Factors affecting the adoption of e-wallets to enter cashless society: An integration approach
Bibliographic record
Abstract
The Malaysian government actively encourages the development of e-wallets in Malaysia and set a goal to enter a cashless society by 2050. However, the mobile technology that has swept the world does not seem to be developing smoothly in Malaysia. The objective of the study is to investigate the determinants that impact the user behavior of Malaysians in adopting e-wallets and proposes integration theoretical models, namely UTAUT 2, Diffusion of Innovation, and self-efficacy to support the study. Data were collected among 253 Malaysian e-wallet users in the Federal State of Kuala Lumpur. The survey (online questionnaire) was distributed to respondents via QR codes and links as data collection. The PLS-SEM was utilized to test hypothetical relationships. The findings of the study demonstrated that compatibility, hedonic motivation, habits, and self-efficacy have a significant relationship with the user behavior of e-wallets. Self-efficacy was found to be the strongest predictor in influencing the use behavior of e-wallets. Conclusion, implications, and suggestions for future study were also discussed.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.003 | 0.001 |
| 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".