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Record W3208523246

Challenges of the digital economy on international taxation rules from the perspective of global business society

2021· article· en· W3208523246 on OpenAlexaboutno aff
Keiji Aoyama

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsnot available
Fundersnot available
KeywordsDigital economyPillarBusinessIndustrial organizationProcess (computing)EconomicsEconomyMarket economyEngineering
DOInot available

Abstract

fetched live from OpenAlex

While the examination process on a new tax allocation rule has been developed in the OECD and its final discussion is still on-going, this paper explores what kind of efforts and contributions have been made by businesses who are important stakeholders on this issue and identifies whether those responses have been well addressed or not. During the drafting stage managed by the Inclusive Framework (IF), supported by the OECD secretariat, the main issue has been to what extent any residual profits of digital transformation enterprises (digital MNEs) should be allocated between the home country of the digital MNEs and market countries. The features of the digital economy, especially “Scale without mass” have served as a mechanism to allocate their residual profits to their home countries. The private sector generally believes that such outcome seems reasonable, mainly because the digital economy heavily depends on intangibles developed by the headquarters company, that bears the huge R&D expenditures. The private sector claims that the traditional allocation methodology looks reasonable and legitimate and that the government should respect it to a great extent. To support this discussion, the private sector has been referring to the 1998 Ottawa Principle endorsed by the OECD participants’ ministers. The agreed document referred to several taxation principles, including neutrality, equity, etc, as a guidance on how to address taxation of e-commerce transactions. During the discussion on the Action1 of the BEPS Project (taxation on the digital economy), businesses again have been sticking to the same Principle. It claims that any new allocation rule to address the challenge of digitalization should be proportionate to the value creation mechanism within any business model. The comments from businesses are summarized as following;. To structure a new tax base and designate allocation keys to it, if necessary, the governments should respect business accounting practice as much as possible, and the additional allocation of profits to market countries should be minimized, because the private sector heavily depends on the intangibles that are developed by its parent company as well as on the global network that is managed by its parent company. Thus, even if a new additional allocation rule would be agreed, the compliance cost for the new rule should be minimized. During the final stage of drafting the two pillar approaches, input from the private sector is important and indispensable, especially for the technical issues, such as the use of consolidated accounting reports, documentation requirements on taxpayers and dispute prevention and resolution program. So far, it is observed that public consultations have been organized in a timely manner and working effectively, however, before final political negotiations among the IF countries, consultations with businesses could produce practical and administrable adjustments to the OECD frameworks.

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)0.016
metaresearch head score (Gemma)0.018
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 score0.017
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0050.012
Scholarly communication0.0170.016
Open science0.0020.007
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0050.001

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 head0.023
GPT teacher head0.226
Teacher spread0.203 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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