Zsolt Katona, Professor

Closed (1) Real or Fake: Managing User Authenticity in Ad Auctions

Applications for Fall 2018 are now closed for this project.

We are looking for talented designers and AI geeks. Our analytical modeling shows that blocking fake users on user-generated-content platform, such as Facebook, can make them click ads. Subsequently, ad revenue decreases as the number of fake clicks increase. The research will use real Facebook pages created by the team to empirically examine fake activities and validate the theoretical results. Specifically, we will come up with predictive metrics to quantify to what extent fake activities affect ad revenue. You will have develop your web design or machine learning muscles.

For alumni placement, see https://www.linkedin.com/in/xinchendigitalmarketing/
For what quantitative marketing phd is about, see below from a computer scientist-turned marketer and Professor at Wharton
https://www.ron-berman.com/2010/11/02/quant-marketing-what-is-that/


Designers will set up Facebook pages in the study and learn how to automate web data collection. AI geeks will contribute to developing and improving extant web-scraping programs as necessary and conduct subsequent predictive modeling. This project is especially well-suited for apprentices who wish to pursue an academic career in marketing science or an industry career in tech. By participating in the project, apprentices will develop web design, web scraping, and data analysis skills as well as people skills by working collaboratively with other teammates.

Day-to-day supervisor for this project: Xin Chen, Ph.D. candidate

Qualifications: A hard work ethic, superb attention to details, strong intellectual curiosity, and most importantly a fearless spirit to quickly pick up whatever new tool as needed. A minimum of 6-hour average weekly commitment and we will give priorities to those who wish to commit more time and energy. To qualify for consideration, please make sure to fill out https://goo.gl/forms/oLWDZW1IsMlXnRXm1

Weekly Hours: to be negotiated

Closed (2) Alibaba Fintech - Online Credit Markets

Applications for Fall 2018 are now closed for this project.

The Alibaba Fintech project, in collaboration with Ant Financial’s Luohan Academy, aims to estimate the informational rent Fintech produces in China’s consumer lending markets. We will examine how the combination of financial and marketing technology revolutionizes the lanscape of China's online credit card markets. Specifically, we apply econometric and predictive models to assess how it affects lender’s subsequent consumption and investment behavior, and estimates the crucial externalities thereof.

Fluency in Chinese is mandatory. We are looking for candidates who have strong data skills, i.e. fluency in R or Python.

Day-to-day supervisor for this project: Xin Chen

Qualifications: We are looking for candidates who have strong data and writing skills and an incredible work ethic. This project is suitable for those who wish to continue graduate studies in business, financial engineering, or a tech career after graduation. A hard work ethic, superb attention to details, strong intellectual curiosity, and most importantly a fearless spirit to quickly pick up whatever new tool as needed. A minimum of 6-hour average weekly commitment and we will give priorities to those who wish to commit more time and energy. To qualify for consideration, please make sure to fill out https://goo.gl/forms/oLWDZW1IsMlXnRXm1

Weekly Hours: to be negotiated