摘要 近年来,在政策、需求和资本的刺激下,长租公寓进入了快速增长阶段。然而,行业竞争日益激烈,公寓运营商们都希望能扩大市场份额。合理的租金定价不仅能帮助企业吸引更多的顾客,提高品牌的知名度,而且能降低房间空置率,加快资本回收,从而达到扩大市场份额的目的。但目前长租公寓在运营中的租金设定大多基于门店管理者的主观判断,缺乏一定的标准,合理性很难得到保证。为解决人工定价存在的问题,本文将影响租金价格的内外部因素作为特征属性,利用某长租公寓运营商的已开业项目过去一年的经营数据及相关外部数据作为样本集,尝试构造了梯度提升回归树(Gradient Boosting Regression Tree)模型为长租公寓进行房间级定价,并通过验证得出,该模型对长租公寓的租金定价具有很强的参考性。 In recent years,with the stimulation of policies,demand and capital,long-term apartments have entered a stage of rapid growth.However,the competition is increasingly fierce and operators long for expanding their market share.Reasonable rental pricing can not only help companies attract more tenants,increase brand awareness,but also reduce the vacancy rate of rooms and accelerate capital turnover,thus achieving the goal of expanding market share.Unfortunately,the current rental price setting is based on the subjective judgment of the store manager.Without certain price setting standards,there is a lack of rationality of the price.In order to solve the problem of manual price adjustment,this paper attempts to build a Gradient Boosting Regression Tree(GBRT)model,which takes internal and external factors affecting the rental as attributes and uses the operating data of a long-term apartment company’s current rental units in the past year and related external data as the training data to set the price of apartments.We find that that the rental price predicted by the GBRT model can provide proper reference for the company.
机构地区 安永华明会计师事务所 厦门大学管理学院
出处 《管理会计研究》 2021年第1期35-44,102,共11页 MANAGEMENT ACCOUNTING STUDIES
基金 国家自然科学基金项目(71672162) 中央高校基本科研业务基金项目(20720151132)的资助。
分类号 F29 [经济管理—国民经济]
