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. This paper was accepted by David Simchi-Levi, behavioral economics and decision analysis. Funding: R. Webb work was supported by Social Sciences and Humanities Research Council [Grant 430-2019-00246]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4738 .