I am an Associate Professor in the Department of Marketing Management at the Rotterdam School of Management, Erasmus University.

My research considers substantive problems related to new media and the Internet, as well as the entertainment industry. From a theoretical perspective, I am most interested in information's dual role as: 1) something whose acquisition can reduce uncertainty about future consumption, and 2) something whose acquisition provides utility directly to consumers. Methodologically, my primary research tools are Bayesian econometrics and structural modeling.

Active Projects

The Effect of Links and Excerpts on Internet News Consumption
With Carl Mela and Ron Shachar
Manuscript + Technical Appendix
Previously circulated under the title "Hyper-Media Search and Consumption"
Measuring the Effects of Experimental Costs on Sample Sizes
Advertiser Learning in Internet Ad Networks
With Carl Mela and Santiago Balseiro
Iowa Primaries
With Ron Borkovsky and Andrew Ching
Experimenters Using Online Subject Pools
With Gabriele Paolacci

Recent Projects

When Kerry Met Sally: Politics and Perception in the Demand for Movies
With Ron Shachar
Full working paper version
Management Science manuscript
Summary article for RSM Discovery magazine
Management Science version
Video of me sitting in a movie theater discussing the results
Lead article in Management Science 60(7)
A Key Word History of Marketing Science
With Carl Mela and Yiting Deng
Marketing Science version

Recent Blog Posts

Politics and perception in the demand for movies 2014-06-25

My paper with Ron Shachar, When Kerry Met Sally: Politics and Perception in the Demand for Movies, has been accepted for publication at Management Science and is available for download via Articles in Advance. I've also filmed a short video in which I talk about the main results, and co-authored (with Imogen Moore) a brief summary article.

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I am a Fan of Stan 2013-10-07

Stan is an application framework for building Monte Carlo samplers. Superficially, it looks a lot like BUGS (or JAGS): you define a model using an R-like syntax and then...magic!...samples appear. But that's where the similarities end.

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