I am an Associate Professor of Marketing in the Rotterdam School of Management at Erasmus University. I earned my PhD from Duke University. My research has been published in Marketing Science, Management Science, and Journal of Marketing Research. I am a past recipient of the INFORMS Society for Marketing Science Dissertation Award.
My substantive research areas centers on entertainment, news, advertising, and digitization, especially settings where information, learning, and other types of adaptation affect choice. I also develop methods to improve causal inference from data generated by field and lab experiments.
PhD in Business Administration (Marketing), 2012
BA in Business Administration, 2005
University of Washington
We present an experimental method for optimizing compliance promotions, which are promotions in which customers must voluntarily participate (e.g. physician detailing, loyalty reward offers, retention campaigns, coupons). This entails an experiment to exogenously vary promotion features, a means to identify which promotion features can be causally extrapolated, an approach to extrapolate those causal effects, and an optimization over the promotion features, conditioned on the extrapolation.
We explore the impact of digitization on community participation across various interest communities. Overall, digitized events have lower prospective participation compared to in-person ones. However, participation varies significantly based on event characteristics and interest topics, suggesting a need for tailored digital community-building strategies.
Direct buy advertisers procure blocks of ad impressions at fixed rates from publishers. To find sites where their ads are effective, they must try many publishers, leading to wasted resources. By pooling advertiser information and recognizing the similarity in performance of ads with similar visual elements, we show substantial gains in advertiser welfare and publisher revenue can be achieved.
We develop a dynamic learning model and fit it to browsing and link data from celebrity news sites. We simulate how banning links affects consumer browsing and find that linking increases celebrity news consumption, especially among consumers who browse the least.
Experimental samples that are too small to detect true effects have plagued the behavioral sciences for years. This study shows how much costs matter for sample size selection by analyzing data describing experiments conducted at a behavioral lab. Click on this card for a link to the manuscript, and an explanation of why I am no longer trying to publish this paper.
We present a predictive model of local demand for movies with two unique features. First, we allow consumers’ heterogeneity to depend on their voting tendencies. Second, instead of relying on genre classifications to characterize movies, we estimate latent movie attributes.
We examine the history of keywords used by articles published in “Marketing Science” to develop insights on the evolution of marketing science as a field.
Pay-for-performance programs score hospitals using process measures organized by therapeutic area. We propose an alternative method for scoring hospitals. Our method reflects how hospitals organize care, is better aligned with patient outcomes, and leaves room for hospitals to improve.