Recently, instant delivery has been growing rapidly, with numerous platforms emerging to offer such services. Requestors dynamically arrive at the platform to place delivery service requests that detail their pickup locations, recipient locations, package weights, departure times, and willingness-to-pay (WTP). The platform then uses its dedicated riders, scattered in different places, to fulfill these requests. Given the dynamic and fluctuating characteristics of the demand, coupled with limited rider resources and heterogenous pickup costs, the platform faces the critical problem of dynamically pricing the requests and assigning the riders to maximize social welfare. To address this problem, we propose an online auction-based transaction mechanism. Specifically, we first propose a scoring function to evaluate the values of the requests over multi-period operations taking into account the requests’ attributes, riders’ delivery costs, and resource availability. Based on the scoring function, we design a time-varying Vickrey–Clarke–Groves (VCG)-like payment rule that can reflect the impacts of fluctuating supply-demand imbalances. Under this rule, a requestor will pay more during undersupply periods than during oversupply periods. To carve out the different impact degrees of the supply-demand imbalances, we further consider the linear, quadratic, and exponential time-varying resource parameters to construct the payment rule. In addition, we develop an online instant delivery resource allocation model to efficiently assign the riders to fulfill the accepted requests. We show that the proposed mechanism has desirable properties (individual rationality, budget balance, and incentive compatibility) and is computationally efficient. Furthermore, we give a lower bound for the mechanism efficiency. To validate the practicality of our mechanism and get some managerial insights into the operations of the instant delivery platform, we conduct numerical studies to compare the performance of our mechanism to the First-in, first-out (FIFO) allocation mechanism and to investigate the impacts of pricing functions, rolling horizon configurations, and rider numbers on the mechanism's performance.

中文翻译：

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基于在线拍卖的即时配送服务定价和分配机制


最近，即时交付迅速发展，出现了许多提供此类服务的平台。请求者动态地到达平台以提出递送服务请求，详细说明其取件位置、收件人位置、包裹重量、出发时间和付款意愿 （WTP）。然后，该平台使用分散在不同地方的专用骑手来满足这些请求。鉴于需求的动态和波动特性，再加上有限的骑手资源和异质的取车成本，该平台面临着动态定价请求和分配骑手以实现社会福利最大化的关键问题。为了解决这个问题，我们提出了一种基于在线竞价的交易机制。具体来说，我们首先提出了一个评分函数，以评估多周期操作中的请求值，同时考虑请求的属性、骑手的交付成本和资源可用性。基于评分函数，我们设计了一个类似时变的 Vickrey-Clarke-Groves （VCG） 支付规则，可以反映波动的供需失衡的影响。根据此规则，请求者在供应不足期间将比在供应过剩期间支付更多的费用。为了梳理供需失衡的不同影响程度，我们进一步考虑了线性、二次和指数时变资源参数来构建支付规则。此外，我们还开发了在线即时配送资源分配模型，以有效地分配骑手来完成已接受的请求。我们表明，所提出的机制具有理想的特性（个体理性、预算平衡和激励兼容性）并且计算效率很高。 此外，我们给出了机制效率的下限。为了验证我们机制的实用性并获得对即时交付平台运营的一些管理见解，我们进行了数值研究，将我们的机制的性能与先进先出 （FIFO） 分配机制进行比较，并调查定价函数、滚动视野配置和骑手数量对机制性能的影响。