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Vertical Integration and Proprietary Information Transfers

2001· article· en· W1985586978 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

VenueJournal of Economics & Management Strategy · 2001
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMerger and Competition Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsUpstream (networking)Downstream (manufacturing)BusinessVertical integrationInformation sharingCommissionCompetition (biology)Industrial organizationWelfareEconomic surplusPrivate information retrievalInformation asymmetrySocial WelfareValue (mathematics)Process (computing)MicroeconomicsEconomicsMarketingMarket economyFinanceTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

Suppose that rival downstream producers of a final good contract with the same upstream supplier of an input and, in the process, reveal private information. A vertical merger between the upstream supplier and one of the downstream firms may dissipate the information advantage of the remaining downstream firms. The welfare consequences of such a merger and related information sharing depend on the value of information, the benefits of integration apart from information sharing, and the nature of upstream competition. In this paper, conditions are found under which owners of a vertically integrated firm are better off breaking up into independent firms. This result may explain AT&T's recent spinoff of Lucent Technologies. Further results suggest that a prohibition on information transfers, such as that often proposed by the Federal Trade Commission and Department of Justice as a precursor to approving vertical mergers, may actually reduce expected consumer surplus and expected social welfare.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.644

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.207
Teacher spread0.183 · 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