Essays on the Economics of Digital Markets

Abstract

This dissertation provides a comprehensive investigation of the IT economy in the digital market by examining user behaviors and institutions’ strategies. The essays include research questions from two different dynamic settings and answer questions by applying corresponding empirical setups. The first essay examines the impact of technology restriction and demand shifts in transportation dynamics. A transportation network company (TNC) is an app-based, two-sided platform that matches passengers with vehicles through information sharing. In 2015, the Shanghai government introduced a policy to restrict taxi drivers’ use of TNC apps during certain hours. We leverage this exogenous policy shock to investigate the economic impact of information sharing on the use of taxis and the entire transportation dynamics. We identify (1) a significant decrease in the total number of taxi transactions during the enforcement time but a significant increase during non-enforcement times, (2) simultaneous traffic increase on public transportation during policy enforcement and non-enforcement times (3) increase in congestion level on surface streets, indicating a spillover to private vehicle use for short-distance rides. Interestingly, our mechanism analysis reveals an increased average travel distance after restricting information sharing suggesting the dominant mechanism of information sharing. The second essay investigates the right online connection that helps users in the job market. Recognizing recruiters’ increasing reliance on professional networking sites, job seekers strive to create as many professional connections as possible. In particular, a common tactic is to make LinkedIn connections with professionals who work for the target companies in the job seekers’ target fields, as they can offer timely information about new job openings and become potential referrers. This paper empirically investigates whether such a networking tactic is actually instrumental in obtaining referrals. Much to our surprise, the analysis reveals that this common tactic is not a promising way to get referrals: We find that job seekers are less likely to be referred by employees who are in the target company and the target field due to the peer competition. We further find that this adverse effect of job similarity on referrals weakens as the hierarchical level of the referring employee gets higher than that of the job candidate, because they are less likely to compete directly. Although one might expect that gender homophily may weaken this competition effect, we find that it does not.