Market Preferences of Different Operators of Long-Term Rental Apartments in a Fuzzy Environment
Author(s): |
Guangxia Zhou
Changyou Li Jiapeng Wang Jingyan Wu |
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Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 23 May 2023, n. 6, v. 13 |
Page(s): | 1418 |
DOI: | 10.3390/buildings13061418 |
Abstract: |
The long-term rental apartment market in China is steadily growing to be a trillion-dollar sector, but excessive market growth can lead to several issues. Due to the high demand for long-term rentals, many investors will enter the market. Nevertheless, without direction and supervision, it is simple to overdevelop the supply of long-term rentals, which would have negative effects on the real estate market. Long-term rental apartments involve a variety of companies, and it is vital that we drive their beneficial growth. To provide other operators with a comparison to find flaws, enhance improvements, and prevent irrationally increasing the stock, this paper uses the Pythagorean fuzzy decision-making method to identify the most well-liked long-term rental apartment operators and the most significant rental needs of tenants in the market environment. The results of the study show that real estate developers’ flats are the most popular among the four major operators, and that C4: Providing emotional value, C7: Ability to resist risk and C8: Ability to prevent social incidents are aspects that tenants value more than others. The results of the study provide real estate operators with directions for optimization, provide other operators with criteria for improvement, prevent blind increases in rental stock and provide operators with a healthy competitive environment, which is of great significance to the healthy development of long-term rental apartments in China. |
Copyright: | © 2023 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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data sheet - Reference-ID
10731808 - Published on:
21/06/2023 - Last updated on:
07/08/2023