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Record W6890209879 · doi:10.34989/sdp-2023-1

The 2021–22 Merchant Acceptance Survey Pilot Study

2023· article· en· W6890209879 on OpenAlexaffabout

Bibliographic record

VenueEconstor (Econstor) · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsBank of Canada
Fundersnot available
KeywordsCashPaymentCurrencyPoint of salePoint (geometry)Mobile paymentPayment service providerSurvey data collection

Abstract

fetched live from OpenAlex

In recent years, the rise in digital payment innovations such as contactless cards and Interac e-Transfer has spurred a discussion about the future of cash at the point of sale. The COVID19 pandemic has also contributed to this discussion: While consumers reported that some merchants started to refuse cash early in the pandemic, such reported refusals dropped as the pandemic progressed. The Bank of Canada’s most recent Merchant Acceptance Survey (MAS) took place in 2018, prompting a need for updated data to study merchant cash acceptance, payment trends and conditions for the potential issuance of a central bank digital currency (Lane 2020, 2021a). Against this background, the Bank conducted the 2021–22 MAS Pilot Study to monitor payment methods accepted by small and medium-sized businesses (SMBs). Survey data was collected from merchants in two batches, in late 2021 and early 2022. Our results show that 97% of SMBs in Canada accepted cash in 2021–22 and only 3% have plans to stop accepting cash. For cards and digital payments, merchant acceptance has increased since 2018. Additionally, the acceptance of different payment methods varies by the size of the merchant, industry and region.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.013

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 head0.043
GPT teacher head0.239
Teacher spread0.196 · 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 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

Citations1
Published2023
Admission routes2
Has abstractyes

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