Exploring real estate blockchain adoption: An empirical study based on an integrated task-technology fit and...

Area of Science:

• Information Systems
• Real Estate Technology
• Technology Adoption Models

Background:

• Blockchain technology (BCT) adoption is crucial for businesses, yet factors influencing its use in the real estate sector remain under-researched.
• Existing studies have not sufficiently explored the specific drivers for BCT implementation within real estate transactions.

Purpose of the Study:

• To investigate the key factors influencing the adoption of blockchain technology in the real estate sector.
• To extend the Technology Acceptance Model (TAM) with Task-Technology Fit (TTF) to understand BCT adoption dynamics.

Main Methods:

• A quantitative survey approach was employed, collecting data from 311 real estate buyers and sellers in China.
• Partial Least Square Structural Equation Modeling (PLS-SEM) was utilized for data analysis to test the proposed theoretical model.

Main Results:

• Attitude, perceived usefulness (PU), and data privacy and security (DPS) were found to be the most influential factors in BCT adoption.
• Perceived ease of use (PEOU) significantly impacts attitude, while TTF influences both PU and PEOU.
• Perceived compatibility (PC) was confirmed to moderate the relationship between TTF and PEOU.

Conclusions:

• Blockchain technology adoption in real estate is positively influenced by user attitudes, perceived benefits, and robust security measures.
• Ease of use and the fit between tasks and technology are critical for fostering acceptance and driving adoption.
• Implementing BCT in real estate can enhance efficiency, reduce intermediary costs, improve security, and streamline processes like title transfers.