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Record W3193983199 · doi:10.1002/mde.3438

Optimal pricing and choice of platform advertising schemes considering across‐side network effect

2021· article· en· W3193983199 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

VenueManagerial and Decision Economics · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsToronto Metropolitan University
FundersFundamental Research Funds for the Central UniversitiesChina Scholarship CouncilNational Natural Science Foundation of China
KeywordsSocial plannerScheme (mathematics)PlannerOperator (biology)Point (geometry)MicroeconomicsValue (mathematics)Social WelfareComputer scienceWelfareAdvertisingMathematical optimizationEconomicsBusinessMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

This paper examines the choice of advertising schemes for the two‐sided platform considering the across‐side network effect. We present various advertising schemes, derive the equilibrium decisions, and then compare these schemes from the point of view of the platform operator and social planner. Compared to the “TN” scheme, commissions charged from the provider in the “SA” scheme and the “TA” scheme are higher, but the former scheme is beneficial to the provider. Moreover, there exists a threshold value of the across‐side network effect, and hence, the “TA” scheme cannot bring the largest 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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.881
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 communication0.0010.003
Open science0.0000.001
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 head0.016
GPT teacher head0.229
Teacher spread0.213 · 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