Abstract: In the traditional rental mode, consumers need to pay the deposit for rental products, which limits the development of the rental platform. With the rapid development of big data technology, third-party credit evaluation organizations represented by Sesame Credit and Tencent Credit have developed. Based on the data resources owned, third-party credit evaluation organizations can evaluate consumers’ credit levels, which will provide support to the credit rental business mode, and also provide new business opportunities to the rental platform. This paper conducts a study on whether the rental platform should incorporate the third-party credit evaluation mechanism. Taking into account several factors, including the proportion of “rich” customers, the proportion of high credit customers and the credit evaluation accuracy, this paper constructs the profit models of the rental platform under the two strategies, incorporating and not incorporating the third-party credit evaluation mechanism. Then, by solving the models, the optimal product rental price, the platform’s profits under the two strategies are obtained. Further, by means of numerical simulation, this paper compares the optimal profits of the rental platform under the two strategies.
The research results show: (1)Under the credit rental model, the rental price is affected by the proportion of “rich” customers, the proportion of high credit customers and the credit evaluation accuracy. Therefore, the price strategy should be adjusted appropriately according to market conditions. (2)Based on the factors, such as the proportion of “rich” customers, the proportion of high credit customers and the credit evaluation accuracy, the rental platform should make strategies for incorporating the third-party credit evaluation mechanism. When the proportion of “rich” customers is high, the platform should not incorporate the third-party credit evaluation mechanism. When the proportion of “rich” customers is low and the proportion of high credit customers is high, the platform should incorporate the third-party credit evaluation mechanism. And, with an increase in the credit evaluation accuracy, the platform will gain more profit from the incorporation of the third-party credit evaluation mechanism.
In addition, this paper further studies the changes in social welfare under the two strategies. The research shows according to the size of social welfare, the government and relevant departments can regulate the incorporation strategy of the third-party credit evaluation mechanism of the rental platform. When the proportion of “rich” customers is low and the proportion of high credit customers is high, the government and relevant departments may adopt the method of providing financial subsidies or reducing taxes to the rental platforms, and encourage rental platforms to incorporate the third-party credit evaluation mechanism. When the proportion of “rich” customers is high, the government and relevant departments may restrict or regulate the incorporation of the third-party credit evaluation mechanism for the rental platforms by strengthening the supervision of the rental platforms or establishing punishment mechanisms.
This study provides a theoretical basis and reference for the decision-making of rental platforms and relevant government departments. But, this paper assumes that the credit evaluation accuracy is an exogenous variable, and further research can consider taking a contractual design approach to promote the third-party credit evaluation agency to continuously improve the evaluation accuracy.

Key words: rental platform, third-party credit evaluation mechanism, strategy analysis, numerical simulation

摘要： 本文针对租赁平台是否应该引入第三方信用评估机制开展研究。考虑有钱支付押金的消费者比例、自身高信用的消费者比例以及信用评估准确率等因素,构建不引入和引入第三方信用评估机制两种策略下租赁平台利润模型。通过模型求解,分别确定了两种策略下最优租赁价格和租赁平台的最优利润。通过数值仿真方法对两种策略下租赁平台最优利润进行比较分析。研究发现:当有钱支付押金的消费者比例较小且自身高信用的消费者比例较大时,平台应该引入第三方信用评估机制,且信用评估准确率越高,平台引入第三方信用评估机制越有利;当有钱支付押金的消费者比例较大时,平台不应该引入第三方信用评估机制。此外,本文进一步研究了两种策略下社会福利的变化。所得到的研究结果对租赁平台第三方信用评估机制的引入策略具有一定的指导价值。

关键词: 租赁平台, 第三方信用评估机制, 策略分析, 数值仿真