CAREER: Marketplace Design for Freight Transportation and Logistics Platforms

职业：货运和物流平台的市场设计

• 批准号: 2145661
• 负责人: He Wang
• 金额: $ 52.82万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-15 至 2026-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2145661&HistoricalAwards=false
• 关键词: CAREER; Marketplace; Design; Freight; Transportation

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). This Faculty Early Career Development (CAREER) grant will contribute to the advancement of national prosperity and economic welfare by supporting research to study digital freight and logistics marketplaces. The freight transportation industry in the US is enormous in market size but is also extremely fragmented and suffers from inefficiency. Digital freight marketplaces that emerged over the last few years are reshaping the logistics industry by offering automated and efficient channels to connect carriers with shippers. This award supports research to develop a fundamental understanding of methodologies for designing and optimizing digital freight marketplaces. The research findings will facilitate the growing innovation in the freight transportation marketplaces through collaboration with leading freight marketplace companies. The research also will benefit small trucking carriers and owner-operators, which account for over 90% of all carriers in the U.S., by lowering the barrier for them to participate in freight marketplaces and providing them with steady work and reliable earnings. The accompanying educational plan aims to educate the trucking industry workforce about digital freight marketplaces and broaden STEM interest for underrepresented communities through hands-on activities. Freight marketplaces face significant uncertainty from both the demand and supply side of the market, as they exhibit both geographical imbalance and seasonal volatility. This research will consider designing, analyzing, and optimizing marketplace control mechanisms for two-sided digital freight platforms. This research fills an important gap in the freight transportation literature, which mostly considers carriers with fixed capacities. This project considers a variety of market control mechanisms such as pricing, bundling, auction, and dedicated contracts; these mechanisms will need to be carefully coordinated to form an effective hybrid strategy while accounting for market participants who may strategically withhold their truthful preferences from the market operator. This research methodology will integrate fields such as statistical analysis and causal inference, stochastic models, approximate dynamic programming, auctions, and mechanism design. The performance assessments of the methods will be informed by available data and experiments in collaboration with freight industry partners who operate large-scale marketplaces.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项全部或部分根据2021年美国救援计划法案（公法117-2）资助。该学院早期职业发展（CAREER）补助金将通过支持研究数字货运和物流市场，为促进国家繁荣和经济福利做出贡献。美国的货运业市场规模巨大，但也非常分散，效率低下。过去几年出现的数字货运市场正在重塑物流行业，提供自动化和高效的渠道，将承运人与托运人联系起来。该奖项支持研究，以发展对设计和优化数字货运市场的方法的基本理解。研究结果将通过与领先的货运市场公司合作，促进货运市场不断增长的创新。这项研究还将使小型卡车运输公司和业主运营商受益，这些公司占美国所有运输公司的90%以上，降低他们参与货运市场的门槛，为他们提供稳定的工作和可靠的收入。配套的教育计划旨在教育卡车运输行业的劳动力了解数字货运市场，并通过实践活动扩大代表性不足的社区对STEM的兴趣。货运市场面临着来自市场供需双方的巨大不确定性，因为它们表现出地理不平衡和季节性波动。本研究将考虑设计，分析和优化双边数字货运平台的市场控制机制。这项研究填补了货运文献中的一个重要空白，该文献主要考虑具有固定容量的承运人。该项目考虑了各种市场控制机制，如定价，捆绑，拍卖和专用合同，这些机制将需要仔细协调，以形成一个有效的混合战略，同时考虑到市场参与者谁可能从战略上隐瞒他们的真实偏好的市场运营商。该研究方法将整合统计分析和因果推理，随机模型，近似动态规划，拍卖和机制设计等领域。该方法的性能评估将通过与运营大型市场的货运行业合作伙伴合作的现有数据和实验来提供信息。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Constant Regret Resolving Heuristics for Price-Based Revenue Management

基于价格的收入管理的持续遗憾解决启发法

• DOI: 10.1287/opre.2021.2219
• 发表时间: 2022
• 期刊: Operations Research
• 影响因子: 2.7
• 作者: Wang, Yining;Wang, He
• 通讯作者: Wang, He

Task assignment, pricing, and capacity planning for a hybrid fleet of centralized and decentralized couriers

• DOI: 10.1016/j.trc.2024.104533
• 发表时间: 2024-03
• 期刊: Transportation Research Part C: Emerging Technologies
• 作者: A. Behrendt;Martin Savelsbergh;He Wang

Dynamic Pricing and Matching for Two-Sided Queues

双边队列的动态定价和匹配

• DOI: 10.1287/opre.2021.2233
• 发表时间: 2023
• 期刊: Operations Research
• 影响因子: 2.7
• 作者: Varma, Sushil Mahavir;Bumpensanti, Pornpawee;Maguluri, Siva Theja;Wang, He
• 通讯作者: Wang, He

A Prescriptive Machine Learning Method for Courier Scheduling on Crowdsourced Delivery Platforms

众包配送平台上快递调度的规范性机器学习方法

• DOI: 10.1287/trsc.2022.1152
• 发表时间: 2023
• 期刊: Transportation Science
• 影响因子: 4.6
• 作者: Behrendt, Adam;Savelsbergh, Martin;Wang, He
• 通讯作者: Wang, He

Network Revenue Management Under a Spiked Multinomial Logit Choice Model

尖峰多项 Logit 选择模型下的网络收益管理

• DOI: 10.1287/opre.2022.2281
• 发表时间: 2022
• 期刊: Operations Research
• 影响因子: 2.7
• 作者: Cao, Yufeng;Kleywegt, Anton J.;Wang, He
• 通讯作者: Wang, He