Evidence map›Paper›PMID 38204929›Full record

ArticleRisk management and healthcare policy2024

Blockchain Adoption for Generic Drugs in the Medicine Supply Chain with Consumers' Risk-Aversion: A Game-Theoretic Model Within Chinese Legal Framework.

Zibin Cui, Xiangdong Liu, Zehua Feng, Zhengzong Huang

Abstract read
In one paragraph

Article in Risk management and healthcare policy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Zibin Cui *School of Management, Guangdong University of Technology, Guangzhou, People's Republic of China.
Xiangdong Liu *School of Law, Guangdong University of Technology, Guangzhou, People's Republic of China.
Zehua FengSchool of Law, Guangdong University of Technology, Guangzhou, People's Republic of China.
Zhengzong HuangSchool of Marxism, Shenzhen Technology University, Shenzhen, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Blockchain is expected to mitigate consumers' risk-aversion and quality uncertainty about generic drugs in medicine supply chains. This study investigates the effect of blockchain adoption for disclosing the quality information of generic drugs that compete with original drugs in the market and proposes legal measures accordingly. Methods: We employ a game-theoretic model to analyze a medicine supply chain including a generic drug manufacturer, an original drug manufacturer, and a retailer. We examine when should the supply chain members adopt blockchain for generic drugs and how blockchain affects the medicine supply chain. Results: Our results show that the quality information of generic drugs determines how blockchain adoption affects the price and sales quantity of generic and original drugs. Moreover, we observe that the generic drugs manufacturer and the retailer decide to adopt blockchain only if consumers' risk-aversion degree is sufficiently low. Also, a low risk-aversion degree can lead to higher whole supply chain's profitability with blockchain adoption, and generate a win-win-win situation of blockchain adoption for the consumers, the generic drug manufacturer, and the retailer. Conclusion: To mitigate consumers' risk aversion, the law should safeguard consumer rights. Blockchain adoption can benefit the medicine supply chain and consumers under certain conditions. However, it also requires the coordination of supply chain members' benefits and the disclosure of quality information.

Indexed as

blockchain adoptiongeneric drugmedicine supply chainquality uncertaintyrisk aversion

Identifiers

PMID38204929
PMCPMC10776887

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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.