Prof. Dr. Damian Leschik
Professor of B.A. Business Administration & MBA
Profile
Prof. Dr. Damian Leschik is Professor of Marketing Management at IU International University of Applied Sciences, teaching on the Business Administration and MBA programmes at Campus Cologne. He holds a doctorate in Business Administration from Charles Sturt University in Australia, where his thesis was awarded the Joss Group Outstanding Thesis Prize. He combines many years of university teaching with around 15 years of industry experience in production, marketing and business development at international companies including Paion, Lanza and tesa Labtec, and he advises organisations on artificial intelligence, data science and market research. His research examines the use of artificial intelligence in marketing research, in particular silicon sampling, alongside data science methods and consumer behaviour.
Research Areas
Artificial intelligence in market research and silicon sampling
Data science for consumer insights
Generative AI in marketing and sales
Consumer behaviour and value propositions in immersive environments
Publications and Presentations
Leschik, D., Baums, K., & Mazurek, J. M. J. (2026). Unlocking the future of marketing: The transformative potential of virtual reality, augmented reality, and spatial computing. In G. Schuster & C. Bornemeyer (Eds.), Handbuch innovatives Marketing (pp. 1-13). Springer Gabler. https://doi.org/10.1007/978-3-658-46709-8_33-1
Leschik, D., Ritz, F., Milicevic, A., Appel, D., & Beckers, N. (2026). Exploring AI-generated interviews using the means-end chain model: A comparative study with human-led interviews. In G. Schuster & C. Bornemeyer (Eds.), Handbuch innovatives Marketing (pp. 1-17). Springer Gabler. https://doi.org/10.1007/978-3-658-46709-8_41-1
Leschik, D. (2025). Model evaluation of post-M&A success metrics in the German biopharmaceutical industry. Journal of Business Models, 13(1), 146-167. https://doi.org/10.54337/jobm.v13i1.7502
Leschik, D., & Lac, V. (2024). Unlocking the marketing and sales potential: Bridging generative AI with domain-specific data using retrieval augmented generation architecture. In Generative Künstliche Intelligenz in Marketing und Sales. Springer Gabler. https://doi.org/10.1007/978-3-658-45132-5_15