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Record W2142345840 · doi:10.5539/jms.v1n1p32

Evaluating the Impacts of Online Banking Factors on Motivating the Process of E-banking

2011· article· en· W2142345840 on OpenAlexvenueno aff
Akram Jalal, Jassim Marzooq, Hassan A. Nabi

Bibliographic record

VenueJournal of Management and Sustainability · 2011
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsnot available
Fundersnot available
KeywordsLikert scaleUsabilityCredibilityScale (ratio)Technology acceptance modelBusinessThe InternetInformation securityMarketingPsychologyComputer scienceWorld Wide WebComputer security

Abstract

fetched live from OpenAlex

Purpose – The purpose of this research paper is to explore and mature the Impact of selected factors on the customers’ intention to use internet banking in Bahrain.Design/methodology/approach – This research based on an empirical study using a questionnaire with five-point Likert-scale, is applied to 171 usable responses. Three factors are tested, that is perceived usefulness (PU), perceived ease of use (PEOU), security and privacy (PC).Findings – Results indicate that all the elements for the three identified factors are important with respect to the users’ adoption of e-banking services. Credibility factors (Security and Privacy) are the major sources of dissatisfaction, which have remarkably impacted users’ satisfaction. In the meantime, perceived ease of use (PEOU) and perceived usefulness (PU) are sources of satisfaction. The results also disclose that security and privacy factors play an important part in determining the users’ acceptance of e-banking services with respect to different segmentation of age group, income level and level of education.

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)0.009
metaresearch head score (Gemma)0.004
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 score0.089
Threshold uncertainty score0.496

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.151
GPT teacher head0.432
Teacher spread0.281 · 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

Citations29
Published2011
Admission routes1
Has abstractyes

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