Research Methodology for Innovation and Entrepreneurship

Introduction

Please note that this is a preliminary course description. The final version will be published in June 2026.

This course is designed to help students design and conduct solid, theoretically informed, empirical research in the field of innovation and entrepreneurship. It addresses issues relevant to qualitative and quantitative research and provides a foundation for informed research consumption in courses and independent research production in the master thesis. Students will be exposed to both theory and implementation of established and cutting-edge methodological topics.

The purpose of empirical research in the social sciences in general is to build theories that help us to understand the world. For strategic management in particular, the purpose of empirical research is to understand the myriad issues that pertain to the survival and success of organizations. Good research is both theoretically interesting and persuasive. Persuasiveness depends on whether the empirical evidence presented in the research convinces readers that the author’s arguments and interpretations are likely to be valid. This course aims to help students identify theoretically interesting and researchable topics within the fields of innovation, entrepreneurship, and related disciplines, as well as to increase the students’ ability to design and conduct empirical research that will make their findings persuasive. The knowledge and skills the students are expected to acquire in this course are highly relevant for the task of successfully completing a MSc thesis.

Course content

The course content includes several modules, with topics including:

Research Methodology & Problem Identification

• Introduction to research methods and design
• Research questions: what makes for good research questions?
• Literature review: how to conduct a critical literature review, what to focus on when reviewing the literature you have identified in your literature search, as well as how to report the reviewed literature
• TBD: Library session: understanding of information search strategies, and develop your ability to critically evaluate information sources

Research Design: Constructs, Context, & Measurement

• Research design: common research designs, logic of quasi-experimental research designs, rival hypotheses and crucial tests
• Sampling, selection, concept operationalization and measurement: quantitative data sources, selection bias and case selection, operationalization and measurement, validity, reliability and generalizability issues, common method bias
• Qualitative research and interviewing: what is qualitative research, interviews

Quantitative and Qualitative Data Analysis

• Survey methods and analysis: survey data, sampling and response rates (self- selection, generalizability issues), measurement scales, survey items (validity and reliability issues)
• Qualitative data analysis: Developing propositions, developing a process model, coding and inductive analysis of texts
• Observation, document analysis and case studies
• Database/archival methods and analysis: Sampling, Creating your own database, variable construction, model building, statistical analysis
•  Approaching the empirical setting, getting and working with the data, approaching the empirical setting, ethical guidelines for research, consent forms, non-disclosure agreements

Module on quantitative analysis and experiments (shared 3 sessions)

• Experimental setup, scenario and parallel design, AB testing, t-tests (comparisons of two groups), Anova, Ancova, Effect sizes.

Machine Learning, Textual Analysis, and Other Methods (shared 3-4 sessions)

• Machine learning, AI, and text analysis
• Social Network Analysis
• Simulation modelling