Research on the Behavior and Mechanism of Algorithmic Differential Pricing in Housing Rental Market

Abstract

Abstract: The profound application of big data and algorithms has changed the traditional pricing methods. A variety of rental methods and pricing methods in the housing rental market have provided a scenario for studying the pricing behavior and mechanism of algorithms. The empirical research based on the micro-data of the housing rental market in X city reveals that: compared with traditional pricing methods, the algorithmic pricing significantly reduces the rental price, that is, the leasing enterprises can reduce the labor cost to alleviate the rental pressure of tenants, which increases the welfare of tenants through algorithmic pricing. After subdividing the samples on the supply side, it is found that the specialized housing rental enterprises do not take advantage of data and technology to deprive tenants of their welfare through algorithmic pricing. After subdividing the samples on the demand side, it is found that the algorithm pricing has differential pricing behaviors based on the domicile and age of the tenants. The dynamic effect of algorithmic pricing indicates that the algorithm will improve in favor of tenants over time and adjust the price according to changes of the external market environment. This means that supporting the application of digital technologies such as algorithms in the housing rental market, regulating the unreasonable differential pricing behavior driven by algorithm and vigorously cultivating professional and high-quality real estate brokers are of great significance to the sustainable development of the housing rental market.

Key words: algorithmic pricing, price mechanism, big data, housing rental market

CLC Number:

F293

Chen Li-zhong, Tang Tian. Research on the Behavior and Mechanism of Algorithmic Differential Pricing in Housing Rental Market[J]. Contemporary Finance & Economics, 2025, 0(2): 3-12.

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