Economics, Management, and Financial Markets

Maria Kovacova

2022 Economics, Management, and Financial Markets

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The objective of this paper is to systematically review metaverse customer engagement and virtual retail experiences. The findings and analyses highlight that augmented reality shopping tools articulate immersive and engaging content and multisensory customer experiences across interconnected virtual worlds. Throughout April 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “metaverse commerce” + “digital twin simulation and modeling tools,” “deep learning object detection technology,” and “visual perception and sensor fusion algorithms.” As research published in 2022 was inspected, only 178 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 38 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR. JEL codes: D53; E22; E32; E44; G01; G41 Keywords: digital twin; simulation; modeling; deep learning; object detection; visual perception; sensor fusion; metaverse commerce

Mark Newell

2022 Economics, Management, and Financial Markets

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The aim of this systematic review is to synthesize and analyze immersive virtual shopping and metaverse brand experiences. With increasing evidence of metaverse technologies integrating cognitive computing systems and virtual retail algorithms, there is an essential demand for comprehending whether Customer predictive analytics leverages machine learning-based product recognition tools, picture-making neural networks, and cognitive artificial intelligence algorithms across interconnected digital realms and immersive virtual spaces. In this research, prior findings were cumulated indicating that immersive shopping experiences can be achieved through sensory data mining techniques and machine vision algorithms in the virtual retail market. I carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout May 2022, with search terms including “metaverse economy” + “customer engagement and data visualization tools,” “ambient sound recognition software,” and “deep learning-based sensing technologies.” As I analyzed research published between 2021 and 2022, only 214 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, I decided on 51, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Distiller SR, ROBIS, and SRDR. JEL codes: D53; E22; E32; E44; G01; G41 Keywords: customer engagement; data visualization; ambient sound recognition; deep learning; sensing technologies; metaverse economy

Katarina Valaskova

2022 Economics, Management, and Financial Markets

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Based on an in-depth survey of the literature, the purpose of the paper is to explore metaverse engagement and experiences in virtual retail environments. In this research, previous findings were cumulated showing that business intelligence tools, visual analytics, and digital machines can determine consumer behavior and engagement in retail livestreaming across virtual environments, and we contribute to the literature by indicating that predictive customer analytics, natural language processing algorithms, and simulation modeling tools are instrumental in virtual shopping sessions in extended reality environments. Throughout June 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “retail metaverse” + “visual and spatial analytics,” “immersive virtual simulation technologies,” and “motion planning and object recognition algorithms.” As research published in 2022 was inspected, only 223 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 53 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR. JEL codes: D53; E22; E32; E44; G01; G41 Keywords: visual and spatial analytics; immersive virtual simulation; motion planning; object recognition; retail metaverse