Choosing a Fit Technology: Understanding Mindfulness in Technology Adoption and Continuance
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
Mindfulness is an important emerging concept in society. This research posits that a user’s mindful state when adopting a technology is a crucial factor that determines how the technology will fit the task context at the post-adoption stage and, thus, has profound influence on user adoption and continued use of technology. Based on the mindfulness literature, we conceive of a new concept (mindfulness of technology adoption (MTA)) as a multi-faceted reflective high-order factor. We develop a MTA-TTF (task-technology fit) framework and integrate it into the cognitive change model to develop a research model that delineates the mechanisms through which MTA influences user adoption and continued use of technology. We examined the model via a longitudinal study of students’ use of wiki systems. The results suggest that mindful adopters will more likely perceive a technology as useful and choose a technology that turns out to fit their tasks. Hence, mindful adopters are likely to have high disconfirmation, perceived usefulness, and satisfaction at the post-adoption stage. The findings have significant implications for IS research and practices.
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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 | 0.004 | 0.005 |
| 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 | 0.002 |
| 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