The effect of e-payment and online shopping on sales growth: Evidence from banking industry
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
Transforming from digitalization to digitization brings many new technologies to restructure our life and life routines. In today’s competitive world, internet infrastructures and banking industries are counted as integral components for online shopping and commercial transactions. As because, disclosure of online transactions has been allowed through internet media, that would enhance the availability of electronic payment systems. Further, this study aims to explore and investigate the relationship and impact of electronic payment methods on the sales growth with the mediating role of online shopping by targeting UAE banking Industry. This study followed the quantitative approach and a correlational design. The empirical data were collected through a survey designed on a 5-point Likert scale, 217 valid questionnaires were sent to all participants (i.e., top managers, middle managers and technicians) via emails. Different statistical analyses were performed in this study. The results of the study showed high internal consistency among the study variables as Cronbach’s Alpha values ranged from .873 to .855. Further, this study highlighted the significant relationship and direct impact between online shopping and sales growth. Meanwhile, indirect impact was confirmed by the results between online shopping and sales growth through e-payment. In this regard, results can help to identify the impact of e-payment on sales growth through online shopping and also provide advantage for this and many other similar organizational studies.
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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 | 0.002 | 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 | 0.000 | 0.001 |
| Open science | 0.003 | 0.002 |
| 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