Information Technology, Materiality, and Organizational Change: A Professional Odyssey
Bibliographic record
Abstract
We begin with a retrospective reflection on the first author’s research career, which in large part is devoted to research about the implications of information technology (IT) for organizational change. Although IT has long been associated with organizational change, our historical review of the treatment of technology in organization theory demonstrates how easily the material aspects of organizations can disappear into the backwaters of theory development. This is an unfortunate result since the material characteristics of IT initiatives distinguish them from other organizational change initiatives. Our aim is to restore materiality to studies of IT impact by tracing the reasons for its disappearance and by offering options in which IT’s materiality plays a more central theoretical role. We adopt a socio-technical perspective that differs from a strict sociomaterial perspective insofar as we wish to preserve the ontological distinction between material artifacts and their social context of use. Our analysis proceeds using the concept of “affordance” as a relational concept consistent with the socio-technical perspective. We then propose extensions of organizational routines theory that incorporate material artifacts in the generative system known as routines. These contributions exemplify two of the many challenges inherent in adopting materiality as a new research focus in the study of IT’s organizational impacts.
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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.006 | 0.059 |
| Scholarly communication | 0.014 | 0.032 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".