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The course equips participants with theoretical, methodological, and practical tools to develop high‑quality quantitative research projects in these domains. Participants learn how to move from an early‑stage research idea to a coherent research design, how to operationalize key constructs in I&E contexts, and how to select appropriate empirical strategies. Special emphasis is placed on understanding methodological standards in leading innovation, management, and entrepreneurship journals.
Through lectures, discussions, and hands‑on exercises, participants deepen their understanding of how to design robust empirical studies, identify credible sources of variation, handle common empirical challenges, and critically evaluate existing quantitative I&E research.
After completing this course, participants will be able to:
- Develop theoretically grounded research questions in innovation and entrepreneurship and articulate why they matter for academic and practical relevance.
- Translate conceptual ideas into testable hypotheses and structure them within a coherent quantitative research design.
- Select and justify appropriate empirical methods commonly used in innovation and entrepreneurship research (e.g., surveys, experiments, archival data, mixed data sources).
- Operationalize key constructs in I&E contexts and understand the challenges of measurement, construct validity, and data quality.
- Identify credible identification strategies and evaluate potential threats to causal inference in entrepreneurial or innovation-driven settings.
- Critically assess empirical I&E studies, including theory development, research design, data, and analytical strategy.
- Develop and present a refined empirical research proposal, aligned with their doctoral project and meeting the standards of leading journals in the field.
Anmeldefrist: January 17, 2027