Date of Award

May 2019

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Economics

Committee Member

Matthew Lewis

Committee Member

Tom Lam

Committee Member

F. Andrew Hanssen

Committee Member

Christy Zhou

Abstract

The first chapter of this dissertation deals with different cash-back rebates in the new-automobile market. In the automotive industry, manufacturers use different types of cash-back rebates to attract buyers to their brands. In this chapter, I mainly focus on the use of “conquest cash” and “loyalty cash” which enable manufacturers to discriminate price among different groups of customers. The conquest cash and loyalty cash are based on consumers’ purchase history. The purpose of conquest cash is to poach the rival manufacturers’ customers, whereas the loyalty cash lowers prices for the manufacturer’s customers. Moreover, I examine “college-graduate” discounts and “military” discounts which manufacturers use to practice price discrimination on certain demographic groups of customers. I empirically investigate the factors associated with greater use of these offers in the U.S. auto industry and compare these patterns to predictions from the theoretical literature. The theoretical studies include product differentiation and brand preferences as plausible reasons to explain price discrimination by purchase history. My results suggest that manufacturers’ market share impacts the manufacturers’ decision for customer poaching and customer retention. However, the manufacturers’market share does not determine the use of college-graduate and military discounts.

The second chapter examines how competition affects information disclosure on Airbnb. Airbnb accommodates lodging for travelers by matching hosts and guests in an online platform. Hosting on this platform has been getting popular in recent few years. Similar to other online platforms, sharing photos, description of a product, and reviews of previous users are possible ways to attract customers. It is possible that as the competition among Airbnb’s listings increases, hosts change the description of their listings. Theoretical papers include different relationships between competition and information disclosure. I use publicly available data of Airbnb’s listings in San Fransico and its surrounding cities to examine whether an increase in the number of listings impacts hosts’ information disclosed about the quality of listing. My findings suggest that on average a higher number of listings increases the number of words in the description of listings.

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