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Record W3123447939 · doi:10.1111/jems.12306

A theory of multihoming in rideshare competition

2019· article· en· W3123447939 on OpenAlexaff
Joshua S. Gans

Bibliographic record

VenueJournal of Economics & Management Strategy · 2019
Typearticle
Languageen
FieldEngineering
TopicTransportation and Mobility Innovations
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMultihomingDuopolyMonopolyCompetition (biology)MicroeconomicsFace (sociological concept)EconomicsIndustrial organizationBusinessComputer scienceThe InternetCournot competitionSociology

Abstract

fetched live from OpenAlex

Abstract We examine competition among ridesharing platforms, where firms compete on both price and the wait time induced with idled drivers. We show that when consumers are the only agents who multihome, idleness is lower in duopoly than when consumers face a monopoly ridesharing platform. When drivers and consumers multihome, idleness further falls to zero as it involves costs for each platform that are appropriated, in part, by their rival. Interestingly, socially superior outcomes may involve monopoly or competition under various multihoming regimes, depending on the density of the city, and the relative costs of idleness versus consumer disutility of waiting.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.031
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0040.005
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0310.001

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 head0.015
GPT teacher head0.213
Teacher spread0.198 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations57
Published2019
Admission routes1
Has abstractyes

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