The Other Side of Acceptance: Studying the Direct and Indirect Effects of Emotions on Information Technology Use1
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- none
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: ObservationalConsensus signal: none
- Genre
- Candidate signal: EmpiricalConsensus signal: Empirical
- Teacher disagreement score
- 0.895
- Threshold uncertainty score
- 0.201
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.292 · how far apart the two teachers sit on this one work
- Validation status
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
Abstract
Much ado has been made regarding user acceptance of new information technologies. However, research has been primarily based on cognitive models and little attention has been given to emotions. This paper argues that emotions are important drivers of behaviors and examines how emotions experienced early in the implementation of new IT applications relate to IT use. We develop a framework that classifies emotions into four distinct types: challenge, achievement, loss, and deterrence emotions. The direct and indirect relationships between four emotions (excitement, happiness, anger, and anxiety) and IT use were studied through a survey of 249 bank account managers. Our results indicate that excitement was positively related to IT use through task adaptation. Happiness was directly positively related to IT use and, surprisingly, was negatively associated with task adaptation, which is a facilitator of IT use. Anger was not related to IT use directly, but it was positively related to seeking social support, which in turn was positively related to IT use. Finally, anxiety was negatively related to IT use, both directly and indirectly through psychological distancing. Anxiety was also indirectly positively related to IT use through seeking social support, which countered the original negative effect of anxiety. Post hoc ANOVAs were conducted to compare IT usage of different groups of users experiencing similar emotions but relying on different adaptation behaviors. The paper shows that emotions felt by users early in the implementation of a new IT have important effects on IT use. As such, the paper provides a complementary perspective to understanding acceptance and antecedents of IT use. By showing the importance and complexity of the relationships between emotions and IT use, the paper calls for more research on the topic.
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.
The record
- Venue
- MIS Quarterly
- Topic
- Technology Adoption and User Behaviour
- Field
- Decision Sciences
- Canadian institutions
- McGill UniversityConcordia University
- Funders
- not available
- Keywords
- Technology acceptance modelBusinessInformation technologyKnowledge managementMarketingPsychologyComputer scienceHuman–computer interactionUsability
- Has abstract in OpenAlex
- yes