Sebastian Tillmanns: Catalogue data in Autumn Semester 2024 |
| Name | Dr. Sebastian Tillmanns |
| Address | Professur f. Technologiemarketing ETH Zürich, WEV G 226 Weinbergstr. 56/58 8092 Zürich SWITZERLAND |
| Telephone | +41 44 632 65 06 |
| stillmanns@ethz.ch | |
| Department | Management, Technology, and Economics |
| Relationship | Lecturer |
| Number | Title | ECTS | Hours | Lecturers | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 363-0305-00L | Empirical Methods in Management | 3 credits | 2G | S. Tillmanns | ||||||||||||||
| Abstract | In this class, students learn how to understand and conduct empirical research. It will enable them to manage a business based on evident-based decision-making. The class includes assignments related to the lecture content. | |||||||||||||||||
| Learning objective | The general objective of the course is to enable students to understand the basic principles of empirical studies. After successfully passing the class, they will be able to formulate research questions, design empirical studies, and analyze data by using basic statistical approaches. | |||||||||||||||||
| Content | Data has become an important resource in today’s business environment, which can be used to make better management decisions. However, evidence-based decision-making comes along with challenges and requires a basic understand of statistical approaches. Therefore, this class introduces problems and key concepts of empirical research, which might be qualitative or quantitative in its nature. Concerning qualitative research, students learn how to conduct and evaluate interviews. In the area of quantitative research, they learn how to apply measurement and scaling methods and conduct experiments. In addition, basic statistical analyses like a variance analysis and how to conduct it in a standard statistical software package like SPSS or R are also part of the lecture. The lessons learned from the lecture will empower students to critically assess the quality and outcomes of studies published in the media and scientific journals, which might form a basis of their managerial decision-making. We recommend the lecture also to students without basic statistical skills, who plan to attend more advanced lectures in the field of artificial intelligence such as Marketing Analytics. The lecture will be taught in presence. There will be individual assignments that students have to solve throughout the lecture. In addition to that, there will be some non-mandatory online exercises as an additional opportunity to prepare for the exam. | |||||||||||||||||
| Literature | Literature and readings will be announced. For a basic understanding we recommend the Handbook of Good Research by Jürgen Brock and Florian von Wangenheim. | |||||||||||||||||
| Prerequisites / Notice | The course includes out-of-class assignments to give students some hands-on experience in conducting empirical research in management. Projects will focus on one particular aspect of empirical research, like the formulation of a research question or the design of a study. Assignments will be graded and need to be turned-in on time as they will be shown and discussed in class. Class participation is encouraged and can greatly improve students' learning. In this spirit, students are expected to attend class regularly and come to class prepared. | |||||||||||||||||
Competencies |
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