An Investigation of the Effects of Customer's Educational Attainment on their Adoption of E-banking in Nigeria
Bibliographic record
Abstract
The study aimed at investigating the effects of customers’ educational attainment on their adoption of e-banking in Nigeria and adopted the extension of technology adoption model (TAM) by adding customers’ educational attainment to it. The researcher used primary data collected through administered structured questionnaire. The researcher employed the SPSS (16.0) for descriptive statistical analysis and the Structural Equation Model (SEM) as statistical test tool using AMOS (16.0). By extending the TAM, the study concluded that customers’ educational attainment directly influence customers’ perceived usefulness and perceived ease of use and through these indirectly influence the level of adoption of e-banking by customers. The results of this study provides solid ground for developing appropriate marketing strategies to encourage the adoption of e-banking by the Nigerian banking customers. The study recommended that banks use different customers’ educational attainment levels as e-banking product designing tool, thus making adoption easier and faster; and Government should make efforts to improve the level of literacy, especially computer literacy among citizens. This will make it easier for customers to operate, interact and access e-banking platforms in Nigeria.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".