The panel aims to present and discuss papers related to digital business history. This includes the use of digitized archives, born-digital sources, relational databases, and programming in business history research, as well as new AI tools for research.
During the last ten years, a slow transformation of research practices among business history scholars has started. There has been much discussion about the need to develop business history methods (Kipping & Üsdiken, 2014; Rowlinson et al., 2014; Vaara & Lamberg, 2016, Decker et al., 2021), and digital methods and sources have been seen as one promising avenue (Putnam, 2016). Until now, there has been a lot of discussion about digitizing archival material, the use of digital sources, and the availability of born-digital sources (Nix and Decker, 2021; Decker et al., 2022), but the methodological side has somewhat surprisingly been left with less attention. Consequently, the possibilities of digital methods and sources remain unrealized. Economic and business history has a long tradition of using digital methods and sources. However, in the case of qualitative research, the development could have been faster (Eloranta et al., 2020). Digitized sources have been used in business history for a long time, which has already transferred a large part of research material from archives to researchers’ computers (Nix & Decker, 2021). Digital history is portrayed as “a methodological approach framed by the hypertextual power of these technologies to make, define, query, and annotate associations in the human record of the past” (Cohen et al., 2008).
At the same time, AI is beginning to be used in research. AI might help researchers with some tasks – including the ability to assemble or categorize large datasets quickly, but it also poses challenges. How do we, e.g., preserve “the Historian’s craft” in the age of AI? How do we ensure that interpretation is not influenced by the black box that is the AI algorithm? That context is not lost?
The session includes both methodological and empirical papers. The papers by Ekholm and Gatti highlight how digital tools can be used in business history research – and also provide empirical applications on early-modern and modern business history. The papers by Fridl and Hyman discuss how AI can be used in business history research and teaching.
Participants
Chair: Pasi Nevaiainen, University of Jyvaskyla
Discussant: Erik Lakomaa, Stockholm School of Economics
Presenters:
Fabio Gatti, University of Bern “Trade and Production Effects of the Plague: The Saminiati and Guasconi Bank of Florence (1626-1634) “
Christoffer Friedl, Stockholm School of Economics “Establishing rigorous digital and AI methodologies for business history research”
Laura Ekholm, University of Helsinki “Jews, Northern Europe, and the synthetic data in business history“
Louis Hyman, Johns Hopkins University “Teaching AI and History”