Visual and Spatial Analytics, Immersive Virtual Simulation Technologies, and Motion Planning and Object Recognition Algorithms in the Retail Metaverse.

• Author: Valaskova, Katarina

1. Introduction

   Lifetime customer value and immersive retail experiences in relation to blockchain token-based digital assets can be attained by use of data-driven artificial intelligence, virtual navigation tools, and sentiment analytics. The purpose of our systematic review is to examine the recently published literature on the retail metaverse and integrate the insights it configures on visual and spatial analytics, immersive virtual simulation technologies, and motion planning and object recognition algorithms. By analyzing the most recent (2022) and significant (Web of Science, Scopus, and ProQuest) sources, our paper has attempted to prove that analytical artificial intelligence, contextual consumer data, and sentiment analytics enable personalized digital shopping and immersive retail experiences across virtual marketplaces. The actuality and novelty of this study are articulated by addressing metaverse engagement and experiences in virtual retail environments, that is an emerging topic involving much interest. Our research problem is whether Business intelligence tools, visual analytics, and digital machines can determine consumer behavior and engagement in retail livestreaming across virtual environments.

   In this review, prior findings have been cumulated indicating that predictive customer analytics, natural language processing algorithms, and simulation modeling tools are instrumental in virtual shopping sessions in extended reality environments. The identified gaps advance metaverse live shopping in virtual retail stores. Our main objective is to indicate that predictive technology can drive revenue and boost user retention and continuance intention by use of historical and contextual data. This systematic review contributes to the literature on digitized retail products and entertaining metaverse events in immersive hyper-connected virtual spaces by clarifying that brands can leverage the metaverse as a virtual retail destination by use of data visualization and augmented reality shopping tools, spatial analytics, and customer biometric data. This research endeavors to elucidate whether immersive retail experiences as regards consumer sentiment and behavior can be achieved through transaction geolocation data, cognitive artificial intelligence algorithms, and social commerce tools. Our contribution is by integrating research findings indicating that picture-making neural networks, real-time data visualization tools, and biometric authentication features shape virtual consumer engagement and user experiences and behaviors across interconnected digital realms.

2. Theoretical Overview of the Main Concepts

   Customer experience analytics requires haptic and biometric sensor technologies, conversational artificial intelligence, and machine learning-based product recognition across immersive virtual environments and decentralized 3D digital worlds. Predictive technology can drive revenue and boost user retention and continuance intention by use of historical and contextual data. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), metaverse engagement and experiences in virtual retail environments (section 4), consumer digital engagement throughout metaverse live shopping in virtual retail stores (section 5), digitized retail products and entertaining metaverse events in immersive hyper-connected virtual spaces (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 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." 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 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 (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. Metaverse Engagement and Experiences in Virtual Retail Environments

   Metaverse adoption can shift consumer and business behaviors, enabling virtual products and services while building long-term competitive advantages and real-time immersive interactivity (Almarzouqi et al. 2022; Beniiche et al., 2022; Chandra, 2022; Wang et al., 2022; Xi et al., 2022) through decentralization and interoperability across compute infrastructure. Predictive technology can drive revenue and boost user retention and continuance intention by use of historical and contextual data.

   Data sharing technologies, customer predictive analytics, and augmented reality shopping tools configure 3D metaverse experiences during retail live-streaming (Bibri and Allam, 2022; Elawady et al., 2022; Guo and Gao, 2022; Hwang and Chien, 2022; Upadhyay and Khandelwal, 2022; Wang, 2022), creating engaging brand awareness across immersive 3D worlds. Immersive retail experiences as regards consumer sentiment and behavior can be achieved through transaction geolocation data, cognitive artificial intelligence algorithms, and social commerce tools.

   Artificial intelligence chatbot customer service, social commerce capabilities, and business intelligence tools (Akour et al., 2022; Carey, 2022; Deveci et al., 2022; Reis and Ashmore, 2022; Turner, 2022; Yeh et al., 2022) articulate metaverse engagement and experiences in virtual retail environments. Visual capabilities and biometric analytics can increase customer loyalty, shopper engagement, and brand awareness through customer data during digital shopping journey. Business intelligence tools, visual analytics, and digital machines can determine consumer behavior and engagement in retail livestreaming across virtual environments. (Table 3)

5. Consumer Digital Engagement throughout Metaverse Live Shopping in Virtual Retail Stores

   Simulation modeling tools, behavioral and demographic analytics, and computer vision algorithms (Arpaci et al., 2022; Deng et al., 2022; Frajtova Michalikova et al., 2022; Kraus et al., 2022; Park et al., 2022; Zhao et al., 2022) assist immersive 3D technologies in the retail metaverse, driving brand awareness. Livestreaming e-commerce can leverage precision marketing tools as regards virtual assets by harnessing customer data, thus optimizing shopping patterns in terms of convenience, engagement, satisfaction, loyalty, sentiments, preferences, and behaviors.

   Visual analytics, predictive modeling tools, and biometrics data fusion optimize consumer digital engagement (Akyildiz et al., 2022; Kozinets, 2022; Li et al., 2022; Popescu Ljungholm, 2022; Tlili et al., 2022; Zvarikova et al., 2022a, b) throughout metaverse live shopping in...