Research Trends in the Diffusion of Internet Banking inDeveloping Countries
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.011 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".