英文标题：
《Driver Surge Pricing》
---
作者：
Nikhil Garg, Hamid Nazerzadeh
---
最新提交年份：
2021
---
英文摘要：
  Ride-hailing marketplaces like Uber and Lyft use dynamic pricing, often called surge, to balance the supply of available drivers with the demand for rides. We study driver-side payment mechanisms for such marketplaces, presenting the theoretical foundation that has informed the design of Uber\'s new additive driver surge mechanism. We present a dynamic stochastic model to capture the impact of surge pricing on driver earnings and their strategies to maximize such earnings. In this setting, some time periods (surge) are more valuable than others (non-surge), and so trips of different time lengths vary in the induced driver opportunity cost.   First, we show that multiplicative surge, historically the standard on ride-hailing platforms, is not incentive compatible in a dynamic setting. We then propose a structured, incentive-compatible pricing mechanism. This closed-form mechanism has a simple form and is well-approximated by Uber\'s new additive surge mechanism. Finally, through both numerical analysis and real data from a ride-hailing marketplace, we show that additive surge is more incentive compatible in practice than is multiplicative surge.
---
中文摘要：
优步（Uber）和利夫特（Lyft）等租车市场使用动态定价（通常称为激增）来平衡可用司机的供应和对租车的需求。我们研究了此类市场的驱动端支付机制，为优步新的附加驱动端激增机制的设计提供了理论基础。我们提出了一个动态随机模型来描述激增定价对驾驶员收益的影响，以及他们实现收益最大化的策略。在此设置中，一些时间段（喘振）比其他时间段（非喘振）更有价值，因此不同时间长度的行程在诱导驾驶员机会成本中有所不同。首先，我们表明，乘性激增（历史上是叫车平台的标准）在动态环境中与激励不兼容。然后，我们提出了一种结构化、激励相容的定价机制。这种封闭形式的机制形式简单，与优步新的加性喘振机制非常接近。最后，通过数值分析和一个叫车市场的实际数据，我们表明，在实践中，加性激增比乘性激增更具激励相容性。
---
分类信息：

一级分类：Computer Science        计算机科学
二级分类：Computer Science and Game Theory        计算机科学与博弈论
分类描述：Covers all theoretical and applied aspects at the intersection of computer science and game theory, including work in mechanism design, learning in games (which may overlap with Learning), foundations of agent modeling in games (which may overlap with Multiagent systems), coordination, specification and formal methods for non-cooperative computational environments. The area also deals with applications of game theory to areas such as electronic commerce.
涵盖计算机科学和博弈论交叉的所有理论和应用方面，包括机制设计的工作，游戏中的学习（可能与学习重叠），游戏中的agent建模的基础（可能与多agent系统重叠），非合作计算环境的协调、规范和形式化方法。该领域还涉及博弈论在电子商务等领域的应用。
--
一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
--
一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
--

---
PDF下载：
-->