Abstract
ABSTRACT The rise of big data and sophisticated, machine learning algorithms is increasing the prevalence of price discrimination and even personalized pricing. In traditional models, where consumers’ willingness-to-pay (WTP) is a function of preferences (and budget constraints), price discrimination is often celebrated for increasing efficiency albeit while reducing consumer surplus. This favourable view of price discrimination should be re-evaluated when WTP is a function of both preferences and misperceptions. With demand-inflating misperceptions, price discrimination is even more harmful to consumers and might reduce efficiency. These results are derived using a simple, linear demand model with different levels of price discrimination (or segmentation). In the many consumer markets where misperception is common, more careful scrutiny of price discrimination is warranted.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
