Innovating the Real Estate Economy: Data-Driven Development Models for a New Cycle
- DOI
- 10.2991/978-94-6463-888-2_29How to use a DOI?
- Keywords
- Real Estate; Innovation; Digital Tools; Economic Models; Real Estate Economy
- 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.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Xiangdong Feng PY - 2025 DA - 2025/12/03 TI - Innovating the Real Estate Economy: Data-Driven Development Models for a New Cycle BT - Proceedings of the 2025 7th International Conference on Economic Management and Cultural Industry (ICEMCI 2025) PB - Atlantis Press SP - 290 EP - 297 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-888-2_29 DO - 10.2991/978-94-6463-888-2_29 ID - Feng2025 ER -