From Founding to Frontiers: Mapping the Intellectual Landscape through A Quarter Century of Research in Communications of the AIS
Bibliographic record
Abstract
The Communications of the Association for Information Systems (CAIS), one of the founding journals of the Association for Information Systems, marked its 25th anniversary in 2024. In commemoration, this study offers a comprehensive bibliometric and science mapping review of CAIS’s scholarly evolution. While CAIS was established in 1999, consistent bibliometric coverage in Scopus and Web of Science began in 2006; thus, our analysis spans 2006-2024, reflecting nearly two decades of indexed output within the broader 25-year history of the journal. Drawing on 1,152 articles from Web of Science and Scopus, analyzed using the SPAR-4-SLR protocol and Biblioshiny, this study maps CAIS’s academic impact and thematic evolution. Results identify the journal’s most cited works, influential authors, institutions, and countries, while highlighting shifts in its intellectual structure. A unique contribution is the integration of download data from the CAIS website, complementing citation metrics. Regression analysis shows a strong positive link between downloads and citations, indicating how readership translates into scholarly influence. The findings also reveal a clear geographical imbalance, with North America, particularly the United States, dominating outputs. Guideline papers emerge as especially impactful. Based on these insights, we propose a research agenda to guide future CAIS contributions.
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.030 | 0.054 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".