Evidence map›Paper›PMID 42102100›Full record

ArticlePloS one2026

Blockchain-enabled strategic optimization: A decision analytics framework for multinational enterprises' e-commerce entry model.

Liurui Deng, Xiaoying Hu, Ying Xiao

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Liurui DengCollege of Business, Hunan Normal University, Changsha, Hunan, China.
Xiaoying HuCollege of Business, Hunan Normal University, Changsha, Hunan, China.ORCID https://orcid.org/0009-0006-5600-6139
Ying XiaoSchool of Economics and Trade, Hunan Vocational College of Commerce, Changsha, Hunan, China.ORCID https://orcid.org/0009-0000-0627-9952

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With e-commerce booming, MNEs (Multinational Enterprises) often tap into online markets through E-retailers in multinational e-commerce platforms. Therefore, which e-commerce entry model MNEs choose can be critical, especially when the MNE owning a retail division in the same market. Notably, the MNE can address the plague of low-quality images of e-retailers by introducing blockchain technology, but the effectiveness of blockchain technology for quality verification also varies across different e-commerce entry models. In this paper, we develop a two-tier supply chain model with a manufacturing division in a high-tax area and various retailers in a low-tax area. The retailers comprise the manufacturing division of the MNE and e-retailers. The e-retailers include self-operated e-commerce, FBP merchants, i.e., merchants handling sales while the platform manages product delivery and after-sales services, and SOP merchants, i.e., merchants separately manage operations, shipping, and sales. We find that the larger the tax disparity, the lower the overall profits of MNEs, irrespective of the implementation of blockchain technology. Furthermore, the overall profit of the MNE is more significant when adopting a singular e-commerce entry model without the introduction of blockchain technology; conversely, the total profit of the MNE is more significant when adopting a composite e-commerce entry model with the introduction of blockchain technology. Interestingly, when blockchain technology is implemented, the MNE is more lucrative under the e-commerce entry model with a medium initial market potential if the service gap between the e-retailer and the manufacturing division is modest.

Indexed as

BlockchainCommerceInternetModels, Economic

Identifiers

PMID42102100
PMCPMC13155611

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.