Discovering the adoption factors of internet banking usage among banking customers in Kota Kinabalu / Husinah Basari
Bibliographic record
Abstract
Internet is a powerful tool used in various field. In banking sector, Internet is use as a medium of interaction between banks and their customers. The usage of Internet is not stop there. On 2000, the banking sector in Malaysia revolutionized with the introduction of a new channel which is online banking or also known as Internet banking. Internet banking is one of the technologies which are getting recognition around the globe. It has grown tremendously over the past several years and will continue to grow as financial institutions continue to strive to allow customers to complete fund transfers, pay bills, access account information or manage their account online. This innovation seems to be accepted by many banking customers around the world despite some disadvantage such as security, trust and fraud. For Malaysia market itself, the Internet bankers shown to be increased to 8.7 millions on second quarter of 2010. A total of 115 respondents are involved in this study. And the problems analyzed include factors influencing the adoption of Internet banking as suggested by previous researchers such as TAM, DOI and privacy and security. As well as demographic profile, users' attitude and behaviors towards Internet and Internet banking. The findings based on three main different independent variables; security and privacy, Technology Acceptance Model which consists of perceived usefulness and perceived ease of use and Diffusion of Innovation characteristics. It showed that all the variables are influenced consumers' Internet banking adoption except for complexity, trialability, security and privacy factors. The recommendations from researcher also presented based on the findings in this research.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".