Research Methods in Information Systems

Course Content

Introduction to IS research (Christian Meske, RUB)

This introductory session will kick off the course by discussing the fundamentals of science and provide an overview of research and research methods in our field. It will cover an initial understanding of science and how a research discipline creates scientific progress. It will provide an overview of the information systems field and discuss which forms of scientific knowledge exist in the discipline. It will further provide an overview of the publication process and a short introduction into reviewing. This session will end with an outline of IS research methods, which will be covered in the following sessions in detail.

Reviewing Literature for Theory Development (Christian Janiesch, TUDO, Ralf Plattfaut UDE)

This session aims to highlight the critical role literature reviews play in scholarly research and theory formulation. It offers an opportunity for PhD candidates to engage with the complexities of synthesizing and integrating academic literature for the advancement of theoretical frameworks. During this seminar, participants will be exposed to various strategies, methodologies, and tools essential for systematically reviewing literature, analyzing existing theories, identifying gaps, and developing cogent theoretical frameworks. It will highlight and discuss different contemporary literature scoping and review as well as literature processing and analysis methods relevant to the IS domain. This baseline comprises the methods of vom Brocke et al. (2015) and Boell & Cecez-Kecmanovic (2014) as well as Nickerson et al. (2013). Further guidance will be given on the topic of meta synthesis, archetype development, and the editorial requirements when submitting to review journals such as ACM CSUR and IJMR.

Data- and Network Analysis (Hannes Rothe, UDE)

We will introduce participants to explanatory and exploratory quantitative research methods with a focus on network analysis. They will learn about research procedures for quantitative data analysis, ranging from data understanding & preparation, visualization, analysis, to evaluation. The tutorial includes practical application along these steps. For that purpose, we engage with different sources of web-based data, discuss alternative data sourcing strategies, and ways of producing analysis pipelines. In a deeper dive, participants learn methods of network analysis on micro-, meso- and macro-level for which the workshop introduces some general concepts and mechanisms of network theory.

Structural Equation Modeling (Frederik Ahlemann, UDE)

Participants will be introduced to the general approach of structural equation modeling (SEM) and how it links to theory testing. Participants will learn the basic elements of a structural equation models and alternative approaches to measurement (reflective versus formative). They will get insights into the basic steps of model development, testing and interpretation of results. The course will explore fundamental quality criteria for structural and measurement models and show how they are examined in order to test models based on empirical data. The course will also cover different approaches to model validation (component based versus covariance-based). In the second half of the course, students will have the opportunity to apply what they have learned using SmartPLS and a small demo dataset.

Qualitative Research (Manuel Wiesche, TUDO)

Participants will develop an understanding of qualitative exploratory research methods including case studies and grounded theory methodology. They will understand when such methods should be applied and which critical decisions and which challenges arise. Students will learn how the methods can be applied to research projects in the Information Systems (IS) field. Participants will further understand the espoused goal of theory development for novel phenomena but also other contexts in which qualitative-exploratory approaches can be helpful. Participants learn about the key methodological procedures and how they are applied in the IS context. Cumulatively, this session seeks to provide participants with a thorough understanding of qualitative-exploratory research methods to navigate the existing procedural heterogeneity and variance in types of qualitative methods in IS research.

Design Science Research (Jens Pöppelbuß, RUB, Christian Janiesch, TUDO)

Participants will develop an understanding of design science research as one of the main research paradigms in Information Systems with a long tradition, especially in Germany. They will discuss how this research paradigm is different to behavioral research, but also how it can be reasonably integrated with it or at least complement it. Design science research intends to create new and innovative artifacts, including constructs, models, methods, and instantiations (e.g., software and hardware). Participants will learn about these different types of artifacts and discuss under what circumstances these can be considered valuable knowledge contributions to academia (knowledge contribution types and contribution framework; Gregor & Hevner 2013). They will also be introduced into widely accepted process models and guidelines for conducting design science research (Hevner et al. 2004, Peffers et al. 2008). The importance of and different approaches to artifact evaluation will be discussed. Further, the concepts of design theory and design principles will be introduced. They refer to growing attempts to abstract from specific artifact design projects towards generalizable design knowledge. Finally, a publication schema for design science studies (Gregor & Hevner 2013) as well as the anatomies for design theories (Gregor & Jones 2007) and design principles (Gregor et al. 2020) will be presented to guide the write-up process of design science research projects.

Introduction to the Philosophy of Science for Business Information Scientists (Reinhard Schütte, UDE)

The philosophy of science is commonly classified as a sub-discipline of philosophy and deals with the conditions and assumptions under which scientific knowledge arises and endures. Thus, the philosophy of science forms the basis of every single science. The course will outline the basic issues of philosophy of science, ontology, epistemology, and methodology, and demonstrate the importance of positioning at the meta-level in order for statements to hold at the object-level. Some research areas of business informatics are problematized in terms of their basic positioning, and the options for young scholars of business informatics to find solutions in the thicket of philosophy of science are shown.

Experimente und Kausalität (Mario Schaarschmidt, UDE)

Experiments are a well-suited method for empirically investigating cause-and-effect relationships. The course on Designing Experimental Studies focuses on key decisions in designing and conducting experiments. Participants will gain clear insight into the usefulness of experiments, the basics of experimental design, and “best practices” for conducting experiments, including a discussion on the effect of subject pool and incentives. The goal is to develop an understanding of the logic behind an experiment as well as provide ideas and practical advice for conducting experiments. The course is offered in an interactive manner and includes examples from current research to enhance both conceptual knowledge and practical application of experimental research.