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Record W2077964603 · doi:10.3406/ecofi.2010.5385

Une analyse des facteurs de l’acceptation et de l’usage des instruments de paiement par les commerces en France

2010· article· en· W2077964603 on OpenAlexaboutno aff
David Bounie, Jean-Pierre Buthion, Abel François

Bibliographic record

VenueRevue d économie financière · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsPaymentPayment cardBusinessCashSample (material)Point of salePayment service providerComputer scienceFinance

Abstract

fetched live from OpenAlex

An Analysis of the Factors of the Acceptation and Use of Payment Instruments by Retailers in France The empirical literature on the economics of payment instruments mainly focused on consumer payment behaviours. However, the recent theoretical studies on the two-sided markets applied to payment cards show that merchant plays as well a fundamental role in the use of payment instruments at the point of sale. Now, to the exception of a Canadian study realized by Arango and Taylor (2008), there is no empirical study dedicated to the analysis of the determinants of the acceptation and use of the payment instruments by retailers. Using an original data set from a survey administrated in France from March to May 2008 on a sample of 4,601 retailers who sell goods and services to final consumers, this paper aims at analyzing the factors that influence the acceptation and use of cash, check and payment card by French retailers. Classification JEL : E42, G24, L81.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.332

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.227
Teacher spread0.203 · 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 designObservational
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

Citations6
Published2010
Admission routes1
Has abstractyes

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Same venueRevue d économie financièreSame topicDigital Platforms and EconomicsFrench-language works237,207