Mixed Pricing in Online Marketplaces
Penn collection
Degree type
Discipline
Subject
online markets
merger analysis
Applied Behavior Analysis
Behavioral Economics
Business
Business Administration, Management, and Operations
Cognitive Psychology
Management Sciences and Quantitative Methods
Marketing
Sales and Merchandising
Funder
Grant number
License
Copyright date
Distributor
Related resources
Author
Contributor
Abstract
A rich theory literature predicts mixed strategies in posted prices due to standard price discrimination, search frictions, and various other rationales. While typically interpreted as implying occasional sales or price dispersion, online marketplaces enable a firm to truly use randomization as a tool in pricing, and so such behavior should be expected to arise in online settings. We investigate a case of mixed pricing across a large subset of products on a major e-commerce website. We first test for randomizing behavior, and then construct a model of price discrimination that would generate randomization as optimal behavior. We estimate the model and use it to assess pricing effects of a proposed merger in the industry.