Behavioral Analytics, Immersive Technologies, and Machine Vision Algorithms in the Web3-powered Metaverse World
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F22%3A00002481" target="_blank" >RIV/75081431:_____/22:00002481 - isvavai.cz</a>
Result on the web
<a href="https://addletonacademicpublishers.com/contents-lpi/2445-volume-21-2022/4236-behavioral-analytics-immersive-technologies-and-machine-vision-algorithms-in-the-web3-powered-metaverse-world" target="_blank" >https://addletonacademicpublishers.com/contents-lpi/2445-volume-21-2022/4236-behavioral-analytics-immersive-technologies-and-machine-vision-algorithms-in-the-web3-powered-metaverse-world</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Behavioral Analytics, Immersive Technologies, and Machine Vision Algorithms in the Web3-powered Metaverse World
Original language description
The authors aim to determine whether, with the growing evidence of data tracking, management, measurement, optimization, and analysis in metaverse worlds, there is a fundamental requirement to understand whether live shopping-enabling technologies can improve customer engagement and satisfaction in immersive virtual and augmented reality-based environments.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
50200 - Economics and Business
Result continuities
Project
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Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Linguistic and Philosophical Investigations
ISSN
1841-2394
e-ISSN
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Volume of the periodical
21
Issue of the periodical within the volume
neuvedeno
Country of publishing house
US - UNITED STATES
Number of pages
16
Pages from-to
57-72
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85135607382