The rise of online business and information platforms like Airbnb, Facebook, and Google, have transformed society, but not always for the better. A striking example of their unintended externalities occur in mandatory participation third party payer systems, or MP3PP’s, in which information platforms enjoy immense power by becoming the primary channels through which merchants reach their customers. The research project I was assigned focuses on online sponsored search, one of most profitable MP3PP industries, and the complex regulatory issues that come with manipulating search results for profit. Merchants have no choice but to pay search engines in order to gain any exposure, some compensating for poor service by paying more exorbitant amounts and thus hurting consumers. We investigated how this type of search engine behavior affects consumer welfare, accounting for variations to the MP3PP business model such as price discrimination, competition, and seemingly “free” services such as free Gmail and YouTube. We aimed to simulate the behavior patterns of profit-minded search engines interacting with self-interested consumers.
This research experience has taught me on many different levels, from nifty tricks in RStudio to the fundamental way I will ever approach problem-solving in the future. Being entrusted with such a complex project—and given great autonomy on how to solve it—teaches me more than just hard skills like coding. I have been directly involved in experimental design and had a say in what to do and how we would do it. Because I knew not only what but also why we asked certain questions, I have become a much more structured, efficient, and comfortable problem-solver. I have a better knack at deconstructing complex, sprawling questions into step-by-step tasks. I have learned to be confident in my ability to reach solutions even if I feel lost at first. Because of the nature of research, I am better at treating uncertainty in my results as a game, or a fun challenge, rather than something wrong. I understand confusing results as a normal part of the process that may even lead me closer to, not further from, realization.
The research experience also enhances what I learn on my academic track in business analytics, marketing, and economics. Besides gaining solid skills in coding and modeling, I sharpened my intuition about how businesses and consumers make decisions—utilizing various interdisciplinary concepts I have learned in classes (including, but not limited to, the self-perpetuating benefits of high market share, 3D solution planes from multivariable calculus, and Cournot and Hotelling duopoly models from microeconomics). I was able to back up my data tables with qualitative logic based on what we see in reality, and vice versa. I learned about the ethical implications of how search engines commodify information and was able to reflect those implications right in the numbers my code produced. That to me is something amazing.