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Published June 22, 2023 | public
Journal Article

Combining Choice and Response Time Data: A Drift-Diffusion Model of Mobile Advertisements

Abstract

Endogenous response time data are increasingly becoming available to applied researchers of economic choices. However, the usefulness of such data for preference estimation is unclear. Here, we adapt a sequential sampling model—previously validated to jointly explain subjects' choices and response times in laboratory experiments—to model users' responses to video advertisements on mobile devices in a field setting. Our estimates of utility correlate positively with out-of-sample measures of ad engagement, thus providing external validation of the value of incorporating endogenous response time information into a choice model. We then use the model estimates to assess the effectiveness of manipulating attention toward an advertisement at the beginning of a decision. Counterfactual simulations predict that making an ad "nonskippable" (requiring users to watch some portion of the ad)—as is the practice of some online platforms (e.g., YouTube)—generates only modest increases in click-through rates and revenue.

Additional Information

© 2023 INFORMS. The authors thank Colin Camerer, John Clithero, Cary Frydman, Lawrence Jin, Shijie Lu, Rosemarie Nagel, Whitney Newey, Ram Rao, David Reiley, Xiaoxia Shi, Jakub Steiner, Colin Stewart, Tomasz Strzalecki, Pengfei Sui, and Raluca Ursu as well as seminar attendees at Berkeley (Haas), Caltech, Chinese University (Hong Kong), Duke (Fuqua), Hong Kong University of Science and Technology, Hong Kong Baptist University, Ohio State, Princeton, Toronto (Rotman), the 2020 Korean Economic Review International Conference, the 2019 Economic Science Association (Los Angeles), the 2019 Workshop on the Economics of Advertising and Marketing (Porto), the 2019 Conference on Structural Dynamic Models (Chicago), and the 2018 California Econometrics Conference (Irvine) for helpful comments. R. Webb work was supported by Social Sciences and Humanities Research Council [Grant 430-2019-00246].

Additional details

Created:
August 22, 2023
Modified:
October 20, 2023