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Record W2571472926 · doi:10.5539/ibr.v10n2p74

Challenges of Paperless Trade: Redesign of the Foreign Trade Processes and Bundling Functions of Traditional Documents

2017· article· en· W2571472926 on OpenAlexvenueno aff
Mustafa Emre Civelek, Murat Çemberci, Nagehan Uca, Ümit Çelebi, Abdurrahman Özalp

Bibliographic record

VenueInternational Business Research · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicLaw, logistics, and international trade
Canadian institutionsnot available
Fundersnot available
KeywordsDocumentationOrder (exchange)Table (database)Database transactionBusinessComputer scienceIndustrial organizationInternational tradeEconomicsDatabase

Abstract

fetched live from OpenAlex

Technological innovations in recent years have resulted in paper based documentation will be completely abandoned in all business processes, however the paper-based processes still prevail in foreign trade transactions due to complicated business processes. Institution and companies in different countries involved in foreign trade transactions. Therefore integrative solutions are needed. This paper seeks to put forward a methodology to pave the way to the future international trade. Therefore we developed a taxonomical approach to this clutter in order to partially surmount the integration problem because a road map should be determined before the holistic solution. Taxonomical approach has been suggested for grouping the foreign trade documents in terms of their functions. All the parties participating in a foreign trade transaction should be able to connect to each other in a single online platform. There is a need for a single online platform of which all parties are members to complete a foreign trade transaction using a single integrated electronic document. Finally, opinions of the professional have been received for seeing the real procedures. Literature and practices have been synthesized and partial solution grouping the foreign trade documents in terms of their functions has been suggested. To constitute a base for the initial step of the road to integrated foreign trade document a taxonomical table has been prepared. Aim of this table to guide the firms that search for solutions to develop electronic equivalent of paper based documents.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.849
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.217
GPT teacher head0.353
Teacher spread0.136 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations11
Published2017
Admission routes1
Has abstractyes

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