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Record W2030790307 · doi:10.1506/26tj-40p4-lyev-93ck

Synergy among Seemingly Independent Activities*

2002· article· en· W2030790307 on OpenAlexvenueno aff
Anil Arya

Bibliographic record

VenueContemporary Accounting Research · 2002
Typearticle
Languageen
FieldDecision Sciences
TopicAuction Theory and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic rentIncentiveAdverse selectionConvexityStochastic gameMicroeconomicsProduction (economics)EconomicsValue (mathematics)Principal (computer security)Scale (ratio)MathematicsComputer scienceFinancial economicsStatistics

Abstract

fetched live from OpenAlex

Abstract “Synergy” implies that the value of activities undertaken jointly is greater than the sum of the values of the individual activities. Reasons cited for synergy include economies of scale, benefits due to vertical integration, and efficiency gains from shared inputs and skills. This paper shows that incentive (control) reasons alone can make activities synergistic. The result is derived in a model of adverse selection with risk‐neutral participants and linear technology. The linearity in the setting removes any obvious benefits to undertaking activities in tandem. Synergy gains are attributed to a convexity in the principal's payoff introduced by the activities' impact on the production versus rents trade‐off.

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 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)0.012
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.242
GPT teacher head0.426
Teacher spread0.184 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2002
Admission routes1
Has abstractyes

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