动态定价和客户投诉

Y. Wei, Linli Xu, Yi Zhu
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引用次数: 3

摘要

许多双边匹配平台,如住宿、劳务和拼车,都使用审查系统来监控服务提供商,不满意的客户可以在那里投诉他们的服务体验。本文利用来自某大型拼车平台的综合数据集,探讨了服务提供商(司机)是否系统性地收到了并非其过错的投诉。我们发现,高峰期收费(一个不是司机过错的因素)平均会使投诉的可能性增加1.12至1.33倍。对于新手司机和高峰时段,这种影响会被放大。我们使用另外两种方法为这一发现提供因果支持:利用对峰时定价设置上限的政策变化的回归不连续,以及利用峰时触发不连续的匹配估计。为了将分析的终点扩展到经济影响,我们估计了投诉如何影响司机的日常收入。我们计算出,司机从高峰收费中获得的直接收入中,有25%被因投诉率上升而导致的未来收入损失所抵消。这些结果表明,在监控和评估客户评论以改善服务体验时,平台应该考虑非服务提供商负责的因素。
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Surge Pricing and Customer Complaints
Many two-sided matching platforms, such as those for lodging, labor, and ridesharing, use a review system to monitor service providers, where dissatisfied customers can complain about their service experience. Using comprehensive datasets from a large ridesharing platform, this paper explores whether service providers (drivers) systematically receive complaints for reasons that are not their fault. We find that surge pricing, a factor that is not the driver's fault, increases the likelihood of complaints by a factor of 1.12 to 1.33, on average. This effect is amplified for novice drivers and during rush hours. We use two additional approaches to provide causal support for the finding: a regression discontinuity exploiting a policy change that sets caps on surge pricing, and a matching estimator exploiting discontinuity in surge triggering. To extend the endpoint of our analysis to the economic impact, we estimate how the complaints affect a driver's daily income. We calculate that 25% of a driver's immediate income gain from surge fares is offset by the future income loss due to the increased complaint rate. These results suggest platforms should account for non-service-provider-responsible factors when monitoring and evaluating customer reviews to improve service experiences.
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