考虑租客异质性的长租公寓动态定价及租赁模式研究

doi:10.16381/j.cnki.issn1003-207x.2024.1177

摘要/Abstract

摘要：

针对长租公寓企业盈利率低、定价体系尚不完善、供需难匹配等发展困境，基于租客异质性探讨季节性因素和不同租赁模式对长租公寓企业动态定价及经营收益的影响。利用Logit模型刻画租客选择行为的异质性，分别构建不考虑季节性因素的长租模式、考虑季节性因素的长租模式以及考虑季节性因素的长短租结合模式下多周期多等级房间的动态规划模型，得到三种模式下各时期各等级房间的最优定价及企业预期总收益，进而通过模型分析得出长租公寓企业的动态定价策略，最终利用某品牌长租公寓企业实例进行数值分析，并得出了最优的租赁模式选择。研究结果表明，季节性动态定价有利于企业在旺季获取超额收益、在淡季提供更低价格，在获取季节性溢价的同时更好地进行市场细分；长短租结合模式在合理设置价格折扣和短租比例的情况下能够有效拓宽客源，进一步提升企业收益。研究结论为长租公寓企业实施科学动态定价及开展多元化经营提供了参考。

关键词: 顾客异质性, 长租公寓, 动态定价, 租赁模式, 收益管理

Abstract:

Based on the industry characteristics of customer heterogeneity， seasonal demand， pricing， and the long-term impact of leasing models on revenue in long-term rental apartment enterprises， three dynamic planning models for multi period and multi-level rooms under the condition of customer discrete selection are established based on revenue management research methods. It explores the impact of seasonal dynamic pricing and long-term rental combined leasing models on the operating revenue of long-term rental apartments， and conducts numerical analysis through real-life cases of well-known long-term rental apartment enterprises in China. It is found that for pricing strategies：（1） Throughout the entire business cycle， in the presence of inventory surplus， higher-level rooms always have pricing power；（2） For the traditional long-term rental model， the pricing of low-level rooms should remain stable， while the price of higher-level rooms can fluctuate appropriately according to customer arrival rates；（3） When implementing seasonal dynamic pricing， price changes must comply with market supply and demand laws， but price adjustments for lower level rooms should be based on the sales profit of higher-level rooms；（4） In the combination of long-term and short-term rental models， the marginal revenue of long-term/short-term rental is the key factor determining pricing. When the ratio of marginal revenue between short-term and long-term rental is high， pricing should generally increase， and when it is low， the opposite is true. In addition， long-term rental discounts should be accompanied by short-term rental price increases， and a pricing strategy of “high price， high discount” during peak seasons and “low price， low discount” during off-season can be adopted. However， the average discount intensity during the operating period should not be too large. For the selection of leasing models， launching short-term rental services can effectively stimulate market vitality and alleviate the negative impact of insufficient demand during the off-season. Under the reasonable control of the proportion of short-term rental customers and long-term rental discount coefficients by long-term rental apartment enterprises， the revenue of the combination of long-term and short-term rental models is significantly higher than that of the long-term rental model. The results indicate that seasonal dynamic pricing and the combination of long-term and short-term leasing models can significantly improve the total revenue of long-term rental apartment enterprises， providing favorable references for the systematic， standardized pricing and diversified operation of the industry.

Key words: customer heterogeneity, long-term rental apartments, dynamic pricing, leasing model, revenue management

中图分类号:

F272.3

叶蓓蓓,苏应生,吴江, 等. 考虑租客异质性的长租公寓动态定价及租赁模式研究[J]. 中国管理科学, 2026, 34(7): 95-105.

Beibei Ye,Yingsheng Su,Jiang Wu, et al. Dynamic Pricing and Leasing Model of Long-Term Rental Apartments Based on Customer Heterogeneity[J]. Chinese Journal of Management Science, 2026, 34(7): 95-105.

图/表 9

表1

模型符号及含义"

符号	含义	符号	含义
$T$	经营期间的时期总数	$x t$	$t$ 时期各等级房间的数量集合
$t$	经营期间的某一特定时期	$e j$	第 $j$ 个元素为1其余元素为0的 $n$ 维向量
$n$	房间质量等级总数	$x t - e j$	$t$ 时期末 $t - 1$ 时期初各等级房间的数量集合
$λ t$	$t$ 时期的顾客到达率	$u t j$	$t$ 时期租客对第 $j$ 等级房间的预期效用
$q j$	房间质量等级系数	$θ$	租客质量偏好系数
$p t$	$t$ 时期各等级房间的价格集合	$α t j$	$t$ 时期租客对第 $j$ 等级房间的选择概率
$p t j$	$t$ 时期第 $j$ 等级房间的价格	$V t$	$t$ 时期企业的预期总收益

表1

图1

图2

图3

图4

图5

图6

图7

表2

δ和β对模型C长/短租收益及总收益的影响"

$δ$	长租收益	短租收益	总收益	$β$	长租收益	短租收益	总收益
0.98	34958.79	6877.72	41836.52	0.10	28508.79	5489.60	33998.39
0.96	33514.47	6640.30	40154.77	0.12	28963.36	5645.36	34608.72
0.94	32074.63	6403.10	38477.73	0.14	29338.03	5792.82	35130.86
0.92	30639.01	6164.92	36803.93	0.16	29472.81	5898.39	35371.20
0.90	29214.94	5925.40	35140.34	0.18	29214.94	5925.40	35140.34
0.88	27813.52	5688.39	33501.90	0.20	28762.57	5916.76	34679.33
0.86	26440.57	5455.26	31895.83	0.22	28324.57	5879.81	34204.38
0.84	25096.99	5225.92	30322.91	0.24	27748.12	5815.11	33563.22
0.82	23983.56	5030.21	29013.77	0.26	27023.11	5719.39	32742.50

表2

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