Internet Banking Adoption in Saudi Arabia: An Empirical Study
Bibliographic record
Abstract
The current study was conducted with the primary objective to explore the factors and analyse their relevance and importance in the adoption of internet banking in Saudi Arabia. In this paper, we gathered evidence from 300 consumers about the factors they considered important before opting for internet banking. Responses were collected by administering a Likert scale close ended structured questionnaire. Factor analysis was conducted to group the factors into significant components areas. The results showed that the factors under study explained 91.508% of the variance in internet banking adoption. Also, that the trust is the most crucial factor for the consumers of internet banking (25.950% variance) followed by ease of using internet banking services (25.188% variance); whereas 21.921% variance explained efficiency and effectiveness of the internet banking and 18.449% variance explained the importance of information about the internet banking to the consumers. The findings of this study will allow the banks to develop internet banking strategies tailored to the expectations of their clients. The study recommends banks to focus on building the trust of the customers and should also make internet banking as convenient as possible. Besides, the internet banking should be efficient and effective in delivering banking services. Furthermore, there should be sufficient information available regarding internet banking. Saudi Arabia is the largest economy in the Middle East. Of late the country has focused on the modernisation of its economy and has been trying in earnest to integrate with the world economy. The e-commerce activities are also growing; however, research in internet banking is limited. The findings of the paper can serve as a model for the adoption of internet banking especially in Saudi Arabia and in the Middle East or elsewhere in general. The research was conducted in Saudi Arabia, and more researches could be conducted based on this study in other parts of the Middle East for more generalisation of the findings.
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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 | 0.015 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".