E-Payment Acceptance Among German Millennials: Perception and Demographic Background
Bibliographic record
Abstract
During the last twenty years, the growth of the internet and its ability to facilitate e-commerce transactions has had a profound impact on the way business is done by both corporations and individuals (Herhausen et al., 2015; Jeffus et al., 2017). The unprecedented growth of e-commerce has driven the creation of new payment systems to transfer funds electronically from person-to-person or person-to-business (Teoh et al., 2013; Sumanjeet, 2009). The intent of this research is to explore the factors surrounding e-payment use in specific geographical regions to provide a better understanding of that regions e-payment behaviors. This research centers on German millennials, how they value e-payment, and what factors influence their acceptance of electronic funds transfer technology. To reach this goal, a survey was conducted with German millennials exploring what behavior affects their usage of e-payment systems. The results of this survey can provide insights to understand attitudes and behaviors of young generations in their e-payment. The results of this exploratory study center on the descriptive statistics of the respondents.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.000 | 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".