时间：2020年9月17日20:00-21:30

地点：在线讲座ZOOM平台, 1389392785

主讲人：Maxime Cohen教授，加拿大麦吉尔大学

题目：Incentivizing Commuters to Carpool: A Large Field Experiment with Waze

摘要：Traffic congestion is a serious global issue. A potential solution, which requires zero investment in infrastructure, is to convince solo car users to carpool. In this paper, we leverage the Waze Carpool service and run the largest ever digital field experiment to nudge commuters to carpool. We identify users who can save a significant commute time by carpooling through the use of an high-occupancy vehicle (HOV) lane, users who can still use an HOV lane but with a low time saving, and users who do not have access to a HOV lane on their commute. We then send in-app notifications to examine the tradeoff between mentioning the HOV lane, highlighting the time saving, emphasizing the monetary incentive, and showing a generic message. We find a strong relationship between the affinity to carpool and the potential time saving through an HOV lane. Specifically, we estimate that mentioning the HOV lane increases the click-through rate and conversion rate by 133-185% and 64-141%, respectively relative to sending a generic message.

个人简介：Maxime Cohen是麦吉尔大学零售管理和运营管理的副教授，麦吉尔零售创新实验室的联合主任。在此之前，他在纽约大学斯特恩分校技术、运营和统计学担任助理教授，同时也是谷歌人工智能的研究科学家。除了大学教学和学术研究，他还积极为公司和初创公司提供定价、零售和数据科学方面的建议。

他的核心专长是数据科学和运营管理的交叉融合。他曾在零售、共享单车、航空公司、可持续发展、云计算、在线广告、点对点贷款和社交网络方面工作，也曾与不同公司进行合作，包括谷歌、沃兹、甲骨文零售、IBM Research、Via（共享单车）、Spotify、Aldo Group、Cargo、Staples以及其他初创公司，主要利用优化、机器学习、随机建模、计量经济学、博弈论和现场实验等工具开发解决方案。