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Record W2553042893

Research Trends in the Diffusion of Internet Banking inDeveloping Countries

2014· article· en· W2553042893 on OpenAlexvenueno aff
Humphrey M. Sabi

Bibliographic record

VenueThe Journal of Internet Banking and Commerce · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsnot available
Fundersnot available
KeywordsThe InternetLaggingDeveloping countryBusinessWork (physics)PhenomenonMarketingEconomic growthEconomicsComputer scienceWorld Wide Web
DOInot available

Abstract

fetched live from OpenAlex

The internet banking phenomenon has transformed the way banks across the world carry out banking transactions and has brought about new strategic directions for investment in banking information and communication technologies. This paper provides the research trends in the diffusion and adoption of internet banking in developing countries through a content analysis of existing literature that focused on developing countries. The main purpose of the study is to present the current level of research on internet banking in developing countries and expose any gaps that need scholarly attention. Through the analysis of 188 journal articles that focused on internet banking diffusion, adoption and implementation in developing countries, we found that research on internet banking has gained rapid scholarly attention in developing countries since the year 2000 when internet banking became a popular phenomenon and peaking in 2012. However the results also show a dominance of research studies based in Asian countries with many African, Caribbean and South American countries still lagging behind in internet banking research. The finding provides insightful directions and research gaps on internet banking and will be useful to academics and practitioners who are working or plan to work in the area of internet banking in developing countries.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.041
GPT teacher head0.292
Teacher spread0.250 · 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

Citations5
Published2014
Admission routes1
Has abstractyes

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