Matt Meister

Assistant Professor Matt Meister studies consumer judgment and decision-making. Matt's research is particularly focused on how consumers communicate their experiences, and learn about the experiences of others. Matt is also a keen proponent of open science, both for replicability and collaboration. All data and code used in his research is available through his website (mattmeister.com). This includes python code for web-scraping, and the R package specster, a set of flexible, multicore functions to create specification curves to test robustness of statistical results.

As an instructor, Matt loves to teach statistics and data analytics. These classes focus on building intuition for topics like regression, ANOVA, and more advanced econometrics and machine-learning. Then, this intuition is tested through hands-on work in R.

Prior to USF, Matt received a PhD in Marketing from the University of Colorado Boulder, and an undergraduate degree in Business Administration from the Ivey Business School at Western University in London, Ontario. He also worked in Data Analytics at Pelmorex Inc. in Oakville, Ontario. Outside of work, Matt's great interests are jam bands and Toronto sports.

• Behavioral research methods
• Quantitative social science
• Web-scraping
• R Programming

• Judgment and Decision-Making
• Consumers' Evaluations of Products
• Consumer Financial Decision-Making
• Open Science

• University of Colorado Boulder, PhD in Marketing, 2023
• Ivey Business School at Western University, HBA, 2018

• CARD/Ipsos Dissertation Proposal Competition Runner-up

• Are User-Generated Ratings a Good Point of Comparison?
• Quality in Context: Evidence That Consumption Context Influences User-Generated Product Ratings