Monic Sun
Assistant Professor of Marketing, Graduate School of Business, Stanford University
Visiting Assistant Professor of Marketing, Marshall School of Business, University of Southern California
Monic Sun conducts research in the realm of Internet marketing by focusing on strategic information transmission. She explores, for example, how companies decide on the optimal amount of product information to provide to their customers, how various elements in the realm of consumer reviews such as the variance of ratings and informativeness of the reviews have an impact on the market outcomes, and how consumers optimally search for product information in a continuous-time framework. She is also interested in how consumers react to monetary incentives and their friends' behavior in online social networks. Professor Sun's research has appeared in leading journals such as Management Science and Journal of Economics and Management Strategy.
Monic Sun received her PhD in Economics from Boston University and joined the faculty of Stanford GSB in July 2008. Prior to joining the PhD program, she obtained a B.A. in economics from Peking University (China). In her spare time, Monic enjoys reading and travelling.
Publications
- Optimal Search For Product Information, with Fernando Branco and J. Miguel Villas-Boas, Management Science, forthcoming
Consumers often need to search for product information before making purchase decisions. We consider a parsimonious model in which consumers incur search costs to learn further product information, and update their expected utility of the product at each search occasion. We characterize the optimal stopping rules to either purchase, or not purchase, as a function of search costs and the informativeness of each attribute. The paper also characterizes how the likelihood of purchase changes with the ex-ante expected utility, search costs, and informativeness of each attribute. We discuss optimal pricing, the impact of consumer search on profits and social welfare, and how the seller chooses its price to strategically affect the extent of the consumers’ search behavior. The paper also considers the impact of searching for signals of the value of the product, of discounting, and of endogenizing the intensity of search.
- How Does Variance of Product Ratings Matter? Management Science, forthcoming
This paper examines the informational role of the variance of product ratings. We first build a theoretical model on how firm strategies and market outcomes respond to product ratings, and find that a higher variance of ratings increases subsequent demand and profit if, and only if, the average rating is low. We then discuss alternative assumptions on consumer behavior and market structure, and show that the primary forces at work in the baseline model are robust in many variations of the model. Finally, we provide some empirical evidence that is consistent with the model. The paper overall provides a unifying framework that helps managers to understand how variance of ratings, through its interaction with the average rating, plays a critical role in shaping consumers’ purchase decisions. It also points out that variance of product ratings can be used as an effective marketing tool in shaping a product’s perceived image among consumers.
- Disclosing Multiple Product Attributes, Journal of Economics & Management Strategy, Volume 20, Issue 1, pp. 195-224, Spring 2011
How do multiple attributes of a product jointly determine a seller’s disclosure incentives? I model a monopolist whose product is characterized by vertical quality and a horizontal attribute. Contrary to the unraveling theory, the monopolist in equilibrium does not always choose disclosure. When the product’s quality is common knowledge, a monopolist with higher quality is less likely to disclose the horizontal attribute. Notably, the monopolist may choose nondisclosure when his product has the highest quality. The results shed light on mandatory disclosure policies and the design of quality surveys.
- A Reflection on Analytical Work in Marketing: Three Points of Consensus, with R. Thomadsen, R. Zeithammer, D. Mayzlin, Y. Orhun, A. Pazgal, D. Purohit, R. Rao, M. Riordan, J. Shin, and J.M. Villas-Boas, Marketing Letters, forthcoming
People make a wide variety of choices as consumers, managers, employers, and regulators. Most of these choices are not made in a vacuum but rather in a context of strategic interactions that make individual payoffs interdependent across the decision makers. This payoff interdependence leads to intertwined individual incentives, necessitating analysis of the entire system before one can predict and understand individual behavior. Analyzing such a complex system requires a precise mathematical framework to develop intuition and qualify theoretical predictions. A commonly used analytical framework is non-cooperative game theory. We present several general points on which the marketing literature rooted in the paradigm of game theory has reached a broad consensus. We also organize the literature according to three broad substantive areas: competition, information, and market rules. This paper is not an exhaustive review of the literature. Instead, we use several particular examples from each area to illustrate the more general points of consensus that characterize the discourse in the literature. The points of consensus we propose are as follows: 1) Equilibrium analysis within an analytical framework is necessary for testing and refining conventional wisdom about situations with strategic interactions. Equilibrium as a solution concept ensures stability of the system under study, and equilibrium behavior can depart sharply from simpler intuition that does not consider the feedback inherent in strategic interactions. 2) Theoretical predictions can be sensitive to details of the modeling assumptions, making general predictions elusive. A trade-off exists between the generality of modeling assumptions and the usefulness of the resulting insights in answering a concrete question in a specific institutional situation. Therefore, more general models are not necessarily “better,” and the appropriate compromise between generality and usefulness depends on the scope of the question. Further, understanding which details significantly affect a theory’s predictions can be informative in its own right. 3) A two-way road should exist between theory and empirics. In one direction, theory can inform data analysis. In the other direction, empirical analysis can inform the assumptions of the theory. Either way, we agree with Bass (1995, p. G12) that science is “a process of interaction between theory and data that leads to higher level explanations.”
- Informal Payments in Developing Countries' Public Health Sectors, with Ting Liu, Pacific Economic Review, forthcoming
In public health sectors of many developing countries, patients offer payments to their doctors outside the official payment channels. We argue that the fundamental cause of informal payments is that formal prices cannot fully differentiate patients' various needs. We compare welfare implications of different policies that can be used to regulate informal payments. Patient heterogeneity plays a central role in the comparison. Compared with banning informal payments, allowing them improves patient welfare if and only if patients' willingness to pay differs significantly. We also show that selling the right to choose physicians publicly always improves both patient welfare and social welfare.
Working Papers
- Ad Revenue and Content Commercialization: Evidence from Blogs, with Feng Zhu
Many scholars are concerned about the impact of ad-sponsored business models on content providers. They argue that content providers, when incentivized by ad revenue, are more likely to tailor their content to attract “eyeballs,” and as a result, popular content may be excessively supplied. We empirically test this prediction by taking advantage of the launch of an ad revenue-sharing program initiated by a major Chinese portal site in September 2007. Participating bloggers allow the site to run ads on their blogs and receive 50% of the revenue generated by these ads. After analyzing 4.4 million blog posts, we find that compared to nonparticipants, the percentage of popular content increases by about 13% on the participants’ blogs after the program takes effect. More than 50% of this increase can be attributed to topics shifting towards three domains: stock market, salacious content, and celebrities. We also find evidence that, relative to nonparticipants, the participants’ content quality increases after the program takes effect.
