh, Fawzieh Masa’d

Bibliographic record

VenueInternational Journal of Data and Network Science · 2022
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsMediationQuality (philosophy)BusinessAnxietyPsychologyMobile appsService qualityService (business)Internet privacyMarketingComputer scienceWorld Wide WebPolitical science

Abstract

fetched live from OpenAlex

The effect of contextual factors namely information quality, service quality, system quality, Technological readiness, trust in applications (app) and COVID-19 health anxiety, on the intention and consequently the actual use of Mobile Payment (MP) app was examined in this study. Trust, as mediator to the relationship between technological readiness and intention to use MB-app was examined also. Data were obtained from 740 Jordanian Mobile Banking (MB) app users through an online survey. The relationship between service quality, system quality, information quality, trust in the app, COVID-19 health anxiety, Technological readiness and the intentions to use MB-app and the actual use of MB-app was empirically examined. The results showed a positive relationship between service quality, system quality, information quality, trust in the app and COVID-19 health anxiety, and the intentions to use MB-app, and in turn he actual use of MB-app, and a positive mediation of trust on the relationship between COVID-19 health anxiety and the intentions to use MB-app.

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)0.000
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 score0.278
Threshold uncertainty score0.432

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0020.002
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 head0.016
GPT teacher head0.286
Teacher spread0.270 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Data and Network ScienceSame topicOrganizational and Employee PerformanceFrench-language works237,207