Role of network externalities and trust facilitators in shaping mobile payment application continuance intentions: variations across stages of adoption
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
Purpose The study proposes six mobile application attributes that drive pleasurable experiences, perceived usefulness, satisfaction and continuance intentions: number of members, perceived compatibility, perceived complementarity, structural assurance, ubiquitous connection and contextual offerings. Design/methodology/approach The relative effects of these variables on perceived usefulness and pleasurable experiences are evaluated across early and late adopters. The context of the study was m-payment applications and data from 322 early adopters and 321 late adopters were used to validate the framework with structural equation modelling, as well as to measure the intergroup differences with multi-group analysis. Findings The technological and legal backends of the m-payment technology need to be robust such that users derive a meaningful consumption experience, thereby increasing their continued reuse of the m-payment application. Originality/value This work adds theoretically by developing a robust post-adoption model for smartphone applications across different stages of adoption.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it