PhD Program

Authors: Thaddeus Neururer, with George Papadakis and Eddie Riedl

This paper investigates alternative models of learning to explain changes in uncertainty surrounding earnings innovations. As a proxy for investor uncertainty, we use model-free implied volatilities; as a proxy for earnings innovations, representing signals of firm performance likely to drive investor perceptions of uncertainty, we use quarterly unexpected earnings benchmarked to the consensus forecast. We document that uncertainty declines on average after the release of quarterly earnings announcements and this decline is attenuatedby the magnitude of the earnings innovation. This latter result is consistent with models that incorporate signal magnitude as a factor driving changes in uncertainty. Most important, we document that signals deviating sufficiently from expectations lead to net increases in uncertainty. Critically, this result suggests that models allowing for posterior variance to be greater than prior variance even after signal revelation [e.g., regime shifts in Pastor and Veronesi (Annu Rev Financ Econ 1:361–381, 2009)] better describe how investors incorporate new information.

Paper

Author: Kun Yu

This study examines whether institutional ownership and analyst following affect the value relevance of disclosed versus recognized pension liabilities. Using a sample of firms with pension liabilities that were disclosed under SFAS No. 87 and subsequently recognized under SFAS No. 158 from 1999 to 2007, I find that off-balance-sheet pension liabilities are more value relevant for firms with a higher level of institutional ownership or analyst following in the pre-158 period. More importantly, I find that SFAS No. 158 increases the value relevance of previously disclosed off-balance-sheet pension liabilities for firms with a low level of institutional ownership or analyst following, and that the increase in the value relevance becomes less pronounced for firms with a higher level of institutional ownership or analyst following. Overall, the results are consistent with the view that institutional ownership and analyst following affect the value relevance of disclosed information as well as the valuation difference between disclosed and recognized information. This study also highlights the importance of considering institutional ownership and analyst following in the value-relevance research.

Paper

Authors: Jiye Baek, Jesse Shore and Chrysanthos Dellarocas

Social media have great potential to support diverse information sharing, but there is widespread concern that platforms like Twitter do not result in communication between those who hold contradictory viewpoints. Because users can choose whom to follow, prior research suggests that social media users exist I n “echo chambers” or become polarized. We seek evidence of this in a complete cross section of hyperlinks posted on Twitter, using previously validated measures of the political slant of news sources to study information diversity. Contrary to prediction, we find that the average account posts links to more politically moderate news sources than the ones they receive in their own feed. However, members of a tiny network core do exhibit cross-sectional evidence of polarization and are responsible for the majority of tweets received overall due to their popularity and activity, which could explain the widespread perception of polarization on social media.

Author: Hye Young Kang

Digital platforms have become increasingly central for modern economies, particularly as enablers of entrepreneurial ecosystems. A very large number of firms and entrepreneurs enter these platforms every year to compete in the provision of complementary products. Much of the existing research has focused on platform owners, such as Apple or Amazon. Relatively little is known about the competitive dynamics of platform complementors. My research, composed of three essays, investigates these underexplored “within-platform” competitive dynamics. I study these issues in the context of the Apple iOS and Google Android mobile platforms, using a novel dataset that I have constructed from various sources. In my first essay, I theorize that the unique characteristics of platform complementor markets result in two product strategies being particularly important (beyond traditional success factors): the extent to which complementors imitate features from competitors’ products, and their reaction speed to changes introduced by the platform owner. My results suggest an inverted U-shaped relationship between imitation and performance, and a positive relationship between performance and the speed by which complementors react to owner-induced changes. In my second essay, I focus on the coopetitive dynamics between complementors and the platform owner. In particular, I explore situations in which the platform owner launches products that directly compete with complementor products – what I conceptualize as “intra-platform envelopment.” My theorizing centers on the consequences of such envelopment on the affected complementors, and on the strategic levers that complementors can use to mitigate that impact. I find that the effect of intra-platform envelopment on complementor performance varies with the type of platform governance exercised by the platform owner. In my third essay, I explore the strategic dilemma that platform complementors confront between conformity and differentiation when platform owners introduce platform-wide initiatives.

Author: Sarah Whitley

Decisions to purchase the same product are often driven by different motivations. Personal pleasures (i.e., hedonic motivations) trigger consumption in some cases and functional needs (i.e., utilitarian motivations) drive consumption in others. A new oven is a pleasurable indulgence to some consumers, and merely a necessity of home ownership to others. My dissertation explores how hedonic and utilitarian motivations for consumption impact the first part of this decision process: choosing an assortment. I find that consumers prefer larger assortments for hedonically motivated purchases, but smaller assortments for utilitarian motivated purchases, even when the actual product purchased is the same. Underlying these varying predilections for assortment size are consumer perceptions about the uniqueness of their preferences. Consumers believe what provides them pleasure is unique and different from what others find pleasurable (e.g., minimalist Scandinavian design). In contrast, consumers perceive preferences for utilitarian purchases to be driven by the basic needs they fulfill, which are common to all consumers (e.g., an oven and gas burners). These perceptions of preference uniqueness drive preferred assortment size by influencing how many options consumers feel they will need to review in order to find a product matching their preferences.

Authors: Masha Ksendzova, Grant E. Donnelly, and Remi Trudel

We find that consumers perceive cash to be more helpful than card payments, especially at small businesses. Further, the mechanism underlying both the main effect of payment form and the moderating effect of business size is consumers’ perception of overhead-cost reduction by cash. In making overhead judgments, however, consumers may mistakenly overlook the time-based overhead costs businesses incur from processing cash payments. Finally, we find that perceived helpfulness to a business subsequently increases consumers’ purchase satisfaction. Thus, the use of cash can create additional value for consumers, businesses, and their relationships in recurring transactions.

Author: Yicheng Song

This thesis focuses on the understanding and modeling digital user’s decision journey on various digital systems: multi-channel retailing, online media consumption, and crowdfunding platforms, where technology, people, and firm strategies interact.

The first chapter propose a statistical model based approach to identify characteristic paths lead to purchase from consumers’ activity level datasets. Most digital sellers are faced with these kinds of data but there are few practical and academic approach available to address this problem. Specifically, neither of these streams of research try to reveal how, the characteristic paths through which, the marketing events result in purchase. Managers can use such characteristic paths to purchases to better understand and communicate their customer’s shopping behavior—this need is highlighted in trade publication articles. I offer one of the first approaches to extract such paths. I demonstrate that this approach is more effective at predicting individual users’ future purchase than numerous alternatives.

The second chapter focus on user’s decision journey within the short span of online media consumption sessions by following their sequential selection of multiple articles within a session. The unique feature of online media consumption is a reader is rarely “done” after consuming one news item, nor does she feel limited in a given session to selecting from only one of the numerous categories available, which is quite different from the first scenario, where a consumer typically chooses only one of several offered physical products on a given consumption occasion. A reader could have a breadth of interests and a general news/media site offers content on a host of categories, which provides an opportunity to fulfill those interests. Such a reader may want to consume multiple items from a diverse set of categories and what is most relevant at each stage of the session could change with her prior consumptions due to the satiation, leading to the variety seeking behavior. I developing a multi-category utility model that captures consumers’ preference towards different types of content, how quickly they satiate with one type and substitute it with another, and how they trade off potentially higher value from their own costly search efforts with the convenience of selecting from a recommended list to find new content. Taken together, these three elements enable us to characterize how utility-maximizing consumers seek diversity over the course of a session and how likely they are to click on content recommended to them. Empirical results have that the proposed model could better predict reader’s variety seeking behavior and I also show through policy simulations that using this approach could increase user engagement by 23%.

First two chapters model the process of how digital user use their resources (e.g. money and time) to fulfill their own interests. In the third chapter, we turn to the scenario to model decision journey of digital users to help others, where the contributors are both budget and time bounded. I develop a model to understand donors’ path-of-contribution on education crowdfunding platforms based on various theories: from receiving and processing donation requests, visiting the crowdfunding platform, to selecting a set of candidate projects, and to making donation decisions, which enable proposed model to accurately estimate the donor’s future return and their donation behaviors. Finally, using a set of policy simulations, I show that the platform can use our model to design optimal personalized promotion strategies—by suggesting projects to the donors that are likely to create higher utility for the donors—while maximizing realized funding by taking a global view of all available projects and existing donors’ interests.