Event

Smith School DOIT Seminar: Ankur Mani, "The Value of Network Information for Pricing"

Friday, April 28, 2023
1:00 p.m.
2509 Van Munching Hall
Alex Estes
aestes@umd.edu

Smith School DOIT Seminar
The Value of Network Information for Pricing

Ankur Mani
Assistant Professor
Industrial and Systems Engineering Department
University of Minnesota

Abstract
We study the value of network information for pricing under network externalities. Recent trends in industry suggest that increasingly firms are using information about social networks to offer personalized prices to individuals based upon their positions in the social network. In the presence of positive network externalities, firms aim to increase their profits by offering discounts to influential individuals that can stimulate consumption by other individuals at a higher price. Recent research has focused on the computation of optimal prices in deterministic networks under positive externalities.

We would like to answer a more fundamental question: how valuable is social network information and what kind of network information is needed? We find, surprisingly, that the value of full network information and such pricing policies (increase in profits due to price discrimination) in very large random networks are often not significant. Particularly, for Erdos-Renyi random networks, we provide the exact rates at which this value decays in the size of the networks for different ranges of network densities. Our results show that there is a non-negligible value of price discrimination for a small class of moderate-sized Erdos-Renyi random networks.

We also present a framework to obtain bounds on the value of price discrimination for random networks with general degree distributions and apply the framework to obtain bounds on the value of price discrimination in power-law networks. Finally, we demonstrate that networks demonstrating community structure that is stable with respect to scaling may have reasonable value of network information. However, the information about community structure is sufficient and any more information is of no value.

Paper(s): https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3831696
Different parts of the work were jointly conducted with Calvin Roth, Jiali Huang, and Zizhuo Wang.

Biography
Ankur Mani is an assistant professor in the Industrial and Systems Engineering department at the University of Minnesota. He is also an affiliate of the Data Science Initiative and Control Systems and Dynamics Group at the University of Minnesota. He received his Ph.D. from the Massachusetts Institute of Technology and B.Tech. degree from the Indian Institute of Technology, Delhi. Ankur's research interests include networks, distributed experimentation, and game theory with applications in social networks, supply chain networks, transportation networks and health care. His research has appeared in major venues including Management Science and Nature Human Behavior and has received awards from the INFORMS Revenue Management and Pricing section, Aviation Applications section, POMS-HK, and the Net Institute.