Professor Fernbach's research interests deal with many aspects of consumer judgment and decision-making. Much of his work is inspired by causal model theory, the idea that people's judgments and decisions are based on knowledge of the world, knowledge that is represented in terms of causal structure. He also often uses mathematical modeling in his work and aims to create models that are simple, psychologically plausible and have minimal free parameters. He is currently active in research topics including explanation and subjective knowledge, causal reasoning and learning, self-deception, consumer planning, consumer financial decision-making, and antecedents of online consumer reviews.
keywords
Consumer behavior, judgment and decision-making, consumer research, cognitive psychology, cognitive science, computational modeling, marketing, marketing research
MBAX 6380 - Consumer Decision-Making: Behavioral Economics, Psychology, and Experimental Desi
Primary Instructor
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Spring 2021 / Spring 2022 / Fall 2022 / Fall 2023 / Fall 2024
Consumer behavior often defies economic rationality. Behavioral economics attempts to integrate the quirks of human psychology into economic models; judgment and decision-making investigates how people solve economic problems. This course will introduce major theories, findings and ideas from these disciplines, and foundational concepts of experiment design that provide insight into consumer decision-making, with the goal of preparing future managers, analysts, consultants, and advisors to incorporate such insights into marketing and business strategies.
MBAX 6381 - Consumer Decision-Making: Behavioral Economics, Psychology, and Experimental Desi
Primary Instructor
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Spring 2021
Consumer behavior often defies economic rationality. Behavioral economics attempts to integrate the quirks of human psychology into economic models; judgment and decision-making investigates how people solve economic problems. This course will introduce major theories, findings and ideas from these disciplines, and foundational concepts of experiment design that provide insight into consumer decision-making, with the goal of preparing future managers, analysts, consultants, and advisors to incorporate such insights into marketing and business strategies.
MKTG 3050 - Customer Analytics
Primary Instructor
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Spring 2018 / Spring 2019 / Spring 2021 / Fall 2021 / Fall 2022 / Fall 2023 / Spring 2024
Students develop a deep understanding of customer centricity and its implications for the firm, learn about state-of-the-art methods for calculating customer lifetime value and customer equity and develop the analytical and empirical skills that are needed to judge the appropriateness, performance and value of different statistical techniques that can be used to address issues around customer acquisition, development and retention.
MKTG 3350 - Marketing Research and Analytics
Primary Instructor
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Spring 2018 / Spring 2019
Explores fundamental techniques of data collection and analysis used to solve marketing problems. Specific topics include problem definition, planning an investigation, developing questionnaires, sampling, tabulation, interpreting results, and preparing and presenting a final report. Required for marketing majors. .
MSBX 5310 - Customer Analytics
Primary Instructor
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Fall 2018
Provides a deep understanding of how to use data on customer behavior and preferences to inform managerial decision making. Introduces methods for causal inference, modeling consumer demand, and modeling firm decisions. Applications include long-run customer management decisions (customer acquisition and retention) and short-run marketing mix (product, price, promotion and distribution) decisions. The R programming language is used for course examples and assignments. Students are assumed to have a working knowledge of R and linear regression techniques.
