Explore the Factors Affecting the Housing Prices in Wuhan
- DOI
- 10.2991/978-94-6463-811-0_59How to use a DOI?
- Keywords
- Wuhan Real Estate; Big Data Analysis; Housing Price Forecast; Multiple And Linear Regression
- Abstract
In recent years, China’s economy has continued to grow and the urbanization process is accelerating. The real estate market is also of great significance to promoting social stability and improving people’s quality of life. Based on the perspective of big data in this paper, a multiple linear regression model is used to analyse the development of the Wuhan real estate market. The main factors affecting housing prices and their operating mechanisms are discussed by analysing the trend of actual housing prices from 2010 to 2022 and combining them with key factors such as economic indicators, land supply, and housing sales. The study found that the housing price in Wuhan has experienced a process from the initial slow growth in 2010 to the rapid rise in the middle term and then to the recent decline and stabilisation. House prices are expected to remain stable in the next few years. This paper’s research results can help understand the operation law of the Wuhan real estate market.
- 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 - Jiahe Bao PY - 2025 DA - 2025/08/14 TI - Explore the Factors Affecting the Housing Prices in Wuhan BT - Proceedings of the 2025 5th International Conference on Enterprise Management and Economic Development (ICEMED 2025) PB - Atlantis Press SP - 568 EP - 576 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-811-0_59 DO - 10.2991/978-94-6463-811-0_59 ID - Bao2025 ER -