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Record W2952656983 · doi:10.5430/ijfr.v10n5p262

Study on the Development Strategy of Ant Financial

2019· article· en· W2952656983 on OpenAlexvenueno aff
Ximeng Zhang, Myeong Cheol Choi

Bibliographic record

VenueInternational Journal of Financial Research · 2019
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsThe InternetSWOT analysisBusinessChinaFinanceConvergence (economics)Process (computing)Financial servicesMarketingEconomicsComputer scienceEconomic growthWorld Wide Web

Abstract

fetched live from OpenAlex

Convergence of Internet technology and traditional financial industry has created a new field of Internet finance. Nowadays, China has a very large Internet user base and application market. With the application and development of the Internet, China has become one of the most developed countries that use Internet banking services and has the highest number of Internet finance users. Ant Financial is the first to enter the Internet financial market, and has now become a representative of China’s Internet finance industry due to its extensive layout and rich business. Most of the previous research has only studied a part of Ant Financial without an analytical framework. Therefore, this study intends to investigate the history, development process, and success factors of Ant Financial. The contents of this paper are as follows. First, the development process and the current situation of Ant Financial Services are expounded. Second, the advantages and disadvantages of the current development process are analyzed by the SWOT analysis technique. Through the comparison of the research results, the guiding opinions for the development of Ant Financial Services are proposed. Finally, summary of the success reasons and future prospects for development are presented.

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)0.011
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.812
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.364
GPT teacher head0.519
Teacher spread0.155 · 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 teacher head, not a consensus.

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
Published2019
Admission routes1
Has abstractyes

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