Senior Researcher
Dr. Vladimir Manewitsch
Vladimir Manewitsch's work focuses on empirical consumer research using inferential and experimental methods. His research currently focuses on the role of AI in consumer decisions. The aim is to gain scientific insights that have practical relevance for digital and sustainable market transformation.
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Recent Projects
- AI-generated respondents
- The Human Factor in Virtual Influence
- Trust: How Does Eye Contact Influence the Relationship Between Humans and Robots in Purchase Decisions?
- 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
Short CV
- 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
Selected publications
- Kaiser, C., Kaiser, J., Manewitsch, V., Rau, L., & Schallner, R. (2025, June). Simulating Human Opinions with Large Language Models: Opportunities and Challenges for Personalized Survey Data Modeling. In Adjunct Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization (pp. 82-86).
- Kaiser, C., Schallner, R., Manewítsch, V., & Fenne, E. (2024). The Role of Eye Contact in Human-Robot-Interaction: Trust and Decision Making in Virtual Financial Advisory. Proceedings of the The 32nd European Conference on Information Systems, Cyprus.
- Kaiser, C., Manewitsch, V. & Schallner, R. Designing Influence: How Cartoonish and Humanlike Characters Shape Consumer Decisions. NIM Marketing Intelligence Review, 2025, Sciendo, vol. 17 no. 1, pp. 48-53. https://doi.org/10.2478/nimmir-2025-0008
- 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.