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Record W2589724354 · doi:10.4236/ti.2017.81005

The Evolution of E-Commerce Payment

2017· article· en· W2589724354 on OpenAlexvenueno aff
Lin Chuan

Bibliographic record

VenueTechnology and Investment · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsPaymentNormativeBusinessMarket microstructureMicroeconomicsIndustrial organizationOrder (exchange)EconomicsFinanceLaw

Abstract

fetched live from OpenAlex

Firstly, a game model is established under unconstrained market conditions to illustrate the basic evolutionary rule of the market of e-commerce payment method. It is concluded that the establishment of e-commerce payment market is not normative under the unconstrained market conditions, which shows the importance of the introduction of the third party payment for the establishment of standardized e-commerce trading market. In this way, a standardized e-commerce market can be established. This paper analyses the model parameters to illustrate the strategies and methods to achieve good market behavior. And then it improves the model by adding legal supervision and penalties for illegal businesses and other market constraints. And it’s proved that the regulation of market is very important in creating a good market environment and exit block. Finally, this paper gives some useful suggestions on how to form a good standard of market behavior.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
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 head0.014
GPT teacher head0.205
Teacher spread0.191 · 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 designNot applicable
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
Published2017
Admission routes1
Has abstractyes

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