BILATERAL MATCHING DECISION-MAKING IN PROPERTY TRADING PLATFORM: A METHOD CONSIDERING INTERMEDIARY MORAL HAZARD

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Rui Wang, Wenjing Zuo
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引用次数: 0

Abstract

Effective method of bilateral matching decision-making could drive the property transaction market more dynamic and healthier. In the property trade process, once intermediaries are conscientious, the portrait of matching parties are clearly described, a reasonable and satisfactory result can be got. However, the intermediary moral hazard and the loss of the description about the characteristics of matching parties can affect the matching result. By developing a method for a property transaction platform, this paper proposes a novel approach that considering intermediary moral hazard to improve matching efficiency. A mathematical model of intermediary moral hazard is performed, and then the price and other evaluation indicators of sellers and buyers are described by five different types of value forms. A multi-objective bilateral matching decision-making model that “minimizes the intermediary moral hazard in the case of the maximum benefits of the matching parties” is constructed and solved by the dictionary order method. A real case study of property trade platform is presented to illustrate how the proposed approach could be applied in practice. The results of this research indicate that the proposed approach is a useful tool for matching sellers and buyers under the intermediary moral hazard and has substantial practical application.
房地产交易平台双边匹配决策:一种考虑中介道德风险的方法
有效的双边匹配决策方法可以推动房地产交易市场更加活跃和健康。在物业交易过程中,只要中介尽职尽责,清晰地描绘出配对双方的形象,就能得到合理而令人满意的结果。但是,中介的道德风险和对匹配方特征描述的缺失会影响匹配结果。本文通过开发一种房地产交易平台的方法,提出了一种考虑中介道德风险以提高匹配效率的新方法。建立了中介道德风险的数学模型,并用五种不同类型的价值形式描述了买卖双方的价格等评价指标。构建了“在匹配方利益最大化的情况下,使中介道德风险最小化”的多目标双边匹配决策模型,并采用字典顺序法求解。最后,以房地产交易平台为例,说明本文提出的方法在实践中的应用。研究结果表明,该方法是解决中介道德风险下买卖双方匹配问题的有效工具,具有重要的实际应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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