Exploring collaboration technology use: how users’ perceptions twist and amend reality
Bibliographic record
Abstract
Purpose – This study aims to examine how a collaboration technology is used by three organizational groups. The main focus is on the interplay between the users’ perceptions (of the technology and of the knowledge shared) and the material properties of the collaboration technology. Design/methodology/approach – Two theoretical frameworks (social representations and sociomaterial practice perspective) examine collaboration technology use to better understand the underlying dynamics. The research is conducted as a case study in a US company where a collaboration technology was being implemented. Findings – The findings reveal a process model showing how social dynamics and users’ perceptions of what the collaboration technology can do and cannot do to share the users’ knowledge influence the users’ behaviour. Based on these perceptions, users will twist or amend their interpretation of the reality (the material properties of the technology) to justify their use of the collaboration technology. Research limitations/implications – This research is conducted as a single case study. However, the significant amount of time spent at the research site allowed for a very rich description of the events and processes involved. Practical implications – This study offers guidelines on what influences use and adoption of collaboration technologies. It highlights the importance of providing more than just training, as social dynamics and users’ perceptions continuously influence users’ behaviour. Originality/value – By combining two complementary theoretical frameworks, this study provides a novel and more in-depth explanation of collaboration technology use (or lack thereof).
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.
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 | 0.014 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".