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

    Khai Xiang Chiong,Matthew Shum,Ryan Webb,Richard Chen

    Management Science（2024）SCI 2区

    Univ Texas Dallas | CALTECH | Univ Toronto

    Cited 5|Views4
    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 .
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    mobile advertising,attention,drift-diffusion model,response times,sequential sampling models
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    【要点】：本文将漂移-扩散模型应用于移动广告领域，结合选择和反应时间数据估计用户偏好，并验证了这种信息整合在预测广告效果上的价值。
    

    【方法】：研究采用漂移-扩散模型，将经济选择中的反应时间数据与用户的选择行为相结合，用于分析移动设备上视频广告的用户响应。
    

    【实验】：实验在现实场景中进行，使用数据集来评估广告的效用，并通过对外部样本的广告参与度进行测量来验证模型，预测将广告设置为“不可跳过”对点击率和收入的影响。数据集可通过https://doi.org/10.1287/mnsc.2023.4738访问。