Technological Embeddedness and Organizational Change
Bibliographic record
Abstract
While various theories have been proposed to explain how technology leads to organizational change, in general they have focused either on the technology and ignored the influence of human agency, or on social interaction and ignored the technology. In this paper, we propose a new theory of technology-mediated organizational change that bridges these two extremes. Using grounded theory methodology, we conducted a three-year study of an enterprise system implementation. From the data collected, we identified embeddedness as central to the process of change. When embedded in technology, organizational elements such as routines and roles acquire a material aspect, in addition to the ostensive and performative aspects identified by Feldman and Pentland (2003). Our new theory employs the lens of critical realism because in our view, common constructivist perspectives such as structuration theory or actor network theory have limited our understanding of technology as a mediator of organizational change. Using a critical realist perspective, our theory explains the process of change as a three-stage cycle in which the ostensive, performative, and material aspects of organizational elements interact differently in each stage.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".