Setting the Record Straight: The Intellectual Legacy of H. Igor Ansoff (1918–2002)
Bibliographic record
Abstract
ABSTRACT This study presents a comprehensive annotated bibliography of H. Igor Ansoff's intellectual contributions, addressing significant gaps in existing citation databases such as Scopus and Web of Science, which capture only 9 to 15 percent of his work. Leveraging the Ansoff Archive, this review systematically compiled and verified 165 unique publications, including 56 newly identified works, 29 missing or lost items, and 16 strategic consultancy tools. Through meticulous archival research, cross referencing, and international collaboration, metadata inaccuracies were corrected and Ansoff's global impact was documented, encompassing publications in sixteen languages and extensive consultancy work. The bibliography is organized chronologically and thematically, with detailed codes for corrections, missing works, and verifications. This resource enhances understanding of Ansoff's foundational role in strategic management, highlighting his concepts of strategic surprise and environmental turbulence, and provides avenues for future research on his influence on contemporary strategic frameworks and the broader historiography of management scholarship.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".