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

Khai Xiang Chiong (), Matthew Shum (), Ryan Webb () and Richard Chen ()
Additional contact information
Khai Xiang Chiong: Naveen Jindal School of Management, University of Texas at Dallas, Richardson, Texas 75080
Matthew Shum: Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, California
Ryan Webb: Rotman School of Management, University of Toronto, Toronto, Ontario M5S3E6, Canada
Richard Chen: Independent Researcher

Management Science, 2024, vol. 70, issue 2, 1238-1257

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.

Keywords: mobile advertising; attention; drift-diffusion model; response times; sequential sampling models (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.2023.4738 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:70:y:2024:i:2:p:1238-1257

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().