Multi-Sensor Fusion Technology, Visual Imagery and Predictive Modeling Tools, and Big Geospatial Data Analytics in the Virtual Economy of the Metaverse.

AuthorDuncan, George
  1. Introduction

    Real-time and historical user movements, network analytics visualizations, search engine algorithms, and contextual augmented reality can improve customer engagement and spending across online retail in decentralized commerce spaces. The purpose of my systematic review is to examine the recently published literature on the virtual economy of the metaverse, and integrate the insights it configures on multi-sensor fusion technology, visual imagery and predictive modeling tools, and big geospatial data analytics. By analyzing the most recent (2022) and significant (Web of Science, Scopus, and ProQuest) sources, my paper has attempted to prove that retail analytics can determine purchase intentions, shopping habits, and virtual consumer engagement by use of location data. The actuality and novelty of this study are articulated by addressing customer behavior analytics and engagement tools building customer engagement across immersive virtual environments, that is an emerging topic involving much interest. My research problem is whether decision and behavior visualization can optimize data mining, processing, and modeling, enhancing shopping experiences by capturing consumer data.

    In this review, prior findings have been cumulated indicating that biometric analytics enables personalized shopping experiences in 3D immersive environments by determining customer habits as regards digital assets through synthetic data. The identified gaps advance immersive retail experiences achieved by use of metaverse capabilities and augmented reality shopping tools. My main objective is to indicate that retail brands can deploy analytical artificial intelligence in experiential shopping, thus improving online buying experiences across interactive digital worlds. This systematic review contributes to the literature on consumer sentiment and behavior and purchase intentions in the retail metaverse by clarifying that predictive analytics and data visualizations can improve customer satisfaction throughout connected shopping experiences in terms of 3D immersive content. This research endeavors to elucidate whether retail business analytics can optimize interconnected experiences in immersive virtual worlds by deploying consumer data to determine shopping behaviors and purchasing habits. My contribution is by integrating research findings indicating that consumer analytics and data visualizations can be deployed in retail livestreaming and digital shopping across immersive 3D worlds, driving brand engagement and predicting user behaviors.

  2. Theoretical Overview of the Main Concepts

    Connected shopping experiences in immersive 3D worlds as regards virtual items require data-driven decisions that can assess consumer purchasing habits and retail buying behavior. Speech and sentiment analytics, eyetracking technologies, and logistics intelligence can optimize immersive experiences as regards virtual asset purchasing by assessing behavioral patterns. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), digital user engagement across metaverse worlds (section 4), frictionless customer experiences during live shopping events and in metaverse-related businesses (section 5), consumer sentiment and behavior and purchase intentions in the retail metaverse (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10).

  3. Methodology

    Throughout April 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including "metaverse" + "multi-sensor fusion technology," "visual imagery and predictive modeling tools," and "big geospatial data analytics." The search terms were determined as being the most employed words or phrases across the analyzed literature. As research published in 2022 was inspected, only 173 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, I selected 29 mainly empirical sources (Tables 1 and 2). 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. Extracting and inspecting publicly accessible files (scholarly sources) as evidence, before the research began no institutional ethics approval was required (Figures 1-6).

  4. Digital User Engagement across Metaverse Worlds

    Retail brands can enhance customer experience through metaverse capabilities during live e-commerce shopping (Bibri et al., 2022; Dozio et al., 2022; Hamilton, 2022) across immersive virtual spaces and digital environments. Real-time and historical user movements, network analytics visualizations, search engine algorithms, and contextual augmented reality can improve customer engagement and spending across online retail in decentralized commerce spaces. Speech and sentiment analytics, eye-tracking technologies, and logistics intelligence can optimize immersive experiences as regards virtual asset purchasing by assessing behavioral patterns.

    Artificial intelligence-driven predictive analytics can use detailed customer profiles during virtual shopping sessions, and, through extensive testing and planning (Belk et al., 2022; Jenkins, 2022; Gordon, 2022), can enhance digital user engagement across metaverse worlds. A decentralized infrastructure deploying incessant interconnected data streams can assist retail brands in collecting advanced haptic feedback during visual merchandising by monitoring consumer sentiment and behavior. Retail analytics can determine purchase intentions...

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