Organizations as Digital Enactment Systems: A Theory of Replacement of Humans by Digital Technologies in Organizational Scanning, Interpretation, and Learning
Bibliographic record
Abstract
Digital transformation has become a dominant phenomenon of interest among information systems scholars. To account for this phenomenon, it is imperative to develop a theoretical understanding of its processes and objects. We adapt a seminal organizational theory that conceptualizes organizations as interpretation systems to a possible future of organizations. We theorize digital transformation as a progressive replacement of humans by digital technologies in performing an organization’s fundamental activities underpinning the processes of scanning, interpretation, and learning that encompass an organization’s interaction with its environment. As a result, organizations cease to be human interpretation systems and instead turn into digital enactment systems, where digital technologies, instead of humans, nearly autonomously create and act upon information. We illustrate this digital transformation theory using the example of high-frequency trading. This transformation redefines the relationship among organizations, information, and the environment, changing the role of humans and reshaping strategic decision-making. Thus conceived, digital transformation offers a concrete way of theorizing and accounts for deep implications on the nature of organizations and organizing in the digital age.
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How this classification was reachedexpand
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 | 0.005 |
| 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 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".