Drawing from existing literature on virtual worlds and brand experience, this study investigates the complex and dynamic landscape of brand experiences in branded virtual worlds. Unlike prior research adopting the standard brand experience dimensions designed for the physical context or relying on platform characteristics and perceived value as the brand experience, this study used a qualitative approach to uncover brand experience dimensions specific to this context. Using a critical incident technique on a sample of 120 respondents, we discovered six dimensions: Sensory, Affective, Intellectual, Behavioral, Social, and Empowering, each with its own set of components. These fifteen components, including sensory coherence, negative and complex emotions, physical control, real-world actions, consumption empowerment, and lifestyle exploration, offer implications for designing branded virtual worlds that improve consumer engagement and brand outcomes in both the virtual and real worlds.
The Industrial Metaverse concept posits real-time coordination across distributed operations, yet the infrastructure specifications required to deliver operational value remain unquantified. We introduce the Coordination-Aware Disruption Twin (CADT), an agent-based simulation frame-work that isolates the effects of visibility scope, synchronization latency, and data fidelity. Through a full factorial experiment and baseline comparisons (1,440 runs across two topologies), we demonstrate that Metaverse-grade coordination, when paired with visibility-aware ordering (VAOH), re-duces cumulative backlog by 85.3% relative to the best-performing baseline. Traditional dashboards, which offer identical visibility but higher latency, achieve a 47% reduction. A key finding is that latency explains 67.6% of performance variance (η2 = 0.676), while sensor noise explains effectively none (η2 < 0.001, p > 0.05). A noisy real-time Meta-verse (σ = 0.2) outperforms a perfect-fidelity but delayed dashboard. These results suggest that for sup-ply chain resilience, the Metaverse’s primary value lies not in visualization fidelity but in the speed of state synchronization, serving as a low-latency control plane for distributed decision-making.
As scholarly publishing navigates the rapid integration of artificial intelligence (AI), encompassing generative AI, natural language processing (NLP), large language models (LLMs), and autonomous agents, the editorial ecosystem must adapt to maintain its core integrity. This editorial evaluates the operational advantages of AI, such as enhanced efficiency and automated integrity checks, against systemic risks, including hallucination, bias, and confidentiality breaches. Drawing on recent empirical validations and policy frameworks from the Committee on Publication Ethics (COPE), the International Committee of Medical Journal Editors (ICMJE), and major publishers, we outline a comprehensive editorial policy for the Journal of Metaverse. This policy emphasizes human oversight, transparency, and domain-specific rigor. We also introduce practical implementation mechanisms, including an AI-use disclosure template, auditing protocols, and specific reporting requirements for metaverse research. Furthermore, this editorial explores the strategic use of generative AI for post-publication science communication, demonstrating how automated infographics and multimedia summaries can significantly enhance research visibility and broad accessibility. This document serves as both a functional policy framework and a contribution to the discourse on responsible AI integration in academic publishing.
This Accurate prediction of exchange rates is of critical importance for economic policy related decision making. This study employs a deep learning based framework to model exchange rate dynamics by explicitly accounting for the inherently nonlinear, and regime sensitive nature of financial time series. Unlike traditional artificial neural network approaches that overlook temporal dependencies, recurrent neural network architectures are capable of directly modeling long term time dependencies. Accordingly, this study applies Long Short Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Gated Recurrent Unit (GRU) models to predict the USD/TRY and EUR/TRY exchange rate series. The empirical analysis is conducted using data from the Turkish economy across three distinct subperiods, representing a relatively stable regime and two high-volatility regimes. Hyperparameters are independently optimized for each model and regime with grid search. Predictive performance is evaluated using Mean Absolute Error, Root Mean Squared Error, and Mean Absolute Percentage Error, with Diebold Mariano tests confirming statistical significance and formal benchmark comparisons against ARIMA and random walk models. Results indicate that no single architecture dominates across all conditions: GRU consistently outperforms competitors during the Crisis period for both exchange rates, while LSTM and BiLSTM perform best during COVID19 for USD/TRY, and GRU maintains its advantage for EUR/TRY. Diebold Mariano tests confirm that 89% of pairwise performance differences are statistically significant. Robustness analysis using lag-3 specifications supports that regime-dependent patterns are not artifacts of input structure. By incorporating volatility regimes, statistical testing, and econometric benchmarks, this study demonstrates the practical importance of regime-aware model selection for exchange rate forecasting in emerging market economies.
In the metaverse era, the rapid convergence of physical and digitally mediated environments is reshaping how reality is perceived and constructed. This study revisits the concept of reality through major philosophical theories to examine the relationship between the digital self and the physical self in metaverse contexts. Using Plato’s theory of forms, Descartes’ mind–body dualism, Kant’s transcendental idealism, and Baudrillard’s simulation theory as analytical lenses, it shows how “the real” becomes a multilayered construct in the digital age. Methodologically, the article adopts a structured narrative review and a theory-driven qualitative synthesis of scholarly works, integrating foundational philosophical texts with contemporary research on digital culture and metaverse technologies. The synthesis foregrounds themes of digital identity, virtual selfhood, and algorithmic representation to clarify how digitally mediated environments reconfigure experiences of reality. The findings indicate that the digital self is no longer merely representational but functions as an ontological dimension of existence alongside the physical self. The study concludes that metaverse-enabled digital realities challenge inherited assumptions about reality, prompting renewed philosophical inquiry into identity, being, and truth.
