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Biometric Sensor Technologies, Visual Imagery and Predictive Modeling Tools, and Ambient Sound Recognition Software in the Economic Infrastructure of the Metaverse

Biometric Sensor Technologies, Visual Imagery and Predictive Modeling Tools, and Ambient Sound... We draw on a substantial body of theoretical and empirical research on metaverse assets and services in interactive virtual environments. In this research, prior findings were cumulated indicating that predictive and retail analytics and data sharing technologies optimize consumer purchase behaviors. We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout April 2022, with search terms including “the economic infrastructure of the metaverse” + “biometric sensor technologies,” “visual imagery and predictive modeling tools,” and “ambient sound recognition software.” As we analyzed research published in 2021 and 2022, only 141 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 25, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, ROBIS, and SRDR. Keywords: customer predictive analytics; geolocation data; immersive technologies; metaverse commerce; ambient sound recognition software; biometric sensor technologies http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Contemporary Philosophy Addleton Academic Publishers

Biometric Sensor Technologies, Visual Imagery and Predictive Modeling Tools, and Ambient Sound Recognition Software in the Economic Infrastructure of the Metaverse

Tomas Kliestik
Review of Contemporary Philosophy , Volume 21 (1): 17 – Jan 1, 2022
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Publisher
Addleton Academic Publishers
Copyright
© 2009 Addleton Academic Publishers
ISSN
1841-5261
eISSN
2471-089X
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Abstract

We draw on a substantial body of theoretical and empirical research on metaverse assets and services in interactive virtual environments. In this research, prior findings were cumulated indicating that predictive and retail analytics and data sharing technologies optimize consumer purchase behaviors. We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout April 2022, with search terms including “the economic infrastructure of the metaverse” + “biometric sensor technologies,” “visual imagery and predictive modeling tools,” and “ambient sound recognition software.” As we analyzed research published in 2021 and 2022, only 141 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 25, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, ROBIS, and SRDR. Keywords: customer predictive analytics; geolocation data; immersive technologies; metaverse commerce; ambient sound recognition software; biometric sensor technologies

Journal

Review of Contemporary Philosophy – Addleton Academic Publishers

Published: Jan 1, 2022

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