Understanding the transformation of the information technology function
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
IT functions have changed considerably since they first appeared in organizations, but few researchers have tried to develop a better understanding of how they were transformed. The goal of this article is to explore the question: How and why do IT functions in organizations transform? To this end, we developed a conceptual framework built around a typology of the IT function and based on the theory of punctuated equilibrium. Two case studies were conducted in companies from different industries. Our results suggest that IT functions are transformed in response to various forces, designated as secondary forces, that push IT functions toward change, but only when these secondary forces are influencing the primary forces. These primary forces are: 1) the organization’s vision of the potential of technological tools, 2) the CIO’s participation in strategic decision-making, and 3) the level of knowledge of information systems among members of the management team. When these secondary forces have no effect on the primary forces, the IT function continues to be described by the same ideal profile. This study fills a gap in the literature on information systems by proposing a rich, yet parsimonious theoretical explanation of the transformation dynamic experienced by IT functions in organizations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.013 |
| 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)
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 it