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p-Index From 2021 - 2026
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This Author published in this journals
All Journal Journal of Management and Informatics International Journal of Graphic Design
Na, Im Ha
Unknown Affiliation
Arts Computer Science & IT Decision Sciences, Operations Research & Management

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Ethical AI in the Metaverse: A Mixed-Methods Study on Design Innovation, Social Implications, and Fairness Challenges In-Hwa, Kim; Song-Il, Park; Na, Im Ha; Young, Kim Ahn; Chul, Kim Young
International Journal of Graphic Design Vol. 3 No. 1 (2025): May | IJGD: International Journal of Graphic Design
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/ijgd.v3i1.2791

Abstract

The rapid evolution of the metaverse has transformed virtual environments into dynamic and immersive spaces, with Artificial Intelligence (AI) playing a pivotal role in this transformation. However, despite AI’s contributions to design innovation, significant concerns remain regarding ethical, social, and technical challenges. This study aims to comprehensively analyze the role of AI in enhancing design innovations within the metaverse, while addressing issues of algorithmic bias, data privacy, and social inclusivity. Employing a mixed-methods approach, the research combines quantitative analysis of over 500,000 user interaction datasets from leading metaverse platforms—Decentraland, Roblox, and Meta Horizon—with qualitative insights from semi-structured interviews involving AI developers and UX/UI designers. Statistical analyses, including regression and clustering techniques, alongside thematic analysis, reveal that AI significantly enhances user engagement by improving avatar personalization and adaptive virtual environments. However, findings also highlight persistent risks such as biased algorithmic decisions, lack of transparency, and privacy vulnerabilities, which may hinder equitable participation in virtual spaces. The study further proposes and implements an AI model grounded in Human-Computer Interaction principles and fairness-aware machine learning to mitigate these issues. Results demonstrate improved user satisfaction, inclusivity, and social interaction quality. This research offers critical implications for developers, policymakers, and stakeholders, emphasizing the need for ethical AI governance and inclusive design frameworks in metaverse ecosystems. By bridging technological advancements with social responsibility, the study contributes to the development of a sustainable and equitable metaverse future.
Personalized Digital Marketing Strategies: A Data-Driven Approach Using Marketing Analytics Na, Im Ha; Jae, Yoo In; Hwa, Park In
Journal of Management and Informatics Vol. 4 No. 1 (2025): April Season | JMI: Journal of Management and Informatics
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jmi.v4i1.149

Abstract

The rapid development of digital technology has transformed marketing strategies, enabling companies to leverage big data analytics to enhance personalized marketing approaches. With the increasing volume of customer interaction data collected from various digital platforms, businesses can now gain deeper insights into consumer preferences and behaviors. This study aims to analyze the impact of big data analytics on personalized digital marketing and evaluate the role of data visualization in improving decision-making processes. The research employs an exploratory approach by analyzing secondary data from multiple digital sources, including e-commerce platforms, social media, and company websites. The study applies data-driven segmentation models and machine learning-based predictive analytics to assess customer engagement and conversion rates. The findings reveal that implementing big data analytics leads to a 48.57% increase in customer engagement and a 132% improvement in conversion rates compared to traditional marketing methods. Furthermore, the integration of data visualization techniques enables marketers to interpret complex consumer patterns effectively, contributing to a 46.67% rise in average transaction value per customer. These results indicate that data-driven personalization significantly enhances marketing effectiveness and customer loyalty. This research contributes to the field by providing empirical evidence on the advantages of utilizing big data analytics in digital marketing and highlighting the importance of interactive dashboards for real-time customer trend analysis. Future research is encouraged to explore the automation of personalized marketing through machine learning algorithms and the optimization of real-time data-driven strategies.
Co-Authors Chul, Kim Young Hwa, Park In In-Hwa, Kim Jae, Yoo In Song-Il, Park Young, Kim Ahn