Innovating the Real Estate Economy: Data-Driven Development Models for a New Cycle

Xiangdong Feng ()
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Xiangdong Feng: University of British Columbia

A chapter in Proceedings of the 2025 7th International Conference on Economic Management and Cultural Industry (ICEMCI 2025), 2025, pp 290-297 from Springer

Abstract: Abstract Real estate isn’t just about providing homes—it’s also a major driver of the economy, influencing jobs, finance, and even our ability to adapt to climate change. After more than ten years of low interest rates, the industry is now facing tougher challenges: housing is becoming less affordable, building costs are climbing, and there’s growing pressure to cut carbon emissions. Innovation is no longer optional—it’s essential. In this essay, I bring together the latest data and research to explore five promising ways the sector can adapt: building homes through industrialized, off-site methods; expanding build-to-rent (BTR) developments; using green finance to fund energy-saving upgrades; capturing land value through transit-oriented development (TOD); and embracing digital tools like AI, machine learning, and asset tokenization. For each approach, I explain the economic models used to assess them, run sample calculations to show their impact, and suggest practical steps for putting them into action.

Keywords: Real Estate; Innovation; Digital Tools; Economic Models; Real Estate Economy (search for similar items in EconPapers)
Date: 2025
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DOI: 10.2991/978-94-6463-888-2_29

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