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Enterprise Supply Chain from the Perspective of Socioeconomics——Taking Taobao and Amazon as Examples

2023· article· en· W4386641150 on OpenAlex
Yaze Sun

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.

Bibliographic record

VenueAdvances in Economics Management and Political Sciences · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicImpulse Buying and Technology Impacts
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAmazon rainforestSupply chainThe InternetPerspective (graphical)BusinessMarketingMobile internetBig dataIndustrial organizationComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

With the rapid development of the Internet in the world, the Internet has connected the world as a whole, and online shopping has brought many conveniences to people. People can buy items from all over the world on their mobile phones or computers. Especially in the sudden epidemic period, people stay at home, so online shopping has gradually become the choice of more and more people. This paper mainly studies the corporate supply chains of Taobao and Amazon and their supply policy changes and impacts before and after the epidemic. This paper uses literature analysis method and others to analyze and study this topic. Research data are mainly obtained from professional articles or literature. The results of the study found that both companies found suitable measures for their own supply chain development during the epidemic, and adopted them in a timely manner, and finally achieved unexpectedly good results both at the economic level and social employment level.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.026
GPT teacher head0.276
Teacher spread0.250 · 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