[07-22] Designing Information Strategies for Digital Platforms: Findings from Randomized Field Experiments (A/B tests)

文章来源:  |  发布时间:2019-07-19  |  【打印】 【封闭

  

  时间:2019722日(周一)下午200 

    

  地点:软件所5号楼334申报厅 

    

  讲者:史岚菲(美国弗吉尼亚大年夜学助理传授) 

    

  标题: Designing Information Strategies for Digital Platforms: Findings from Randomized Field Experiments (A/B tests) 

    

  摘要: The rise of digital platforms has transformed our economy and reshaped consumer behaviors and experiences. While practitioners and researchers have a growing interest in understanding digital platforms, there is still a dearth of research on how platforms can design effective information strategies to mitigate fundamental issues such as information asymmetry and search frictions by leveraging granular data. By focusing on significant real-world problems on digital platforms, I aim to examine IT-enabled and analytics-driven information strategies and study the impact of these strategies on the users as well as on the platforms themselves. In this talk, I will be sharing several A/B tests (e.g., motivating mobile adoption, voluntary verification mechanisms, user recommendation, etc.) that I design and conduct in collaboration with two different online platforms. Business implications and actional suggestions will be discussed. 

    

  讲者简介: Lanfei Shi will be joining the University of Virginia, McIntire School of Commerce as a tenure-track professor this coming fall. Her research interests revolve around designing effective information strategies for online multisided platforms, and she adopts a multi-disciplinary approach to combine randomized field experiments with econometrics models and big data analytics. She actively collaborates with online platforms of different types (e.g., E-commerce, social media, online dating) to help with consumer engagement, and many of the good practices suggested by her studies have been adopted by collaborating platforms. She gets her doctoral degree in Information Systems in Robert Smith School of Business at the University of Maryland. Before joining the business school, she was a CS researcher with a focus on data analytics and HCI at the University of Pittsburgh.