Online Demand Learning and Price Optimization with Endogeneity Effect
Project
Online Demand Learning and Price Optimization with Endogeneity Effect
Principal Investigator
David Simchi-Levi, He Wang
Massachusetts Institute of Technology
Oracle Principal Investigator
Sajith Vijayan
Setareh Boroujeni
Su-Ming Wu
Summary
Existing methods used in practice for demand estimation fail to control for price endogeneity, and thus produce inaccurate demand forecast which in turn leads to sub-optimal pricing strategies.
This project involves developing a demand estimation and online price optimization method that produces unbiased price elasticity and improves demand forecast accuracy. The algorithm optimizes the price on the fly, which allows for finding optimal price in the presence of price endogeneity.