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Record W1733025048 · doi:10.32920/ryerson.14639334.v2

When an inefficient firm makes higher profit than its efficient rival

2022· article· en· W1733025048 on OpenAlexaff
Debapriya Sen, Giorgos Stamatopoulos

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMerger and Competition Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMicroeconomicsCournot competitionSubgame perfect equilibriumProfit (economics)DuopolyRevenueIndustrial organizationEconomicsNash equilibriumBusinessCompetition (biology)Game theory

Abstract

fetched live from OpenAlex

<p>This paper considers a Cournot duopoly game with endogenous organization structures. There are two firms A and B who compete in the retail market, where A is more efficient than B. Prior to competition in the retail stage, firms simultaneously choose their organization structures which can be either ‘centralized’ (one central unit chooses quantity to maximize firm’s profit) or ‘decentralized’ (the retail unit chooses quantity to maximize firm’s revenue while the production unit supplies the required quantity). Identifying the (unique)Nash Equilibrium for every retail-stage subgame, we show that the reduced form game of organization choices is a potential game. The main result is that with endogenous organization structures, situations could arise where the less efficient firm B obtains a higher profit than its more efficient rival A.</p>

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)0.000
metaresearch head score (Gemma)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.940
Threshold uncertainty score1.000

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0720.001

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.

Opus teacher head0.039
GPT teacher head0.224
Teacher spread0.185 · 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 designTheoretical or conceptual
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

Citations0
Published2022
Admission routes1
Has abstractyes

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