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ABSTRACT. The purpose of this study is to examine augmented reality shopping experiences, retail business analytics, and machine vision algorithms in the virtual economy of the metaverse. In this article, we cumulate previous research findings indicating that visualization tools, sentiment analytics, and ambient scene detection can optimize customer engagement and journeys on livestreaming shopping platforms across online marketplaces. We contribute to the literature on connected data governance in the metaverse economy by showing that visualization tools, sentiment analytics, and ambient scene detection can optimize customer engagement and journeys on livestreaming shopping platforms across online marketplaces. Throughout February 2022, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “metaverse” + “augmented reality shopping experiences,” “retail business analytics,” “machine vision algorithms,” and “virtual economy.” As we inspected research published between 2021 and 2022, only 71 articles satisfied the eligibility criteria. By removing controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 16, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, MMAT, and SRDR.
JEL codes: D53; E22; E32; E44; G01; G41

Keywords: virtual economy; metaverse; machine vision; retail business analytics

How to cite: Popescu, G. H., Valaskova, K., and Horak, J. (2022). “Augmented Reality Shopping Experiences, Retail Business Analytics, and Machine Vision Algorithms in the Virtual Economy of the Metaverse,” Journal of Self-Governance and Management Economics 10(2): 67–81. doi: 10.22381/jsme10220225.

Received 25 February 2022 • Received in revised form 21 June 2022
Accepted 26 June 2022 • Available online 30 June 2022

1The Center for Applied Macroeconomic Analysis at AAER, New York, NY, USA; Dimitrie Cantemir Christian University, Bucharest, Romania, This email address is being protected from spambots. You need JavaScript enabled to view it. (corresponding author).
2Faculty of Operation and Economics of Transport and Communications, Department of Economics, University of Zilina, Zilina, Slovak Republic, This email address is being protected from spambots. You need JavaScript enabled to view it..
3The School of Expertness and Valuation, The Institute of Technology and Business in Ceske Budejovice, Czech Republic, This email address is being protected from spambots. You need JavaScript enabled to view it..

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