Two decades of integrated reporting in transition: A bibliometric and thematic analysis
Bibliographic record
Abstract
This study discusses Integrated Reporting (IR) research through the lens of its thematic, geographical, and citation evolution from 2006 to 2024. The methodology demonstrates 1,136 SCOPUS-indexed publications, the PRISMA framework, VOSviewer for co-occurrence mapping and Bibliometrics for trend and thematic analysis. The findings reveal that the subject has evolved towards empirical (quantitative) investigations addressing IR quality, determinants, and organizational outcomes. Geographical mapping shows research concentration in Europe and emerging engagement from Asia-Pacific regions, while citation analysis highlights the growing influence of sustainability and ESG-oriented frameworks. Thematic mapping further identifies a paradigm shift from standalone IR studies toward integrated approaches combining CSR, ESG, and SDG perspectives, reflecting the institutionalisation of IR. Unlike previous bibliometric studies, this paper covers a longer time span and a broader dataset, about how the field has matured as a bridge between financial and non-financial reporting. The study thus shows new areas of research to focus.
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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 | 0.030 | 0.085 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.054 | 0.114 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".