Document Type
Article
Publication Date
6-2025
Keywords
Qualitative research, quantitative research, engaged research, research methods, generative artificial intelligence, computational theory construction
Abstract
Emerging phenomena like the increasing volume and variety of available data, machine learning techniques, and, most recently, Generative AI are reshaping our research practices, affording new research methods for testing and developing theory. In this editorial, we discuss our two major observations from running the 'Next-generation IS Research Methods' Special Issue: (1) the need for research methods that enhance our understanding of complex and dynamic phenomena and (2) Generative AI as (potential) productivity enhancer. We compile these observations into an organizing framework and discuss possibilities for applying Generative AI in the fields of qualitative, quantitative, and engaged research. We highlight challenges that might occur when applying Generative AI in research and shed light on the changing role of researchers in such settings of human-AI collaboration.
Citation
Blohm, I., Miranda, S., Ho, S. Y., & Leimeister, J. M. (2025). Next-generation IS research methods – towards a better understanding of complex and dynamic phenomena … and generative AI as the elephant in the room. Journal of Information Technology, 40(2), 102-121. https://doi.org/10.1177/02683962251340699
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Comments
Web of Science
Wiley