I am a fifth year Ph.D. candidate in Marketing at the Stanford Graduate School of Business. I will be joining the Marketing department at the University of Rochester Simon Business School as an Assistant Professor in July 2017.
My research applies empirical industrial organization techniques to unique data contexts to analyze questions relevant to academics and firms. Substantively, I am interested in questions related to product strategy (e.g., pricing, advertising, entry) and sustainability marketing.
In my job market paper I examine the lack of price discrimination on new functionality in many software product contexts and the shift away from distinct intertemporal product versions in this industry. In a second stream of research, together with Wesley Hartmann and partnering water agencies, I am working to understand how advertising and automation technology can be used to shift short and long-term water usage. In my paper co-authored with Wesley Hartmann and Sridhar Narayanan, I study product entry into new markets by exploring the dynamics in post-entry payoffs and the potential for the entrant to assess them ex-ante.
In many durable good contexts, firms have the opportunity to price discriminate on quality by charging higher prices for the latest functionality. In the software good market, on the other hand, we often do not observe price discrimination on the latest versions, despite new versions being introduced over time. I propose that the software firm's ability to price discriminate on latest functionality is restricted by two factors: (1) the extent to which consumers value the innovation from one version to the next and (2) the extent to which legacy software products are costly for the firm to maintain. To analyze this question, I use a unique dataset on individual consumer subscriptions to a Fortune 500 firm's software products. The firm releases new product versions each year, but allows consumers to adopt the latest functionality for free. Despite this policy, descriptive analysis reveals that consumers frequently choose not to upgrade, electing to renew legacy versions of the product instead. To distinguish between the different factors driving this pattern, I develop a dynamic model of consumer choice of different product versions, renewal opportunities and upgrades. This model allows me to separately account for version usage utility, non-monetary costs of purchasing and upgrading and the heterogeneity therein. The estimates of the model reveal that although the majority of the consumers value the new versions, the high value, price insensitive consumers do not, causing it to be unprofitable for the firm to price latest functionality at a premium. Using the estimates and the structure of the model, I further describe a counterfactual that allows me to quantify how much a firm must innovate in order to be able to price new functionality at a premium when legacy versions are costly. The final counterfactual allows me to calculate the minimum legacy version cost that would cause the firm to shift from releasing distinct intertemporal versions to maintaining one continuously upgraded version of the product.
Together with Wesley Hartmann and partnering water agencies, I am working to understand how advertising and automation technology can be used to shift short and long-term water usage. The broad policy motivation for this project is the California drought, and we use this policy context to tackle two sets of research questions. In one paper, we implement an online advertising field experiment, in collaboration with a Southern California water agency, Facebook and Rachio, a WiFi enabled automated sprinkler manufacturer. The goal of the experiment is to better understand which type of advertising content and message sequences are best able to drive short and long-run reductions in residential water usage. This paper therefore contributes to the growing literature on advertising content and the mechanisms through which advertising leads to consumer behavior changes. In a second paper, we implement a large-scale field experiment in collaboration with a Northern California water agency and Rachio. We expect to illustrate how home automation technology can improve the efficiency with which scarce resources are consumed, and thereby contribute to the nascent literature on home automation.
Introducing new products involves weighing the immediate sunk costs of entry against the post-entry stream of returns. The entrant's uncertainty lies in the latter: will realized demand be sufficient to provide a reasonable return on the upfront investment? This paper explores dynamics in post-entry payoffs and the potential for the entrant to assess them ex-ante in the context of In-N-Out Burger entry into the Texas market. We seek to understand how consumer learning about the new entrant and brand loyalty for incumbents impact the demand for the product over time and, in turn, influence entry decisions. Thus, our work is positioned at the intersection of the entry literature and literature documenting the drivers of brand preferences. We also consider both observable and unobservable heterogeneity in consumer preferences, noting that, in the present research, heterogeneity in preferences is in itself an object of interest. By identifying the consumers who value the new product most, and the markets in which these consumers reside, the new product entrant can better identify other promising markets of entry, both in terms of the short-run and long-run outcomes. Additionally, by understanding the impact of strategic levers at the new entrant's disposal (e.g., marketing, store roll-out), we can further address questions about how the firm should behave upon entry.