Voluntary Use of Information Technology: An Analysis and Synthesis of the Literature
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
Voluntariness is recognized as an important influence on individual and collective technology acceptance. We conducted a comprehensive review of this literature and identified a rich set of voluntariness concepts and methods of operationalization. However, while considerable empirical evidence is reported in the literature, our review also revealed inconsistent results concerning the relationship between voluntariness and other concepts. Against that backdrop, we synthesized the literature into three types of voluntariness - perceived, intended and realizable voluntariness (RVOL), and showed how prior literature had not adequately accounted for RVOL. Moreover, we examined the multiple mechanisms that influence voluntariness and created a model to describe how to advance new knowledge about the important relationships among the three types of voluntariness and between voluntariness and user behavior. We argue that these concepts and relationships may help advance our knowledge of how a new technology is used individually and collectively in organizations.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.006 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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