On the Value of Coalition Loyalty Programs
This paper examines how coalition loyalty programs enhance firms’ ability to price discriminate and shows why the optimal program size depends on market composition.
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An Empirical Analysis of Optimal Nonlinear Pricing in Business-to-Business Markets
This paper provides a methodology for business-to-business firms to implement nonlinear pricing optimally.
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Leveraging Generative Artificial Intelligence to Create Visual Content in Digital Advertising
Creating high-performing, brand-aligned advertising visuals is challenging; we develop a generative AI framework using Bayesian active learning to efficiently discover effective designs.
Talking Without Speaking: Paid Trolls on Social Media and Court Decision
This article aims to investigate how public opinions and paid trolls may affect the outcome of legal disputes between opposing parties.
The Ripple Effect of Platform Quality Controls in a Submarket: Evidence from a Secondhand Marketplace
Platform quality controls within a submarket have a positive carryover effect on adopters and a U-shaped spillover effect on nonadopters.
Unraveling Multifaceted User Preferences on Digital Platforms: A Bayesian Deep-Learning Approach
This paper proposes a Bayesian deep-learning model that captures multifaceted, time-varying user activities on digital platforms, yielding interpretable and dynamic preference estimations at the platform and individual levels.
Privacy-Preserving Data Fusion
This paper proposes a generative methodology enabling companies to combine data sets with strong privacy guarantees and near-optimal performance in customer analytics.
A Bayesian Dual Clustering Approach for Selecting Data and Parameter Granularities
We propose a Bayesian dual clustering method that infers both data and parameter granularities.