The mismatch between the supply and demand of online-listed rental housing (ORH) is an important factor restricting the operational efficiency of online rental service platforms. However, extant literature pays little attention to this problem. This study proposes an ORH multiattribute supply and demand matching decision model based on the perceived utility of matching both sides of this market. The model considers the multiattribute information of ORH, such as area, transportation, rent, room, and interior decoration, and quantifies their perceived utility values based on the theory of disappointment. Thereafter, we construct the matching decision model and verify it for feasibility by applying it to Shanghai’s ORH supply and demand information—our empirical case. The results show that this method can be applied to online rental housing platforms and meet the supply and demand matching requirements to the greatest extent. The constructed model takes into account the perceptions of both supply and demand parties, may promote the effective matching of ORH supply and demand, and bears theoretical implications for the improvement of rental housing matching in ORH platforms.

中文翻译：

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在线租赁房屋多属性供需匹配决策模型：基于上海的实证研究

在线租赁房屋的供求不匹配是制约在线租赁服务平台运营效率的重要因素。但是，现有文献很少关注这个问题。这项研究提出了一个ORH多属性供需匹配决策模型，该模型基于匹配该市场双方的感知效用。该模型考虑了ORH的多属性信息，例如面积，交通，租金，房间和室内装饰，并基于失望理论对它们的感知效用值进行了量化。此后，我们构建匹配的决策模型，并将其应用于上海的ORH供求信息（我们的经验案例），以验证其可行性。结果表明，该方法可应用于在线租赁住房平台，最大程度地满足了供需匹配的要求。构建的模型考虑了供需双方的看法，可以促进ORH供需的有效匹配，并对ORH平台中出租房匹配的改进具有理论意义。