The effect of perceived security, perceived ease of use, and perceived usefulness on consumer behavioral intention through trust in digital payment platform
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study investigates the application of the technology acceptance model (TAM) on the digital payment using social media platforms with the extended inclusion of perceived ease of use, perceived security, perceived usefulness, and trust in enhancing consumer behavioral intention. This work has surveyed 250 consumer films on the digital social media platform. Data collection used a questionnaire designed with a five-point Likert scale. The questionnaire was created using a Google Form, and questionnaire distribution was performed by sending the link through social media to the respondents. As many as 300 questionnaires were distributed, and 258 questionnaires were considered valid for further analysis. Data analysis used smartPLS software version 3.0. The result revealed that nine hypotheses were empirically supported while the others two were not supported. Perceived security directly affects trust and consumer behavioral intention. Perceived ease of use directly affects perceived usefulness and consumer behavioral intention. Perceived security indirectly influences consumer behavioral intention through trust and perceived usefulness. Furthermore, perceived usefulness directly affects trust and consumer behavioral intention. Besides, trust directly affects consumer behavioral intentions. Perceived ease of use indirectly affects behavioral intention through perceived usefulness. Moreover, perceived security affects consumer behavioral intentions indirectly through trust. Perceived ease of use influences perceived usefulness. However, perceived usefulness did not indirectly influence behavioral intention through trust. Finally, perceived ease of use did not affect consumer behavioral intention through perceived usefulness and trust. These findings extended the application of the technology acceptance model in using digital payment platforms in Indonesia. These findings reinforced current research on user adoption of new technology. Furthermore, this result provides a managerial implication for digital payment platforms providers to improve consumer behavioral intentions.
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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 | 0.001 |
| 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 | 0.002 |
| Open science | 0.002 | 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 it