This paper examines how data-driven personalized decisions can be made while preserving consumer privacy. Our setting is one in which the firm chooses a personalized price based on each new customer's vector of individual features; the true set of individual demand-generating parameters is...

This study explores the forecasting of Major League Baseball game ticket sales and identifies important attendance predictors by means of random forests that are grown from classification and regression trees (CART) and conditional inference trees. Unlike previous studies that predict sport...

We conduct a lottery experiment to assess the predictive importance of simple choice process metrics (SCPMs) in forecasting risky 50/50 gambling decisions using different types of machine learning algorithms as well as traditional choice modeling approaches. The SCPMs are recorded during a fixed...

Many mobile app providers offer their apps for free and base their business models on user engagement. However, declining app usage over time threatens user engagement and the ability of apps to create business value. To keep users engaged, app providers use gamification, i.e., they link their...

We report the results of surveys we conducted in the US and Israel in 2020, a time when many prices increased following the spread of the COVID-19 pandemic. To assess respondents' perceptions of price increases, we focus on goods whose prices have increased during the pandemic, including some...

We investigate how consumer word of mouth (WOM) develops over time and in turn influences new product adoption. We develop a dynamic aggregate-level model of WOM development and new product diffusion that explicitly captures consumers’ learning of product quality from both marketing...

In recent years there has been a growing stream of literature in marketing and economics that models consumers as Bayesian learners. Such learning behavior is often embedded within a discrete choice framework which is then calibrated on scanner panel data. At the same time it is now accepted...

Discovering the preferences and the behaviour of consumers is a key challenge in marketing. Information about such topics can be gathered through surveys in which the respondents must assign a score to a number of items. In this article we suggest a strategy to analyze such data and achieve this...

Stand-alone marketing models are well-suited to deal with different behavioral features such as variation in transaction frequency (customer heterogeneity with latent classes), recency and attrition (“buy ‘till you die” models), and more general changes in customer transaction rates...