Klaus Miller

Klaus Miller joined the Faculty of Economics and Business Administration at Goethe University in Fall 2015, as an Assistant Professor of Quantitative Marketing.

His research interests meet at the interface of empirical quantitative marketing, management economics, and information systems. Specifically, his research is concerned with pricing and advertising issues in two-sided markets, foremost the digital economy. Methodically, Klaus Miller´s research is based on quantitative empirical modeling, applied econometrics, distributed statistical computing, causal machine learning, as well as large-scale lab- and field-experiments. His research has been published in top-tier academic journals (e.g., the Journal of Marketing Research, the International Journal of Research in Marketing, and the Journal of Product Innovation Management) as well as management-oriented journals (e.g., Marketing Review St. Gallen, GFK Marketing Intelligence Review). In Frankfurt he currently teaches courses on Pricing and Data Science & Business Analytics.

Klaus Miller earned a Master’s degree in Business Administration from the Catholic University of Eichstaett-Ingolstadt (WFI School of Management), Germany in 2005 and a PhD (summa cum laude) in Management Economics in 2008 from the University of Berne, Switzerland. During his PhD, as a postdoctoral scholar and assistant professor, he frequently visited the Wharton School of the University of Pennsylvania (Host: Prof. Dr. Dr. Z. John Zhang) and the Graduate School of Business at Stanford University (Hosts: Prof. Dr. Harikesh S. Nair, Prof. Dr. Navdeep S. Sahni).

Before joining Goethe University, Klaus Miller was an Assistant Professor of Marketing at the University of Berne, Switzerland from 2008 to 2011. From 2013 to 2014, he lectured on Quantitative Methods and Models in Marketing at the University of Zurich, Switzerland.

From 2011 to 2015 he suspended his academic career to serve as Head of Business Intelligence and Analytics at Ringier AG, a leading Swiss media- and entertainment cooperation based in Zurich.

Research Topics

• Quantitative and Data-driven Methods in Marketing
• Two-sided Markets and Digital Platform Economics
• Customer Lifetime Value-Based Customer Acquisition
• Demand Estimation and Consumer Choice Models
• Pricing and Willingness-to-Pay
• Advertising Effectiveness
• Data Privacy & Regulation
• Data Science & Business Analytics
• Online Retailing
• Research Methods

Empirical Modeling * Applied Econometrics * Distributed Statistical Computing * Causal Machine Learning * Large-scale Field- and Lab-Experiments

Skills * Statistical Computing: R, Python, Stata

• Cloud Computing: Amazon Web Services (AWS), Amazon Simple Storage (S3), Amazone Elastic Map Reduce (EMR), Amazon Elastic Cloud (EC2), Amazon Redshift

• Big Data Analysis: Apache Hadoop, Apache Spark

• Web Analysis: Google Analytics, Google Tag Manager, Adobe Analytics, Adobe Tag Manager

• Online Experimentation: Adobe Test & Target, Optimzely

• Languages: English | German | French

Selected Publications

Hofstetter, R., Miller, K.M., Krohmer, H., Zhang, J. (2020), A De-Biased Direct Question Approach to Measuring Consumers' Willingness to Pay, Forthcoming at International Journal of Research in Marketing.

Hofstetter, R., Miller, K.M., Krohmer, H., Zhang, J. (2013), How Do Consumer Characteristics Affect the Bias in Measuring Willingness to Pay for Innovative Products?, Journal of Product Innovation Management, 30(5), 1042-53.

* Write Ups: Marketing und Kommunikation

Miller, K.M., Hofstetter, R., Krohmer, H., Zhang, J. (2011), How Should We Measure Consumers? Willingness to Pay? An Empirical Comparison of State-of-the-Art Approaches, Journal of Marketing Research, 48(1), 172-184.

* Appendix: JMR Web Appendix 
* Write Ups: GFK Marketing Intelligence Review, Marketing Review St. Gallen