报告人简介：谭寅亮，美国杜兰大学弗里曼商学院管理科学方向助理教授，戈德林国际教育中心行政主任。博士毕业于美国佛罗里达大学，学习运营管理及信息系统，拥有丰富的商业分析方面的教学经验，曾获弗里曼商学院最佳教师奖。其研究兴趣主要集中在科技管理与创新、电子产品定价以及人工智能领域。在国际顶级期刊Management Science, MIS Quarterly, Information Systems Research, Production and Operations Management多次发表论文。现在担任Production and Operations Management资深编辑以及Decision Science副编辑。2019年被评为世界最佳40名40岁以下的商学院教授。
内容简介：Digital advertisements offer a full spectrum of behavioral customization for timing and content capabilities. The existing research in display advertising has predominantly concentrated on the content of advertising; however, our focus is on optimizing the timing of display advertising. In practice, users are constantly adjusting their engagement with content as they process new information continuously. The recent development of emotional tracking and wearable technologies allows platforms to monitor the user’s engagement in real time. We model the user’s continuous engagement process through a Brownian motion. The proposed optimal policy regarding the timing of behavioral advertising is based on a threshold policy with a trigger threshold and target level. Our results reveal that for a wide range of settings, the proposed policy not only significantly increases the platform’s profitability, but also improves the completion rate at which consumers finish viewing the advertisement.
