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Fernbach, Philip M Assistant Professor

Positions

Research Areas research areas

Research

research overview

  • 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

Publications

selected publications

Teaching

courses taught

  • MKTG 3050 - Customer Analytics 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. (Spring 2019 UC Boulder)
  • MKTG 3350 - Marketing Research and Analytics 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. . (Spring 2019 UC Boulder)
  • MKTG 8990 - Doctoral Thesis - (Spring 2019 UC Boulder)
  • MSBX 5310 - Customer Analytics Provides a deep understanding of customer centricity and its implications for the firm; state-of-the art methods for calculating customer lifetime value and customer equity; analytical and empirical skills that are needed to judge the appropriateness, performance, and value of different statistical techniques that can be used to address a issue around customer acquisition, development, and retention. Students will use their knowledge of R programming in this course. (Fall 2018 UC Boulder)
  • MKTG 8990 - Doctoral Thesis - (Fall 2018 UC Boulder)
  • MKTG 8990 - Doctoral Thesis - (Summer 2018 UC Boulder)
  • MKTG 3050 - Customer Analytics 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. (Spring 2018 UC Boulder)
  • MKTG 3350 - Marketing Research and Analytics 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. . (Spring 2018 UC Boulder)
  • MKTG 8990 - Doctoral Thesis - (Spring 2018 UC Boulder)

Background

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