Tor Rolfsen Grønsund
Overview
My research relates to emergent digital technology phenomena, including datafication, AI/machine learning, surveillance, and its consequences. Currently I'm undertaking my doctoral training on the transformation to a new generation of companies (data or AI/ML companies) and how they organize to create value and strategic advantage from data. My training is primarily within qualitative interpretative research, with a preference for in-depth case studies and process-oriented perspectives, yet I'm open to other approaches such as design research, ethnography, and mixed-methods involving digital trace data.
In my teaching within entrepreneurship and technology and innovation management, I focus on processual and practice-based approaches to new product and market development under conditions of uncertainty. I have developed multiple courses and a framework (combining lean startup/iterative agile processes and business model structures) which ideas have been translated to and adopted by top international universities, global corporations, startup accelerators, and government agencies.
Teaching (responsible)
Teaching (modules)
- ITLED4290 - Technology and innovation management (S15-)
Publications
Grønsund, T. (2021). Assembling Algorithmic Decision-Making under Uncertainty: The Case of 'Edge Cases' in an Open Data Environment. In Proceedings of the 54th Hawaii International Conference on System Sciences (p. 5657).
Grønsund, T., & Aanestad, M. (2020). Augmenting the algorithm: Emerging human-in-the-loop work configurations. The Journal of Strategic Information Systems, 29(2), 101614.