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

30 Pages Posted: 19 Dec 2018 Last revised: 22 Dec 2020

See all articles by Khai Chiong

Khai Chiong

University of Texas at Dallas - Naveen Jindal School of Management

Matthew Shum

California Institute of Technology

Ryan Webb

University of Toronto

Richard Chen

Happy Elements, Inc.

Date Written: September 16, 2020

Abstract

Endogenous response time data is 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 ex- plain 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 manipu- lating attention towards an advertisement. Counterfactual simulations predict that requiring users to watch some portion of the ad — as is the practice of some online platforms (e.g. YouTube) — generate only modest increases in click-through rates and revenue.

Keywords: Mobile advertising, Attention, Drift-diffusion model, Response times, Video advertisements, Skippable ads

JEL Classification: L81, M37, D03, D83, D87, C15, C22

Suggested Citation

Chiong, Khai and Shum, Matthew and Webb, Ryan and Chen, Richard, Combining Choice and Response Time Data: A Drift-Diffusion Model of Mobile Advertisements (September 16, 2020). Available at SSRN: https://ssrn.com/abstract=3289386 or http://dx.doi.org/10.2139/ssrn.3289386

Khai Chiong

University of Texas at Dallas - Naveen Jindal School of Management ( email )

P.O. Box 830688
Richardson, TX 75083-0688
United States

Matthew Shum (Contact Author)

California Institute of Technology ( email )

Pasadena, CA 91125
United States

Ryan Webb

University of Toronto ( email )

105 St. George Street
Toronto, Ontario M5S 3E6 M5S1S4
Canada

Richard Chen

Happy Elements, Inc. ( email )

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
284
Abstract Views
1,669
rank
127,779
PlumX Metrics