文献类型：期刊文献

英文题名：Housing affordability evaluation based on the third-generation prospect theory and the improved VIKOR method

作者：Wu, Guancen[1];Li, Chen[1];Niu, Xing[2]

机构：[1]Shanghai Univ, Sch Management, Shanghai, Peoples R China;[2]East China Univ Sci & Technol, Sch Social & Publ Adm, Shanghai, Peoples R China

年份：2022

卷号：42

期号：3

起止页码：1405

外文期刊名：JOURNAL OF INTELLIGENT & FUZZY SYSTEMS

收录：;EI(收录号：20220811669047);WOS:【SSCI(收录号:WOS:000752849700010)，SCI-EXPANDED(收录号:WOS:000752849700010)】；

语种：英文

外文关键词：Housing affordability; third-generation prospect theory; dynamic reference point; prospect value; VIKOR

摘要：Housing affordability is an important issue and can be measured by an increasing number of indicators. Different urban settings may lead to different housing affordability criteria. This study incorporates the third-generation prospect theory and improved VIKOR method to construct a novel, comprehensive evaluation model for assessing housing affordability. The housing price to income and rent to income ratios were chosen as evaluation indicators, and the yearly median value of each indicator was taken as a dynamic reference point. The housing affordability indicators' realistic prospect value matrix for large-and medium-sized Chinese cities were obtained for the study period's duration. The comprehensive housing affordability prospect values were ranked using the improved VIKOR with entropy weight method. The novel proposed approach's rationality and effectiveness were examined by comparing the original and prospect values, performing sensitivity analysis on the prospect value parameters, contrasting the ordinary and improved VIKOR methods, and comparing the proposed approach with the TOPSIS method. The results demonstrate that the proposed method can consider the decision maker's psychological factors, endow housing affordability evaluation criteria with dynamic characteristics, overcome the problem of order reversal, and ensure the optimal compromise solution. Therefore, the proposed approach is suitable for housing affordability evaluation.