Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)



First Advisor

Karthik Kannan

Committee Chair

Karthik Kannan

Committee Member 1

Kemal Altinkemer

Committee Member 2

Hossein Ghasemkhani

Committee Member 3

George Shanthikumar


This dissertation consists of three essays that study the transformative impact of new information technologies under three specific contexts using both empirical and theoretical approaches. Chapter 2 examines the online review system, which is the new type of information technology that replaces the traditional word-of-mouth communication. Particularly, we study the practice of the platform owner that uses monetary incentives to attract reviewers. The research problem is important as firms, which seek to strengthen their online review platforms, have considered various forms of incentives, including extrinsic rewards, to encourage users to write reviews. We encountered a natural experiment design where one review platform suddenly started offering monetary incentives for writing reviews. Along with data from and using the difference-in-differences approach, we compare the quantity and quality of reviews before and after rewards were introduced in the treated platform. We find that reviews are significantly more positive but the quality decreases. Taking advantage of the panel data, we also evaluate the effect of rewards on existing reviewers. We find that their level of participation after monetary incentives decreases, but not their quality of participation. Lastly, even though the platform enjoys an increase in the number of new reviewers, disproportionately more reviews appear to be written for highly rated products.

In Chapter 3, we investigate the economic implications of the new online communication system that has become increasing popular in recent years. This system allows consumers to ask and answer questions regarding the products that are available on the platform. It typically co-exists with the standard online review system where consumers share their own experience of the products. Although several websites adopt this Q&A system or even replace the standard review system with it, the economic implications of such a Q&A system have not been studied in the previous literature. We collected the data from two online shopping platforms and employed the difference-in-differences approach to empirically examine the effect of question & answer elements, which exist only on one platform, on product sales. Interestingly, we find that, controlling for everything else, question elements negatively affect product sales while answer elements, particularly the depth of the answers, have a positive impact on sales. However, as we focus on the initial sales, it turns out that the number of questions and the fraction of questions that have at least one answer positively influence the sales. We also find that there is an interaction between Q&A elements and review elements, in that an increase in the number of questions seems to be positively correlated with an increase in the number of reviews in the following period. Meanwhile, an increase in the number of answers appears to reduce the average review length in the subsequent period. Our findings suggest that incorporating the question & answer system could be a potential approach to drive sales. However, it is crucially important for managers to develop appropriate policies to gather necessary answers to questions asked on the platform in order to capitalize on such a system.

In Chapter 4, we provide an analysis of a two-sided platform, which becomes a dominant framework adopted by new Information Technology platforms such as Uber and Airbnb. We develop a game-theoretic model featuring a platform owner who acts as an intermediary that services two types of users to examine the influence of incentive policies the platform owner enforces. Specifically, our main interest is to study the implication of the incentive policy on user behavior and welfare metrics. We find that although the seller welfare always increases with the amount of incentives given by the platform, an adjustment of the incentive allocation policy can also yield similar results in many scenarios. In addition, there exists a case where the platform can increase both the seller welfare and its own welfare without increasing the amount of incentives.