Determinants of the continuous use of mobile apps: The mediating role of users awareness and the moderating role of customer focus
Bibliographic record
Abstract
This research empirically explored the factors influencing the continuous use of mobile Apps in Jordan. The research utilized the Theory of Planned Behavior, the Diffusion of Innovation Theory and the Social Cognitive Theory to build the conceptual foundation of the research model. Using a quantitative approach, the study utilized a questionnaire with a set of well-validated items for the purpose of collecting data. The study collected 524 usable surveys, and analyzed the data using structural equation modeling technique (PLS-SEM). Results indicated that the three constructs relevant to this study (perceived risk, mobile self-efficacy, and social influence) were significant in predicting a users' awareness and the continuous use of mobile Apps. Customer focus moderated the relationship between awareness and continuous intention. In addition, the findings also confirm that users’ awareness mediated the relationship between the three independent variables and the continuous use. The Detailed findings of this research are discussed, with conclusions and future research reported at the end.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".