Towards Understanding the Consumer Behavior of Mobile Banking Applications for Management Decision Makers
Bibliographic record
Abstract
The rapid growth of mobile applications in the banking sector has been increasing due to the ease of use and saving the time of users. However, the fierce competition between banks draws attention to the factors that increase the use of banking mobile applications to maintain the level of satisfaction of the customers of each bank. One of the crucial aspects that decision-makers need to understand is the consumer behavior of mobile banking applications. Therefore, this research paper aims to present a comprehensive exploration of mobile banking adoption by examining the interplay of cultural dynamics, usability, cross-cultural comparisons, economic factors, and the significance of longitudinal insights. It elucidates how cultural norms and societal expectations impact adoption, emphasizing regional variations. The study also dissects mobile banking app interfaces to enhance user-friendliness, tailoring them to diverse user preferences. Cross-cultural comparisons shed light on the interplay between culture, economics, and regulations. It scrutinizes economic factors, considering income levels and financial literacy while emphasizing the importance of longitudinal studies for tracking evolving adoption patterns. This research not only advances our knowledge of mobile banking adoption but also offers practical insights for banks, policymakers, and service providers as they navigate the rapidly evolving mobile banking landscape in an increasingly digital world.
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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 | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".