Chinese Residents’ Willingness to Buy Housing: An Evaluation in Nanyang City, Henan Province, China Based on the Extension Cloud Model
Autor(en): |
Yuan Feng
Maszuwita Abdul Wahab Nurul Afiqah Binti Azmi Hong Yan Han Wu |
---|---|
Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Buildings, 20 September 2022, n. 10, v. 12 |
Seite(n): | 1695 |
DOI: | 10.3390/buildings12101695 |
Abstrakt: |
Real estate has always been a key industry associated with China’s economic and social development, and the real estate market has fluctuated violently in recent years. An objective and accurate evaluation of Chinese residents’ willingness to purchase housing provides a foundation for the sustainable development of the real estate industry. Accordingly, an evaluation index system and an evaluation model of Chinese residents’ willingness to buy housing were established in this study. First, the influencing factors of Chinese residents’ willingness to buy housing were systematically analyzed using Perceived Value Theory. Subsequently, the Continuous Ordered Weighted Averaging was used to assign weights to the selected index system, with smaller expert weights assigned to extreme expert opinions to reduce the subjectivity of the weight calculation results. Ultimately, an evaluation model based on the Extension Cloud Model was constructed. Residents of Nanyang City, Henan Province, China, were selected to find some distinctive conclusions. The empirical study showed that Nanyang residents were hesitant about the purchase intention of the case in April 2021, but quickly became resolute in not buying. Owing to the abrupt change in the real estate industry in China, perceived risk has become the most important risk factor. Several methods have been suggested to improve Chinese residents’ willingness to buy housing. Compared with the Analytic Hierarchy Process, the Entropy Weight Method, the fuzzy mathematics, and the grey cluster analysis, it was proved that the proposed model was more effective and advanced. |
Copyright: | © 2022 by the authors; licensee MDPI, Basel, Switzerland. |
Lizenz: | Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden. |
0.94 MB
- Über diese
Datenseite - Reference-ID
10699917 - Veröffentlicht am:
11.12.2022 - Geändert am:
15.02.2023