Online Policies for Efficient Volunteer Crowdsourcing
Online Policies for Efficient Volunteer Crowdsourcing
复制标题
高效志愿者众包在线政策
DOI：
10.2139/ssrn.3802624
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Scott Rodilitz
中科院分区：
文献类型：
--
作者：
V. Manshadi;Scott Rodilitz
食品回收组织等非营利众包平台依靠志愿者来执行时间敏感的任务。因此，他们的成功关键取决于志愿者的有效利用和参与。为了鼓励志愿者完成任务，平台使用助推机制来通知一部分志愿者，希望他们中至少有一个做出积极回应。然而，由于过多的通知可能会减少志愿者的参与度，因此该平台面临着在通知更多志愿者完成当前任务和为未来的任务保留它们之间的权衡。受这些应用程序的推动，我们引入了在线志愿者通知问题，这是在线随机二分匹配的概括，其中任务按照任务类型的已知时变分布到达。任务到达后，平台会通知一部分志愿者，目的是最大限度地减少错过任务的数量。为了捕获每个志愿者对过多通知的不良反应，我们假设通知会触发一段随机的不活动时间，在此期间她将忽略所有通知。然而，如果志愿者很活跃并得到通知，她将以给定的配对特定匹配概率来执行任务，该概率捕获了她对该任务的偏好。我们开发了两种在线随机策略，可以实现恒定因子保证，这些保证接近我们为任何在线策略的性能建立的上限。我们的策略以及硬度结果通过交互活动时间分布的最小离散危险率进行参数化。我们的策略设计依赖于事前可行解决方案的两个修改：（1）适当缩小事前解决方案规定的通知概率，以及（2）稀疏该解决方案。此外，我们与基于志愿者的食品回收平台 Food Rescue U.S. 合作，通过使用来自美国各地的平台数据进行测试来证明我们政策的有效性。
Nonprofit crowdsourcing platforms such as food recovery organizations rely on volunteers to perform time-sensitive tasks. Thus, their success crucially depends on efficient volunteer utilization and engagement. To encourage volunteers to complete a task, platforms use nudging mechanisms to notify a subset of volunteers with the hope that at least one of them responds positively. However, since excessive notifications may reduce volunteer engagement, the platform faces a trade-off between notifying more volunteers for the current task and saving them for future ones. Motivated by these applications, we introduce the online volunteer notification problem, a generalization of online stochastic bipartite matching where tasks arrive following a known time-varying distribution over task types. Upon arrival of a task, the platform notifies a subset of volunteers with the objective of minimizing the number of missed tasks. To capture each volunteer's adverse reaction to excessive notifications, we assume that a notification triggers a random period of inactivity, during which she will ignore all notifications. However, if a volunteer is active and notified, she will perform the task with a given pair-specific match probability that captures her preference for the task. We develop two online randomized policies that achieve constant-factor guarantees which are close to the upper-bounds we establish for the performance of any online policy. Our policies as well as hardness results are parameterized by the minimum discrete hazard rate of the inter-activity time distribution. The design of our policies relies on two modifications of an ex-ante feasible solution: (1) properly scaling down the notification probability prescribed by the ex-ante solution, and (2) sparsifying that solution. Further, in collaboration with Food Rescue U.S., a volunteer-based food recovery platform, we demonstrate the effectiveness of our policies by testing them on the platform's data from various locations across the U.S.
DOI：
10.1145/3465456.3467613
发表时间：
2021-02
期刊：
Proceedings of the 22nd ACM Conference on Economics and Computation
影响因子：
--
作者：
C. Papadimitriou;Tristan Pollner;A. Saberi;David Wajc
通讯作者：
C. Papadimitriou;Tristan Pollner;A. Saberi;David Wajc
DOI：
10.1287/inte.2019.1005
发表时间：
2019-10
期刊：
INFORMS J. Appl. Anal.
影响因子：
--
作者：
Daniel Freund;S. Henderson;E. O'Mahony;D. Shmoys
通讯作者：
Daniel Freund;S. Henderson;E. O'Mahony;D. Shmoys
具有随机使用期限的可重复使用产品的动态分类优化
影响因子：
5.4
作者：
Rusmevichientong, Paat;Sumida, Mika;Topaloglu, Huseyin
通讯作者：
Topaloglu, Huseyin