Essays on digital economy

• Main Author: Wu, Mengxi, Ph. D. Massachusetts Institute of Technology
• Other Authors: Sara Fisher Ellison and Glenn Ellison.
• Format: Others
• Language: English
• Published: Massachusetts Institute of Technology 2017
• Subjects: Economics.
• Online Access: http://hdl.handle.net/1721.1/111344

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Economics, 2017. === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 109-115). === This dissertation is a collection of three empirical essays studying consumer behavior and firm strategy in the digital economy. The first chapter examines how consumers learn from their market experience in an online marketplace. Using consumers' six-month purchase history data in a unique empirical setting in one of China's largest e-commerce platforms, I find that consumers buy from cheaper sellers as they gain market experience. To investigate how market experience improves the outcomes of price search, I incorporate price learning into a flexible structural search model, in which consumers have Dirichlet priors and update their price beliefs based on their past purchase prices in a Bayesian fashion. The results suggest that consumers have an upward bias in their prior price beliefs and are increasingly more price sensitive as they gain market experience. Early in a consumer's purchase history, the memory of sellers and prices from previous purchases accounts for a large portion of the price improvements, whereas an increasing price sensitivity plays a larger role in explaining the price advantage later on. The second chapter investigates whether the new form of quality disclosure in the digital age - online reviews - incentives restaurants to improve quality. With little local information, tourists rely more on online reviews for restaurant recommendation than locals. Exploiting this source of variation in the impact of online reviews on restaurants, I study the trend of Yelp ratings for chain-affiliated restaurants in Las Vegas between 2005 and 2015. After controlling for common trends of restaurant chains and zip-code areas, I find that for chains with a moderate size, the customer reviews of their units closer to the Strip - the center of Las Vegas tourist activity - improve significantly more during the eleven-year data period when online reviews gain popularity, while the Strip units initially had worse ratings than the off-the-Strip units in the early days of online reviews. No such difference is found for very small, regional chains or large, multinational chains. While market transparency is expected to increase as a result of the digital economy, in the third chapter I document the obfuscation strategies that merchants implement on an e-commerce platform with a price-comparison feature. Furthermore, I present evidence that sellers intentionally engage in the price obfuscation strategy to be more profitable and find a systematic relation between seller experience and their choice of obfuscation strategies: experienced sellers are more likely to use the bait-pricing strategy by advertising a low price, while new sellers tend to combine similar products into one listing to appear more popular and also offer the lowest price. In addition, consistent with results found in the first chapter, consumers with less market experience are more prone to being exploited by price obfuscation. === by Mengxi Wu. === 1. The Mechanisms of Consumer Learning and Price Search in a Homogeneous Goods Market -- 2. Do Online Reviews Affect Quality? Evidence from Yelp.com -- 3. Obfuscation and Experience: Empirical Evidence from on Online Market. === Ph. D.