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Record W2460744065 · doi:10.1111/rssa.12208

Retail Payment Innovations and Cash usage: Accounting for Attrition by using Refreshment Samples

2016· article· en· W2460744065 on OpenAlexaff
Heng Chen, Marie‐Hélène Felt, Kim P. Huynh

Bibliographic record

VenueJournal of the Royal Statistical Society Series A (Statistics in Society) · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsBank of Canada
Fundersnot available
KeywordsPoint of salePaymentCashAttritionPaceBusinessPoint (geometry)Value (mathematics)ATM cardFinanceComputer science

Abstract

fetched live from OpenAlex

Summary Contactless credit cards and stored value cards are touted as a fast and convenient method of payment to replace cash at the point of sale. Cross-sectional approaches find a large effect of these retail payment innovations on cash usage (around 10%). Using a semiparametric panel model that accounts for unobserved heterogeneity and general forms of attrition, we find no significant effect for contactless credit cards and only a 2% reduction in cash usage stemming from single-purpose stored value cards. These results point to the uneven pace of payment innovation diffusion.

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)0.080
metaresearch head score (Gemma)0.206
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.424

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0800.206
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0040.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.033
GPT teacher head0.245
Teacher spread0.212 · 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 designSimulation or modeling
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

Citations35
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Royal Statistical Society Series A (Statistics in Society)Same topicDigital Platforms and EconomicsFrench-language works237,207