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ABSTRACT. The purpose of this study is to examine live shopping in the metaverse in terms of visual and spatial analytics, cognitive artificial intelligence techniques and algorithms, and immersive digital simulations. In this article, we cumulate previous research findings indicating that retail analytics can build brand awareness and improve operational performance across shared virtual environments by customizing user experiences. We contribute to the literature on retail business models in the metaverse environment by showing that cognitive artificial intelligence techniques and algorithms can be pivotal in virtual commerce by enhancing digital shopping experience through location data. Throughout March 2022, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “metaverse” + “live shopping,” “visual analytics,” “spatial analytics,” “cognitive artificial intelligence techniques and algorithms,” and “immersive digital simulations.” As we inspected research published between 2021 and 2022, only 89 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 20, 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.

Keywords: shopping; metaverse; visual; spatial; analytics; immersive

How to cite: Kliestik, T., Novak, A., and Lăzăroiu, G. (2022). “Live Shopping in the Metaverse: Visual and Spatial Analytics, Cognitive Artificial Intelligence Techniques and Algorithms, and Immersive Digital Simulations,” Linguistic and Philosophical Investigations 21: 187–202. doi: 10.22381/lpi21202212.

Received 26 March 2022 • Received in revised form 21 May 2022
Accepted 25 May 2022 • Available online 30 May 2022

1Faculty 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..
1Faculty 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..
2The Institute of Smart Big Data Analytics, New York, NY, USA; Spiru Haret University, Bucharest, Romania, This email address is being protected from spambots. You need JavaScript enabled to view it. (corresponding author).

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