Business model innovation in real estate: Applying the business model navigator to conventional and Tokenised models

https://doi.org/10.55214/25768484.v8i6.2737

Authors

  • Galindo-Reyes Fuensanta Departamento de Economía y Administración de Empresas. Facultad de Marketing y Gestión. Universidad de Málaga, Spain
  • De la Varga-Salto José María Departamento de Economía y Administración de Empresas. Facultad de Marketing y Gestión. Universidad de Málaga, Spain

This study explores the application of the Business Model Navigator framework to enhance business models within the real estate sector, particularly in response to recent technological advancements and shifting market dynamics. By analyzing two case studies—a traditional luxury property developer and a blockchain-based tokenisation platform—the research demonstrates how selected BMN patterns can drive value creation, improve operational efficiency, and enhance scalability. The traditional luxury real estate model, while excelling in delivering high-end properties and tailored customer experiences, faces significant scalability challenges due to its capital-intensive nature. In contrast, the blockchain-based tokenised model offers improved liquidity and broader market accessibility by enabling fractional ownership, though it encounters obstacles related to regulatory compliance and market acceptance of blockchain technology. This research concludes that both models can significantly benefit from the strategic incorporation of BMN patterns, which enhance adaptability and competitiveness in an evolving real estate landscape. The findings offer strategic recommendations for both traditional and innovative real estate companies seeking to optimise their business models through the use of BMN patterns.

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How to Cite

Fuensanta, G.-R. ., & María, D. la V.-S. J. . (2024). Business model innovation in real estate: Applying the business model navigator to conventional and Tokenised models. Edelweiss Applied Science and Technology, 8(6), 3465–3474. https://doi.org/10.55214/25768484.v8i6.2737

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Published

2024-10-31