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Conference object . 2018
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Article . 2018
Data sources: Datacite
ZENODO
Article . 2018
Data sources: Datacite
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THE USE OF BLOCK TECHNOLOGIES IN SUPPLY CHAIN MANAGEMENT AND LOGISTIC INDUSTRY

Authors: Yotsov, Ivo; Kalinova, Zhaneta; Koritarov, Todor;

THE USE OF BLOCK TECHNOLOGIES IN SUPPLY CHAIN MANAGEMENT AND LOGISTIC INDUSTRY

Abstract

Today's supply chain management covers all links in ever more globalized and fragmented production and distribution. Depending on the product, the supply chain can consist of hundreds of stages with a wide geographic distribution, multiple invoices and payments, diferent individuals and companies involved in them. Despite the existence of multiple management systems, this complexity leads to a lack of transparency. This determines the interest in how blockchain technology can transform the supply chain and change the logistics industry. Blochain is a distributed public consensus system that maintains a continuous record of network transactions that are unable to be changed after the recording. With these features blockchain, in practice provides consensus by ensuring transparency. There would be no disputes about transactions in the chain because all entities have the same version of the book, and anyone in the blockchain can see the property chain for a particular asset. This ensures transparency and trust in a supply chain. Better visibility in orders, more accurate and reliable data needed for analysis and greater confidence among all actors in the supply chain are the key benefits of using blockchain technology.

Related Organizations
Keywords

Blockchain, supply chain, supply chain management

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green