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Record W4408617101 · doi:10.1561/111.00000074

Value Chain Configuration and Coopetition

2025· article· en· W4408617101 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStrategic Management Review · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCoopetitionValue (mathematics)BusinessChain (unit)Industrial organizationMathematicsMicroeconomicsEconomicsStatisticsPhysicsGame theory

Abstract

fetched live from OpenAlex

Coopetition — the simultaneous collaboration and competition be- tween firms — has recently risen to become a major subfield in the strategic management domain. Actually, a subfield labeled “coope- tition strategy” has begun to emerge and take shape. This essay reflects how the findings in the coopetition strategy literature align with some of the classic questions in strategic management and discusses the contributions of the six papers published in the SMR Special Issue on Coopetition Strategy. In the context of coopetition strategy, we reflect on (1) how firms gain competitive advantage and improve their performance, (2) how firms create and capture value, (3) the optimal boundaries (and overlaps) between firms, and, last but not least, (4) how firms make strategic decisions. We hope that this essay and the special issue as a whole may generate even greater momentum to consolidate, theorize, and position coopeti- tion strategy within the broader strategic management literature.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.971
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.256
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it