The Ethnography Atelier podcast discusses research methods with accomplished qualitative researchers. We talk to guests about their experiences of conducting research in and around organizations, the challenges they faced and the understandings they gained. If you have comments about the podcast or you'd like to get involved, please contact us.
Episode 12 - Stine Grodal: Archival Methods
Pedro Monteiro and Audrey Holm • March 2022
In this episode with Professor Stine Grodal, we explored the promises and challenges of archival research. We discussed Stine’s use of archival methods in contexts such as nanotechnologies or the tobacco or hearing aid industry. Stine reflects on the kinds of research questions best addressed with archival data and provides specific sampling and analytical strategies researchers can take to approach archival datasets. She also shares advice on where to look for archival data, how to start, when to combine archival research with other research methods, and the benefits of being creative in our methodological approach.
Stine Grodal is Distinguished Professor at Northeastern University D'Amore-McKim School of Business in the department of Entrepreneurship and Innovation. She received her PhD from Stanford University in Management Science and Engineering. Stine examines the emergence of categories in nascent markets and the strategic actions market participants take to create and exploit these emerging social structures.
Hsu, G. and Grodal, S. 2021 The double-edged sword of oppositional category positioning: A study of the U.S. e-cigarette category, 2007-2017, Administrative Science Quarterly, 66(1): 86–132
Grodal, S. 2018. Field expansion and contraction: How communities shape social and symbolic boundaries. Administrative Science Quarterly, 13(4): 783–818.
Kahl, S. and Grodal, S. 2016. Discursive strategies and radical technological change: Multilevel discourse analysis of the early computer (1947-1958), Strategic Management Journal, 37(1): 149-166.
Langley, A. 1999. Strategies for Theorizing from Process Data. The Academy of Management Review, 24(4): 691.