Welcome to my Research Repository

Here, you will find a curated selection of research papers focusing on marketing, data analysis, and innovative methodologies. These papers represent key insights and findings from my academic work, aimed at advancing knowledge and practical applications in the field.

Each paper is carefully chosen to provide value to researchers, students, and practitioners alike, offering unique perspectives and actionable knowledge. Feel free to explore the collection and gain inspiration for your own research and projects.

If you have any questions or wish to discuss a particular topic further, don’t hesitate to reach out via the contact form

Unlocking the Marketing and Sales Potential: Bridging Generative AI with Domain-Specific Data using Retrieval Augmented Generation Architecture

This study examines the security and privacy challenges of generative AI, focusing on Large Language Models (LLMs) and their application to domain-specific data using a retrieval-augmented generation (RAG) architecture. Using data from marketing and sales domains, the RAG approach demonstrated effective strategy suggestions while maintaining data confidentiality and privacy. The findings highlight the need for result aggregation to ensure consistent outputs and showcase the potential of RAG for secure and tailored AI applications.

APPLICATION OF SENTIMENT ANALYSIS AND TOPIC MODELLING IN MARKETING AND MANAGEMENT_ TESLA S

Application of Sentiment Analysis and Topic Modeling in Marketing and Management: TESLA Supercharger Example.

This study explores the integration of sentiment analysis and topic modeling (LDA) to analyze electronic word-of-mouth (eWOM) data from articles and blogs about Tesla’s initiative to expand Supercharger access to other electric vehicle brands. While the overall sentiment was predominantly negative, LDA revealed diverse themes such as charging infrastructure, user experience, stall blockage, and pricing. The findings highlight the value of combining these methods for marketers and businesses to gain deeper insights into sentiment dynamics and thematic structures.

Model Evaluation of post-M&A success metrics in the German biopharmaceutical industry.

This study examines the success metrics of post-M&A activities in German biopharmaceutical SMEs, focusing on their impact on revenue. Using PLS-SEM analysis of survey data from 384 senior managers, the study finds that efficient resource allocation and clinical success rates significantly drive revenue, while economies of scale, scope, and market share have limited impact. The findings highlight the importance of internal efficiencies and innovation over market expansion strategies, offering a novel methodological approach to evaluating post-M&A performance in the industry.

Unlocking the Marketing and Sales Potential: Bridging Generative AI with Domain-Specific D

Publications:

- Leschik, D., Appel, D., Beckers, N., Milicevic, A., Ritz, F. (2025- review process). Exploring AI-Generated Interviews Using the Means-End Chain Model: A Comparative Study with Human-led Interviews. In Springer (Hrsg.) Handbuch Innovatives Marketing 1st. Edition

- Leschik, D., Baums, K., Hartmann, R., Mazurek, J. (2025- review process). Unlocking the Future of Marketing: The Transformative Potential of Spatial Computing. In Springer (Hrsg.) Handbuch Innovatives Marketing 1st. Edition

- Lac, V. Leschik, D. (2024). Unlocking Marketing and Sales Potential: Bridging Generative AI with Domain-Specific Data. In Springer (Hrsg.) Generative AI in Marketing & Sales. Innovative Unternehmenspraxis: Perspektiven, Anwendungsbeispiele, Ethik. 1st. Edition

- Leschik, D., Lac, V. (2023). Application of sentiment analysis and topic modelling in

marketing and management: Tesla Supercharger example. In Laura-Maria Altendorfer et

al. (Hrsg.) Tagungsband Content Marketing 2.0 Marketing & Kommunikation (S. 27-40),

IU Internationale Hochschule

- Leschik, D. (2022 - 2nd Review process). Model evaluation to measure post-M&A success

metrics in the biopharmaceutical industry. Journal of Business Models

- Tigre Moura, F., Leschik D. (2022). Live FM: Fan Monitor Edition 2022 - An analysis of

attitudes and behaviors of music fans in Germany towards technology innovation and

sustainable consumption. IU International University of Applied Sciences

- Tigre Moura, F., Leschik D., Filho S. C., McPherson G., Reid E., (2021). Live FM: Fan

Monitor Edition 2021 - An analysis of attitudes and behavioral trends of music fans in

Germany and Scotland. IU International University of Applied Sciences; University of the

West of Scotland

- Tigre Moura, F., Leschik D., Filho S. C., McPherson G., Reid E., (2020). Live FM: Fan

Monitor Edition 2020 - An analysis of attitudes and behavioral trends of music fans in

Germany and Scotland during the Covid-19 pandemic. IU International University of

Applied Sciences; University of the West of Scotland

- Tigre Moura, F., Leschik D., (2020). Live AM: Artist Monitor Edition 2020 - An analysis of

attitudes and behavioral trends of music professionals in Germany during the Covid-19

pandemic. IU International University of Applied Sciences

- Leschik, D., Rossberger, R., & Oczkowski, E. (2020). M&As in Germany: Measuring

success for the pharma and biotech industries. Journal of Business Strategy

https://doi.org/10.1108/JBS-07-2020-0153

- Leschik, D. (2017). Assessment of Post-Merger and Acquisition Success Factors for

Small- and Medium-Size German Pharmaceutical and Biotechnology Companies, Doctor

of Philosophy, Charles Sturt University.

Presentations:

- Marketing Club Aachen Vortrag (2023): Sentiment Analyse – A Case Study.

- Marketing Content 2.0 Fachtagung München (2023): Application of Sentiment Analysis in Management and Marketing - Tesla Supercharger Infrastructure Example

- Campus Studies Präsentation - IU International University of Applied Sciences (2022): Pilotstudie zur Implementierung eines Marketing Simulationsspiels zur Ergänzung der Hochschullehre.

- Poster Präsentation (2017): Assessment of Post-Merger and Acquisition Success Factors, Technische Hochschule Deggendorf