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Record W4403560389 · doi:10.1080/10919392.2024.2415746

The Addition of New Payment Method and Shareholder Value: Evidence From Cryptocurrency Adoption

2024· article· en· W4403560389 on OpenAlex
Kamran Eshghi, Samira Farivar

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Organizational Computing and Electronic Commerce · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsCarleton UniversityLaurentian University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCryptocurrencyBusinessPaymentValue (mathematics)ShareholderShareholder valueCommerceComputer scienceCorporate governanceComputer securityFinanceMathematicsStatistics

Abstract

fetched live from OpenAlex

Despite the growing adoption of cryptocurrencies as a payment method, the literature lacks a comprehensive exploration of its performance outcome. To address this gap, authors examine the impact of firms’ adoption of cryptocurrencies as a payment method on shareholder value. Employing event study methodology, authors analyze the effect of cryptocurrency adoption announcements made by 27 U.S. firms between 2013 and 2020 on shareholder value. The results indicate that cryptocurrency adoption leads to positive abnormal returns, with an average of 0.65% on the announcement day. Further analysis reveals that firms’ advertising intensity amplifies the positive impact of cryptocurrency adoption on shareholder value. Additionally, non-retail firms tend to receive greater benefits from cryptocurrency adoption compared to retail firms.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.072
GPT teacher head0.394
Teacher spread0.321 · 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