Vladimir Manewitsch's work focuses on empirical consumer research using inferential and experimental methods. Currently, his research focuses on sustainable consumption. The aim is to provide scientific insights with practical relevance for market transformation towards greater sustainability.
- Do consumers think too linearly? Product labels, cognitive biases und consumption decisions
- Adoption rates for the Contact Tracing App
- Causality in business analytics and mental models
- Bayesian networks and causal graphs for driver analysis
- Marketing-mix-modeling with customer panel data (GfK Brand Simulator)
- Discrete choice models: Evaluation of conjoint designs
- Automatic detection of emotions from facial expressions
- Development and implementation of segmentation approaches
- Nuremberg Institute for Market Decisions, Data Science and Behavioral Science Research
- GfK Verein, Fundamental Research (Focus: Statistiscal methods)
- GfK SE, Data Science
- PhD (Dr. rer. pol.) in Economics at University Erlangen-Nuremberg with focus on multivariate statistics, missing data analysis and causal inference
- Diploma in Economics, University Kiel
- Stoltenberg, B., Unfried, M., & Manewitsch, V. (2022). Better Product Labels for Better Consumer Choices. NIM Marketing Intelligence Review, 14(1), 49-53. https://doi.org/10.2478/nimmir-2022-0008
- Lipovetsky, S., & Manewitsch, V. (2020). Analytical Closed-Form Solution for General Factor with Many Variables. Journal of Modern Applied Statistical Methods, 18(1), 2.
- Buder, F., Dieckmann, A., Manewitsch, V., Dietrich, H., Wiertz, C., Banerjee, A., Acar, O. A., & Ghosh, A. (2020). Adoption Rates for Contact Tracing App Configurations in Germany. NIM Research Report.
- Kaiser, C., Schallner, R., & Manewitsch, V. (2019). Revealing Consumer-Brand-Interactions from Social Media Pictures – A Case Study from the Fast-Moving Consumer Goods Industry. Proceedings of the 21st General Online Research Conference, Cologne.