Digital Trace Data Research in Information Systems: Opportunities and Challenges

Wurm, Bastian ; Wessel, Michael; Chiarini Tremblay, Monica; Avital, Michel; Hukal, Philipp and Junglas, Iris (2023): Digital Trace Data Research in Information Systems: Opportunities and Challenges. European Conference on Information Systems (ECIS 2023), Kristiansand, Norway, June 11-16, 2023. In: ECIS 2023 Panels. 1,

Abstract

Digital trace data research is an emerging paradigm in Information Systems (IS). Whether for theory development or theory testing, IS scholars increasingly draw on data that are generated as actors useinformation technology. Because they are ‘digital’ in nature, these data are particularly suitable for computational analysis, i.e. analysis with the aid of algorithms. In turn, this opens up new possibilities for data analysis, such as process mining, text mining, and network analysis. At the same time, theincreasing use of digital trace data for research purposes also raises questions and potential issues thatthe research community needs to address. For example, one key question is what constitutes a valid contribution to the body of knowledge and how digital trace data research influences our collectiveidentity as a field? In this panel, we will discuss opportunities and challenges associated with digital trace data research. Reflecting on the panelists’ and the audience’s experience, we will point to strategies to mitigate common pitfalls and outline promising research avenues.

• Item Type: Conference or Workshop Item (Paper)
• Keywords: Digital Trace Data, Computational Social Science, Computational Theory Development, Research Methods
• Faculties: Munich School of Management > Institute for Digital Management and New Media > Process and Algorithmic Management
• Subjects: 300 Social sciences > 330 Economics
• Language: English