Digital Marketing and Social Media Strategy MBA Course

Param Vir Singh, Carnegie Bosch Professor of Business Technologies and Marketing

Consumer Behavior Undergraduate Business Course

Christopher Y. Olivola, Associate Professor of Marketing

The Cognitive Psychology of Sensitivity to Human Fatalities: Implications for Life-Saving Policies

Christopher Y. Olivola, Associate Professor of Marketing

This research investigates the psychological factors that shape, and often skew, the way people perceive and respond to deadly events, such as the Covid-19 pandemic. Understanding these psychological factors will help policymakers recognize, and ultimately guard against, biases that hinder the deployment of important life-saving policies.
 

The Thought That Counts Is the One We Ignore: How Givers Overestimate the Importance of Relative Gift Value

Jeff Galak, Associate Professor of Marketing

In a recent paper with former doctoral student, Julian Givi, Jeff shows that gift givers should rethink when they give gifts. Whereas most gifts are given on special occasions like birthdays and holidays, to maximize the happiness of gift recipients, with the lowest cost to the gift giver, it turns out gifts on a "random Tuesday" are actually much more advantageous.

Testing Theories of Goal Progress in Online Learning

Joy Lu, Assistant Professor of Marketing

Online educational platforms such as Coursera and Khan Academy increasingly allow learners to progress at their own pace within opt-in and on-demand structures. We build a model that captures how the motivation to consume course content varies over time, and demonstrate how different “learning styles” relate to important downstream outcomes such as final performance and enrollment in additional courses.

Can an AI Algorithm Mitigate Racial Economic Inequality? An Analysis in the Context of Airbnb

Param Vir Singh, Carnegie Bosch Professor of Business Technologies and Marketing

I study algorithmic bias, transparency and interpretability from an economic perspective and investigate the impact of artificial intelligence based solutions in mitigating social inequality. My goal is to develop economic aware machine learning algorithms. In related space, I have quantified the economic value of unstructured data (including text and images) combining deep learning and econometric methods in a number of settings.

Working Paper: Estimating the Informative and Prestige Effects of Celebrity Endorsements: A New CCP Estimator for Discrete Choice Demand Estimation

Tim Derdenger, Associate Professor of Marketing and Strategy

We develop a new approach to model, identify and estimate a dynamic discrete demand model for durable goods with continuous unobserved consumer heterogeneity and unobserved product characteristics using group level market share data. The implementation of our new estimator involves two steps employing nonlinear least squares (NLS) in the first step and two stage least squares (2SLS) in the second. Applying our new method, we separately identify the prestige and informational effects associated with a celebrity endorsement using data from professional golfers such as Tiger Woods, and sales data on golf equipment (drivers).