Managing Metaverse Marketing Challenges Considering Service Quality Model: Application of Intuitionistic Fuzzy Decision Support System

This study aims to explore the application of advanced decision-making frameworks for identifying and prioritizing marketing challenges in the Metaverse, with a focus on the real estate sector. It examines the integration of innovative methodologies to enhance service quality and customer experience within virtual environments. The research adopts a novel ARAS-FUCOM-SERVQUAL methodology to systematically evaluate and rank Metaverse marketing challenges. Data were collected from a cohort of international real estate agents using intuitionistic triangular fuzzy numbers to assess SERVQUAL (Service Quality) dimensions. The study employs multi-criteria decision-making (MCDM) techniques to analyze and validate the collected data, ensuring robust prioritization of the challenges. The findings reveal ten critical marketing challenges in the Metaverse, including interoperability, data privacy, customer engagement, and regulatory complexities. The results demonstrate the effectiveness of the ARAS-FUCOM-SERVQUAL framework in providing actionable insights for strategic planning and resource allocation. Key managerial recommendations are proposed to address these challenges and optimize marketing strategies in virtual environments. This research introduces an innovative combination of the Additive Ratio Assessment System (ARAS) and the Full Consistency Method (FUCOM) with SERVQUAL dimensions, tailored to the Metaverse context. It highlights the potential of these methodologies to bridge the gap between traditional service quality assessments and the evolving requirements of marketing in virtual environments. The study offers a comprehensive framework for addressing the complexities of Metaverse marketing, particularly in the dynamic real estate industry.