Sales Trends and Price Determinants in the Virtual Property Market: Insights from Blockchain-Based Platforms - Akhila Reddy Yadulla; Mohan Harish Maturi; Karthik Meduri; Geeta Sandeep Nadella (International Journal Research on Metaverse, 2024)
The virtual property market, driven by blockchain-based platforms like Decentraland, Cryptovoxels, and The Sandbox, parallels the physical real estate market. This study analyzes sales trends and identifies key factors influencing property prices in Decentraland, covering over 10,000 transactions from January 2020 to December 2023. Objectives include examining daily, weekly, and monthly sales trends, analyzing price distributions by property type, and exploring correlations between property prices, Mana cryptocurrency, and land prices. Daily sales fluctuated significantly, with peak days reaching up to 150 transactions and off-peak days as low as 10. Weekly sales trends indicated cyclical patterns, with notable peaks every four to six weeks, while monthly trends showed a 5% average growth rate. Price distribution analysis revealed parcels ranged from 1,000 to 50,000 Mana (mean: 15,000 Mana), and roads ranged from 500 to 20,000 Mana (mean: 8,000 Mana). A very strong positive correlation (r = 0.99) was found between property prices and land prices, indicating land prices are a significant determinant of property values. Conversely, the correlation between property prices and Mana prices was weak (r = -0.05), suggesting limited direct influence of cryptocurrency volatility on property values. Traditional real estate markets are influenced by factors like location and property characteristics, while virtual property markets are significantly affected by digital factors such as cryptocurrency prices and virtual locations. The integration of virtual reality (VR) and augmented reality (AR) technologies in real estate has transformed property presentation and buyer engagement, enhancing decision-making. Digital tools like Google Trends have proven useful in predicting market trends. This study addresses the gap in understanding digital influences on virtual property values, providing insights for investors, developers, and policymakers. The methodology includes data collection, preprocessing, and analysis using advanced statistical and machine learning tools, offering a comprehensive understanding of Decentraland's virtual property market to aid informed decision-making.