Framing the Frameworks: A Review of IT Governance Research
Bibliographic record
Abstract
With the passage of the Sarbanes-Oxley Act in the United States in 2002, and an ever-increasing corporate focus on ensuring prudent returns on technology investments, the notion of IT governance became a major issue for both business practitioners and academics. Although the term "IT governance" is a relatively new addition to the syntax of academic research, significant previous work is reported on IT decisions rights and IT loci of control, notions that are synonymous with the current understanding of IT governance. This paper presents a literature review for existing research in IT governance. A framework, named the Conceptual Framework For IT Governance Research is proposed to provide a logical structure for existing research results. Using this framework, we classify the previous literature on governance into two separate streams that follow parallel paths of advancement. A popular contemporary notion of IT governance is then presented, together with the argument that this new notion, by implicitly extending both streams of research, represents an initial amalgamation of the two paths of literature. We conclude that even with the consideration of contemporary structures, academicians and practitioners alike continue to explore the concept of IT governance in an attempt to find appropriate mechanisms to govern corporate IT decisions.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.019 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".